Social media is used as a source of information and platform to discuss health care; however, there is little research on discussion of telehealth in social media. Past research has looked at individual platforms, but a comparison of discussion on two platforms (Reddit and Twitter) has not been performed. Understanding telehealth-related social media discourse and the differences between platforms may provide insights into how telehealth is characterized online and which platforms provide patient perspectives. The COVID-19 pandemic provides a unique case study to examine how social media users approached both Reddit and Twitter during an international health crisis. This study used natural language processing tools and two social media platforms to (1) characterize and contrast each platform's telehealth-related posts according to themes and (2) assess the frequency of telehealth and telehealth-related terms posts before and during the onset of the COVID-19 pandemic.We collected 6 years (2016 through 2021) of social media posts from Twitter and Reddit. The themes of the corpus were extracted using hashtags, subreddits, and Latent Dirichlet Allocation (LDA) and were analyzed using descriptive statistics.Both Twitter and Reddit showed exponential growth in the use of the term “telehealth” and telehealth-related terms in early 2020. The use of telehealth-related terms and discussion of COVID-19 coincided in both social media sites; however, other themes were discussed, including how to use telehealth. Reddit LDA clusters showed greatest usage of “telehealth” when associated with using or suggesting telehealth for receiving therapy, counseling, or psychoanalysis while Twitter focused on sharing telehealth news, products, and services.Twitter and Reddit had extensive growth in the use of telehealth-related terms after the COVID-19 pandemic. Twitter and Reddit showed themes connecting COVID-19 to telehealth, especially in reference to services, therapy, and counseling, however, Reddit had more discussion suggesting use of telehealth services or requesting peer insights into how to use telehealth as compared with Twitter, which appeared more focused on telehealth as a business or product. As discussed in their review of telehealth utilization during the COVID-19 pandemic, Garfan et al. note that the pandemic caused a great disruption in health care, including routine outpatient visits being cancelled, a decrease in the delivery of routine medical care, and a shortage of health care resources.4–7 Social media data have an outsized impact on health care due to its universal nature, allowing greater communication opportunities for those with health care issues.7–9Social media represents an explosive, disruptive communication and information sharing technology that has changed how people interact on topics from the most mundane meme to paramount life decisions. According to the Pew Research Center 2021 survey results, ∼70% of Americans use social media.11 Health care systems and researchers are tapping into social media as a big data tool for mining information and understanding patient perspectives on many health care-related topics.12–14In the United States, 80% of internet users use the web to search for health information, and a large proportion of these users turn to social media for information.15 Because of the transition to telehealth during the COVID-19 pandemic, social media became a communication tool for telehealth.2 Further, telehealth-related journal articles have seen explosive growth showing the interconnected nature of a global pandemic and the need for easy-to-access health care outside of clinics and hospitals.16 The user-generated content around COVID-19 can provide patient perspectives on their experiences related to telehealth.17Social media and telehealth became intertwined during the coronavirus disease pandemic (COVID-19). According to a recent COVID-19 and social media scoping review, “Social media became a crucial communication tool for information generation, dissemination, and consumption.”18 A few studies have employed social listening to understand how COVID-19 has impacted social media discussion around telehealth; the few studies that have assessed telehealth and social media are limited in time frame or focus entirely on Twitter.19–21Social listening, the technique of using social media user perspectives to learn about their thoughts on a subject, has been previously used in health care.19 Champagne-Langabeer et al. used five months of Twitter data focused on telehealth to understand the sentiment of “telehealth” and “telemedicine” posts. Results found that most posts were positive or neutral.20Massaad and Cherfan analyzed the geospatial distribution of tweets associated with telehealth during the pandemic but limited the analysis to 1 week at the beginning of the disease spread in the United States.21 Anderson et al. used 1 month of data in 2020 and 2021 to compare the social acceptance of the telemedicine industry due to COVID-19. The analysis used only Twitter data and found that the pandemic moved the discussion of telehealth from introduction of a service to widespread adoption.22Pollack et al. used over a year of tweets and also found that telehealth-related tweets were associated with positive sentiments.While we are starting to understand the impact of COVID-19 on telehealth, there is a lack of understanding of the difference between user discussion of telehealth-related terms on different social media platforms. This research is designed to help understand how Reddit and Twitter users are using social media, which may help provide insights into how targeted interventions can use social media to improve health.Therefore, this study used natural language processing tools and two social media platforms, Twitter and Reddit, to (1) assess the frequency of telehealth and telehealth-related posts before and during the onset of the COVID-19 pandemic and (2) characterize each platform's telehealth-related posts according to theme. Twitter and Reddit were chosen for this study for three reasons.First, these platforms are used as social media forums, and each can provide insights into user perspectives. Second, Twitter and Reddit provide a form of content tagging—Twitter uses hashtags and Reddit uses sub-forums called “subreddits.” Third, both platforms had robust Application Programming Interfaces (APIs), allowing researchers to access historical posts. Overall, this study aimed at providing novel insight into how telehealth-related terms were discussed in both Twitter and Reddit  and identifying trends in telehealth-related tweets and posts over the course of the COVID-19 pandemic.Twitter and Reddit data from January 2016 through December 2021 were used for this study. Twitter archives were accessed using the Twitter Academic Developer API. The Academic API allows researchers to access historical tweets. JavaScript Object Notation (JSON) formatted data were downloaded from the Academic API using twarc2 command line to search for specific terms in the Twitter archive.23 Both submissions and comments were downloaded and are collectively called “posts” in this analysis. The search terms for Twitter and Reddit were “Telehealth,” “Telemedicine,” “Remote Health,” “Distance Health,” “Connected Health,” “Mobile Health,” “mHealth,” “Virtual Care,” “Virtual Health,” “Digital Health,” “Electronic Health,” “Internet Medicine,” “eHealth,” and “Cybermedicine.” These terms were chosen after a scoping review was conducted to identify telehealth-related terms. Results from the scoping review were reported separately.24The twarc2 command included requests to exclude retweets and promoted-only advertisements (null cast). Reddit was accessed via the API Pushshift.io.Pandas was used to create data frames, which were saved as comma separated text files.25 There are two types of Reddit posts: submissions and comments. Reddit submissions have both a title and body, which were combined into one post. Redditors can post comments under a submission. Comments do not contain a title and did not require additional processing to create a post.Python 3.8.10 was used to access, clean, and analyze data . TwitterTweetTokenizer from the NLTK.tokenize toolkit was used to separate string text into lists of tokens to maintain hashtags and URL addresses.26 All tokens were converted to lowercase, and key phrases had spaces removed to maintain their meaning in one token. Stopwords, low information words, were removed from the list of tokens using NLTK.corpus stopwords in English.Tweets and Reddit posts were cleaned using natural language processing tools. Specifically, http.” This allowed for de-duplication of posts that had the same text but linked to different URLs. The URLs of tweets were converted to the string “Twitter uses hashtags (#) to allow for topic tagging. These tags provide insights into Twitter trends and provide natural self-categorization. As part of the cleaning process, COVID-19-related terms were grouped into the string “covid.” Grouped COVID-19 terms [after applying .lower to all strings] include the following: “covid-19,” “covid 19,” “sars cov 2,” “sars-cov-2.” Top hashtags were extracted using regex and grouped by search term. After cleaning and de-duplicating the tweets, descriptive statistics were run in Python and visualizations were created in Tableau 2020.2.17.Reddit posts are tied to a community called a subreddit. While subreddits are a form of classification, there are thousands of subreddits. The large population can limit the ability to understand broad themes. Latent Dirichlet Allocation (LDA) was used to generate a theme for each Reddit and Twitter post. LDA is a probabilistic model that represents posts as a distribution of topics.Gensim.models.LdaMulticore package was run with 20 passes and minimum_probability set to 0, which means that the machine should not filter out any of the generated topics.27The goal of LDA is to infer the topic distributions for each post by generating the most likely word distributions within that post's topic. num_topics was tested via coherence plots. Num_topics tells the machine how many clusters or topics to find in the Reddit posts that is decided by the user. Fine tuning of the number of topics hyperparameters tested numbers in the range from 10 to 100 by increments of 10. The package pyLDAvis was used to visualize the results of the LDA model.28 When visualizing the results, the parameter lambda was set to zero to see terms that were used often within each theme but not outside of that cluster.The hyperparameter sklearn manifold TSNE and visualized with the Bokeh library (Bokeh 2.2.3).29 The Bokeh packages io, models, and palettes were used to create an interactive scatter plot that allowed for filtering out years and a hover tool that showed the post text and LDA label via custom JavaScript. Analysis was performed on an NVIDIA DGX-1.Although LDA supplies topic labels, these labels may focus on words that do not pertain to health or may not be easily interpretable as a theme. To help solve this issue, a t-distributed stochastic neighbor embedding (t-SNE) plot to reduce dimensionality to two dimensions was created to visualize the posts and the clusters were analyzed both in the context of their LDA topic's list of words and by examining example posts or tweets from the cluster. The t-SNE was created using 30:In addition to studying the posts with t-SNE plots, the relevance metric of LDA was used to better understand topic clusters. The LDA's relevance metric helps when interpreting LDA results. This metric was created by Sievert and Shirely and is defined as followsp(w | t) and topic terms are ranked solely based on their probability of appearing within the topic. This means that common words throughout the corpus may appear in the topic words. When the relevance metric is set to 0, the metric is equal to p(w | t)/p(w) so terms are ranked based on how much more probable the word is to be found within the topic as compared with the entire corpus. The relevance metric at 0 terms may help distinguish from other topics. The default for LDA is to supply topic labels that use the relevance metric at 1.When the metric is set to 1, the metric is equal to The results include the analysis of 3,052,928 tweets and 109,634 Reddit posts, which will be referred to as social interactions. While total Twitter posts remained consistently higher than Reddit posts, the total number of social interactions containing telehealth-related terms remained somewhat stable in both platforms during the years 2016–2019. Tweets during those years fluctuated by ∼98,000 tweets, and Reddit posts fluctuated by 5043 posts. During the 2020 coronavirus pandemic, tweets jumped from around 350,000 tweets in 2019 mentioning “telehealth” terms to 850,000 tweets in 2020. The analysis of the telehealth-related search terms showed that Reddit posts discussed the term “telehealth” more frequently than any other term. That term was reported in 62% of the telehealth-related posts, followed by the term “telemedicine” reported in 15% of the telehealth-related posts. Reddit posts are submitted to online communities, known as subreddits. The topics of discussion in these subreddits for “telehealth” include therapy, advice, and world-markets/investments, with the most posts being in the “Psychotherapy” community.The topics of discussion in the subreddits for “telemedicine” focus on health care topics, with the top subreddit “Healthcare” focusing on insurance. The other topics of discussion include telemedicine, telehealth, technology interventions in health care, English-language Really Simple Syndication (RSS) feeds, and specific health topics including suboxone, testosterone, and Attention Deficit Hyperactivity Disorder (ADHD). An individual Reddit user who focuses on blockchain protocol for telehealth was listed as a top 10 subreddits for “telemedicine” because the term #telemedicine is repeated on every post of the user's profile page; however, as this was a Redditor's username, it was not included in The most commonly used Twitter hashtags for “telehealth” and “telemedicine” from January 2016 through December 2021 included #telehealth with 332,272 tweets and #telemedicine with 249,919 tweets. Other top hashtags included during this timeframe were #healthcare, #digitalhealth, #covid19, #healthtech, #mhealth, #health, #healhit, #ehealth, and #mentalhealth.Before the start of the pandemic, Twitter had constant use of the terms “m-health,” “e-health,” and “digital health.” In February 2020, telehealth-related tweets spiked when COVID-19 was declared a disease by the World Health Organization. While the term “telemedicine” showed an increase, the term “telehealth” exhibited a greater increase. In April 2020, the #covid19 hashtag quickly dropped from its high while the #telehealth hashtag declined and began to plateau.Reddit posts showed a spike in “telehealth” and other telehealth-related terms from January 2016 to December 2021. Before the onset of the pandemic, Reddit had little use of any telehealth-related terms. The term “telehealth” was the most commonly used term in this corpus, and unlike Twitter, telehealth-related posts appeared to show a renewed growth in September 2021.y-axis represents the coherence scores, with higher scores indicating a more interpretable topic.As shown in The top topics presented in As seen in the heatmap in The most common theme .41–43 Although not specific to telehealth, previous research has shown that social media and Reddit can be a “passive sensor” of mental health providing forecasting of mental health consultations.43 This may be indicative of Redditor's willingness to share health experiences in narratives submitted to Reddit.This narrative format provides Redditors with a pseudoanonymous platform that can be ideal for providing first-person experiences as seen in its use in mental health research.44 In addition, a Twitter sponsored survey found that almost 90% of Twitter users use the platform to find products and 76% have conversations on Twitter that lead to purchases.45 These Twitter-led insights may provide context on why so many business-related tweets were found in this telehealth corpus.The business-related tweets found on Twitter may be due to bots discussing products or trends with potentially 30% of tweets generated by bots.Several limitations exist with this study. Human language is not always explicit, and tweets or posts may discuss telehealth or COVID implicitly. These posts would not be captured by our analysis, as we queried the Twitter and Reddit APIs using search terms (string matches). In addition, these data were collected using keyword searches and may have missed posts that misspelled “telehealth” or “telemedicine.”Second, when comparing Twitter and Reddit, it is important to note the expectation of anonymity. Reddit provides users with a pseudonymous environment where posters can choose how much to divulge about themselves, sometimes maintaining complete anonymity. In comparison, Twitter exists in an environment that often relies on users providing their real names as exemplified by the Twitter blue checkmark that verifies a user's real identity.Our findings that users were more likely to use Reddit to learn how to use telehealth or to talk about their medical experiences may be a result of the anonymous nature of Reddit. Third, it is also possible that the use of telehealth-related terms was not indicative of a post that was describing the health care field of telehealth. Fourth, LDA is a model that only allows one topic per post, meaning that a post that describes two or more topics has to be placed in just one topic.46 It is also possible that the LDA topic label was not correct for the post, which is discussed more thoroughly later about future research. The LDA may also be difficult to interpret from a human readability perspective: the word co-occurrence the algorithm finds may include terms that are seen as irrelevant or confusing. While our research includes telehealth domain experts, we may not have interpreted the topic clusters correctly. Fifth, users of social media often represent a younger, computer-literate demographic, which is not representative of the diversity of the United States.This problematically may skew the percent each cluster covers.4 Twitter users are 22% White, 29% Black, and 23% Hispanic while Reddit users are 17% White, 17% Black, and 14% Hispanic. These results should not be generalized to the full United States population. Finally, Twitter announced that they will no longer support the Academic API as a free resource.47Specifically, according to a 2021 Pew survey, just below half of Twitter users are ages 18–29 while only 36% of Reddit users are ages 18–29.23 The use of cross-platform analysis may be integral to continuing the field of social media analysis as current platforms' use policies change or platforms are removed.Changes to the API and the transparency around access to Twitter could impact future social media research and reproducibility of past work. Reddit's API is maintained by an outside entity and is dedicated to archiving the platform for researchers.Future research should cement the themes found in social media and telehealth by manually codifying Twitter tweets and Reddit posts into topics that can be used to create an annotated dataset. This dataset can be used for the creation of a machine that will identify individual posts across the dataset and will allow for multiple labels on one post .These codes could be studied over time to see if the pandemic had changed how users discussed telehealth before and after the pandemic. Our study stopped data collection in 2021. Future research may want to include more recent data to understand if the themes outlined in this article continue or if new topic areas are introduced.In addition, the manual creation of labels could be compared with LDA to see if the LDA clusters had a similar distribution of themes. Past research often uses Twitter for the textual corpus; however, this study indicates that Reddit provides more information-rich context around health experiences of its users. Reddit may contain more patient experiences than Twitter, and further research exploring the quality of posts in this social media website could expand the field.This study may help provide researchers and policymakers with insights into the use of Reddit and Twitter in the context of telehealth-related discussion. Our hope is that insights can be derived to support the use of social media to facilitate the use of telehealth for health care needs, particularly psychotherapy and counseling needs.Future research may be able to build upon the themes and insights found in this work to directly impact supporting use of telehealth. Our study found that Reddit may be a more appropriate platform to discuss using telehealth or supporting forums to help Redditors understand access to telehealth especially as a tool to support mental health.Twitter and Reddit had extensive growth in the use of telehealth-related terms after the COVID-19 pandemic. While that growth has declined, telehealth-related terms are being used at a higher rate than before the pandemic. Users on both platforms used “telehealth” more than any other telehealth-related terms. The Twitter hashtag #covid was used in relation to #telehealth throughout the Twitter corpus. Twitter themes focused on telehealth appointments, telehealth increases due to the pandemic, and mental health.Reddit showed themes connecting COVID-19 to telehealth, especially in reference to therapy and counseling. This study also showed that Reddit is an additional forum for understanding how users are discussing and using telehealth and that Reddit posts provide more nuanced information as compared with Twitter, which can be skewed more toward business-related tweets.


The receiver operating characteristic area under the curve was 0.933 for the detection of BI-RADS 5 lesions. Furthermore, tumour grades 2  and 3  exhibited significantly higher SEPHmax than grade 1 tumours (4.0 ± 3.9 mm). Similarly, St. Gallen Ki67-stratified low-risk (p = 0.005) and intermediate-risk (p = 0.013) tumours showed smaller SEPHmax than high-risk tumours. Multivariate analysis revealed a significant correlation between malignant differentiation and SEPHmax  2.42–3.92], p < 0.0001), low tumour echogenicity , and higher patient age . High SEPHmax is a strong predictor for tumour malignancy and a higher tumour grade and can be used to improve tumour characterisation before histopathological evaluation. It may also enable radiologists to identify lesions warranting observation rather than immediate biopsy.To evaluate the diagnostic utility of the maximum ultrasound strain elastography (SE) halo depth in newly diagnosed and histologically confirmed breast lesions, a retrospective study approval was granted by the local Ethical Review Board. Overall, the maximum strain elastography peritumoural halos (SEPHmax)—the maximum distance between the SE stiffening area and the B-mode lesion size—in 428 cases with newly diagnosed breast lesions were retrospectively analysed alongside patient age, affected quadrant, tumour echogenicity, size, acoustic shadowing, and vascularity. Statistical analysis included an ordinary one-way ANOVA to compare the SEPHmax between BI-RADS 2, 3, and 5 groups and between tumour grades 1, 2, and 3. A binary regression analysis was used to determine the correlation between tumour malignancy and the above-mentioned demographic and imaging factors. SEPHmax was significantly higher in BI-RADS 5 tumours (5.5 ± 3.9 mm) compared to BI-RADS 3 (0.9 ± 1.7 mm,  Breast cancer is the most common malignancy in women at an incidence of up to 92 per 100,000 in highly developed countries, which keeps rising due to an increase in life expectancy [Women are encouraged to take part in regular mammography programmes to detect carcinomas at an early stage and to enable early and curative treatment. Such programmes have led to a relative reduction in mortality of up to 20% . NecessaEven though ultrasound detection rates in combination with conventional mammograms can reach substantial values of up to 92.6 to 94.4% , differeTissue elasticity assessment—elastography—has seen an increase in clinical interest over the last decade, as increased tissue stiffness has been linked to high cellularity and malignancy in some entities . While sThe aims of this retrospective study were to assess the diagnostic utility of the maximum ultrasound strain elastography (SE) halo depth in newly diagnosed breast lesions and to assess whether the maximum strain elastography peritumoural halo (SEPHmax) correlates with tumour differentiation, tumour grades, and (immuno)histology findings.Study approval for this retrospective study was granted by the Ethical Review Board on 21 July 2021 .n = 5), inconclusive histology (n = 1), or insufficient ultrasound documentation (n = 8)  . AccordiAll women in our second-level centre undergo a standardized ultrasound examination if referred for (1) routine or screening mammography in cases of breast density ACR C or D, or in case of (2) a suspicious finding upon mammography, (3) referral due to a suspicious finding upon clinical examination, or (4) referral from an extramural radiology practice due to suspicious imaging findings. Examinations were performed on an Acuson Sequoia, Acuson S2000 or S3000 Evolution US scanner with an 18–6 or 13.5 MHz high-resolution probe  encompassing a systematic scanning of the axillary and breast regions. Focal lesions were documented in two perpendicular planes to determine the relation to surrounding tissue, size, B-mode, and Doppler properties. SE was performed by repeated controlled compression of the tumour and the surrounding tissue. Compression quality was assessed by visual inspection and by the vendor-specific quality index. Only SE images with a high quality index  were used for further analysis. In addition, special attention was paid to ensure that the elastographic ROI was no more than a quarter in the chest wall in order to avoid any artefacts. Based on previously published criteria, lesions were graded according to U.S. BI-RADS criteria .On all lesions with an overall BI-RADS score of 4 or 5, and on some lesions with a BI-RADS score of 3, ultrasound-guided biopsies were performed following international guidelines . In shorHistopathological data were retrieved from the hospital’s clinical information system KIS PowerChart  after imaging data collection was complete. Histopathological and immunohistochemistry findings were taken primarily from full-resection reports or otherwise from CNB specimens. If any form of neoadjuvant therapy had been administered since initial diagnosis, the histopathological core needle biopsy reports were used instead. Similarly, lymph node status was determined from sentinel or full resection lymph nodes in cases of no neoadjuvant therapy. Otherwise, results from an initial core needle biopsy (if available) were used. In the absence of histologically proven lymph node metastasis, lymph node status was considered negative following the local tumour board consensus.max was measured in our in-house PACS image viewer  by (1) drawing the lesion outline in the B-mode image to accurately assess the tumour contour, (2) transferring it to the corresponding SE image in the dual-view mode, and (3) measuring the maximum SEPHmax depth of visual discernible elastographic perilesional stiffening regardless of orientation yet following the shortest line from the SEPH contour to the tumour surface. If the tumour could not fully be covered by the elastography box due to size or superficial position, then the elastography box was placed to cover a peripheral tumour section and at least 2 cm of surrounding tissue.Lesion dimensions were measured in two axes in B-mode images and automatically transferred to the accompanying elastogram window during initial imaging. SEPHAll data were stored in Microsoft Excel 16.16.21 . The statistical software used was R within RStudio 2021.9.1  and GraphPad Prism 9.3.1 .Descriptive statistics for all patients include demographic (age) and disease-related factors  as described above. Results include mean ± standard deviation (SD) and ranges in brackets or relative frequency  in brackets.max was compared between (a) BI-RADS 2, 3, and 5 (grouped by histopathologic results) and (b) tumour grades 1–3 (again grouped by histopathologic results) using a Kruskal–Wallis test with Dunn’s multiple comparison test.The SEPHmax were assessed by a linear regression analysis. Continuous predictors were mean-centred and scaled by 1 standard deviation (SD).The correlation between the covariates described above and SEPH2 test. Statistical significance was considered for p-values < 0.05.Continuous data of the groups were compared via an ordinary one-way ANOVA with a Holm–Sidak correction or Kruskal–Wallis test with Dunn’s post-test  to correct for multiple testing. If through log-transformation a Gaussian distribution could be achieved, data was transformed for analysis. Categorical variables were compared via pairwise Fisher’s exact test (in case of 2 × 2 tables) or a χMalignant tumours were grouped by Ki67 ranges  following the St. Gallen risk classification , and then = 175) were benign , 5.6% (n = 24) were of intermediate differentiation, and 53.5% (n = 229) were malignant. Among malignant tumours, grade 1 tumours constituted 23.8% (n = 43), grade 2 78.5% (n = 142), and grade 3 24.3% (n = 44). Lymph node metastasis was present in 18.3% (n = 42). The maximum tumour diameter was 15.4 ± 9.0 mm on average (range 2.9 to 57.3 mm). Lesions were mostly located in the upper outer quadrant , followed by the lower outer  and upper inner quadrant . For an overview, please refer to The average age of the 428 patients included was 56.0 ± 16.5 years. Of all 428 tumours, 40.9% , as well as elastographic ROI y-dimensions , and negatively with minimum skin distance , chest wall distance , and if a significant portion of the chest wall was in the elastographic ROI  (SEPH= 0.016) .max than intermediate  or benign breast lesions . No significant difference was encountered between benign and intermediate lesions (p > 0.9999) (max was significantly higher. While no significant difference was found between grades 2 and 3 (p = 0.43), grade 1 elastographic halo depth (4.0 ± 3.9 mm) was significantly lower than in grade 2  and grade 3   had a significantly higher SEPH 0.9999) a. Furthe 0.0001) b. Pleasep = 0.005) and intermediate-risk tumours (p = 0.013) had a significantly lower SEPHmax than high-risk tumours .Furthermore, after Ki67 stratification, low-risk , as were low lesion echogenicity  and higher patient age . Visual assessment of lesion stiffness , affected quadrant , tumour vascularity , acoustic shadowing , width/height coefficient , and maximum tumour size  did not show a significant correlation  and 90.5% specificity (85.57% to 93.80%) for the identification of a malignant breast lesion. The ROC AUC was 0.93  lexicon, several U.S. imaging features portend to a malignant and more aggressive breast-cancer phenotype; among those are irregular shape, angular or spiculated margins, antiparallel orientation, and posterior shadowing with or without an echogenic halo . FurtherTo improve the diagnostic accuracy of ultrasounds and more reliably identify lesions warranting further histological workup, elastography has seen increased use in breast ultrasounds in the past decade. While shear wave elastography has become more common in recent years , the maiA clear difference regarding the maximum extent of peritumoural stiffening between benign, intermediate, and malignant lesions could be shown. Furthermore, higher tumour grades were associated with greater maximum SE halo depth.At the root of this peritumoural reduction in tissue elasticity, several interface processes between the host and the malignant tissue have been discussed , includiIn contrast to Zhou et al. , we founmax should raise the suspicion of an aggressive tumour variant.Besides the significant correlation of malignant lesion differentiation and the maximum SE halo depth, the evaluation of the halo depth may correlate with further tumour properties such as the Ki67 index. We could demonstrate that high-risk tumours with a Ki67 value > 30% have a significantly higher strain halo depth . According to the St. Gallen international consensus guidelines , systemimax, which correlated significantly with malignant lesion differentiation, low lesion echogenicity and increased patient age were significant diagnostic markers for the differentiation of benign and malignant entities, in line with previous literature [Besides SEPHterature . Visual There are some limiting factors to this study. Firstly, the study was done in a single imaging centre with only three models of ultrasound machines from the same vendor; therefore, multi-centre, larger scale studies with a variety of ultrasound machines should be conducted to rule out vendor and centre-dependent biases and potentially identify improvements to our approach. Secondly, SE is known to be user dependent, which may influence results based on applied pressure and relaxation, potentially influencing halo results. Third, some entities such as encapsulated papillary carcinomas (EPC) with a low invasive potential and lower production of invasion-associated markers  ,32 may nmax appears to be a promising diagnostic tool in the classification and characterisation of newly diagnosed breast tumours, since the SEPHmax was significantly higher in BI-RADS 5 tumours (5.5 ± 3.9 mm) compared to BI-RADS 3 (0.9 ± 1.7 mm) and BI-RADS 2 (0.6 ± 1.4 mm). Furthermore, the assessment of the peritumoural halo allows conclusions to be drawn about the underlying tumour properties such as the Ki67 value. Low-risk tumours have a significantly lower SEPHmax compared to intermediate and high-risk tumours with a cut-off value of 3.3 mm. Therefore SEPHmax may offer a tumour-size-independent preliminary assessment of tumour aggressiveness and may enable radiologists to identify lesions warranting observation rather than immediate biopsy. It has several advantages over other imaging techniques, including non-invasiveness, availability, and short acquisition time. Further research is needed to validate these findings and to determine the optimal protocol for peritumoural halo measurement in breast cancer diagnosis and management.Assessment of SEPH


Tumour vasculature is known to be aberrant, tortuous and erratic which can have significant implications for fluid flow. Fluid dynamics in tumour tissue plays an important part in tumour growth, metastasis and the delivery of therapeutics. Mathematical models are increasingly employed to elucidate the complex interplay between various aspects of the tumour vasculature and fluid flow. Previous models usually assume a uniformly distributed vasculature without explicitly describing its architecture or incorporate the distribution of vasculature without accounting for real geometric features of the network. In this study, an integrated computational model is developed by resolving fluid flow at the single capillary level across the whole tumour vascular network. It consists of an angiogenesis model and a fluid flow model which resolves flow as a function of the explicit vasculature by coupling intravascular flow and interstitial flow in tumour tissue. The integrated model has been used to examine the influence of microvascular distribution, necrosis and vessel pruning on fluid flow, as well as the effect of heterogeneous vessel permeability. Our results reveal the level of nonuniformity in tumour interstitial fluid pressure (IFP), with large variations in IFP profile between necrotic and non-necrotic tumours. Changes in microscopic features of the vascular network can significantly influence fluid flow in the tumour where removal of vessel blind ends has been found to reduce IFP and promote interstitial fluid flow. Our results demonstrate the importance of incorporating microscopic properties of the tumour vasculature and intravascular flow when predicting fluid flow in tumour tissue. Fluid flow in tissue plays an important role in the delivery of oxygen, nutrients and therapeutic agents. The physiology of tumour tissues exhibits several distinct features that influence fluid flow which can potentially promote tumour invasiveness and limit drug delivery. As tumours grow beyond the limit at which preexisting vasculature is able to sufficiently deliver blood, hypoxia develops which can trigger angiogenesis  shunts where short, low-resistance and high-flow pathways form in close proximity to the feeding vessels. A consequence of these AV shunts is that blood preferentially passes through them due to a large pressure gradient, hence blood can completely bypass the entire capillary network. In the vascular networks described in et al. et al. Intravascular and interstitial pressure distributions across the vascular and interstitial space were calculated as described in the Methods section. Initially, cases of tumours with varying degrees of necrosis as described in z = 3000 μm) in the tumour tissue. IFP at this location is highest in the central tumour region reaching a peak of 11 mmHg which then drops rapidly moving away from the tumour center where a pressure of around 2.5 mmHg is calculated at the tumour surface. This IFP profile corresponds with experimental and modelling based studies in the literature and further justifies the validity of the model in capturing the flow dynamics in tumour tissue. It is clear that the IFP profile is sensitive to the degree of necrosis, with a pronounced reduction in IFP in the avascular core in the 26% necrotic tumour. This is not so apparent in the tumour with 3% necrosis where high pressures are still seen in the tumour core, but with a slightly lower magnitude compared to the highest pressure found towards the periphery of the tumour. In the 26% necrotic tumour, IFP at the tumour center is significantly lower than the highest pressure distributed at the tumour periphery. The necrotic tumours exhibit pressure profiles that differ from the non-necrotic tumour.The vascular networks examined so far feature a number of blind ends that may affect the pressure drop and flow in the vascular network. To quantify this effect, the tumour vascular geometries were modified by removing several blind ends to open up the pathways for flow. To achieve this, the blind ends were identified within the network, which were then either removed or assigned as venous end vessels depending on their order within the network. Likewise, an AV shunt was also placed in a region near the arterial vessels. The macroscopic properties of the tumour microvasculature are similar as seen in z = 3000 µm), which displays a similar profile but much lower IFP in the pruned network. These findings suggest that although the vascular distribution and macroscopic parameters of the vasculature in the tumour tissue are almost similar between the original and pruned networks, microscopic changes such as the removal of blinds and addition of AV shunts can significantly alter the flow dynamics in the vasculature and consequently in tissue space.To examine the effect of vessel adaption on fluid flow in tumours, the vessel remodelling framework was applied. This was achieved by discretizing the time over which the vascular network grew and calculating the corresponding fluid flow at each time point. Shear stress and time were used as input data to simulate changes in radius, pore size and wall thickness. The evolution of the vascular network with time is shown in In this work, a mathematical model was developed where the tumour vascular network is described at a microscopic level on the whole tumour scale and is integrated with Pozrikidis’s fluid flow model to investigate the flow dynamics in tumour tissue. The angiogenesis model was extended to 3D which made it possible to capture the explicit distribution and geometry of the tumour vasculature and its abnormal features. The tumour model was coupled to a fluid flow model which has a distinct advantage of enabling vascular and interstitial flow to be strongly coupled through integration of flow in the vessels and interstitial space over the vessel surface, to provide approximations for fluid flow and transvascular flux that are grounded in physical reality. By applying fluid flow-based boundary conditions on the vessel wall and integrating the pressure over the vessel surface, explicit morphological features of the vasculature including each vessel’s orientation, radius and length can be incorporated. The model was integrated with a vascular remodelling framework that allows for vessel permeability to vary depending on their maturity and local shear stress. The integrated angiogenesis and fluid flow model was evaluated by comparing the obtained morphological and hemodynamic parameters with data in the literature, demonstrating a good agreement.et al. who investigated the distribution of molecules delivered intravenously in subcutaneous RG-2 tumours , fibronectin concentration (f) and tumour angiogenic factor concentration (c), which describing vascular growth are given below:The tumour model is generated to provide an explicit representation of the tumour vasculature at a microscopic scale. The extravascular space is assumed to consist of uniformly distributed cancer cells and extracellular material. To generate the explicit tumour vasculature, Anderson and Chaplains mathematical angiogenesis model is implemented , movement along the x-axis , movement along the y-axis , and along the z-axis . The magnitude of the probability coefficients depends on local TAF and fibronectin concentrations. At each time step the seven probability coefficients are calculated to produce seven ranges between each coefficient. A random number is generated between 0 and 1 and the movement of the endothelial cell depends on the range where the random number falls. Hence, the movement of the tip endothelial cell is based on three components: random, chemotactic and haptotactic movement. Branching and anastomosis are common features in tumour vasculature, and these are represented following the approach of Anderson and Chaplain th generation can be modelled as monotonously decreasing as follows:In order to apply the fluid flow model to the vascular network generated from the angiogenesis model, the geometry of the network must be regulated and further defined. First, nodes are assigned to coordinates where tip merging or branching occurs and where the tips initially sprout and end. Then further nodes are created along the path that the tip moves. A connection matrix logging the connectivity between the nodes is formed based on the data from the raw vascular network generated. A depth-first search algorithm is then used to move down from the initial node, creating segments based on the connection matrix. To define the diameter of the vessels, a maximum diameter is set at the initial parent vessels which are assumed to be maintained for subsequent vessels down the network, except in the case where branching or merging occurs. When this occurs the diameter of the daughter vessel is assumed to decrease in size. The change in radius from a vessel of the m is a coefficient less than 1. Applying the vascular regulation algorithm to the networks generated from the angiogenesis model yields the vascular geometries shown in where et al., which provides a framework to model changes in vascular structure in response to stimuli . The interstitial pressure at point The interstitial space is discretized and the single- and double-layer potentials 3, which was discretized into a structured grid with uniform spacing of 150 μm along each orthogonal axis. Using this hardware and discretization parameters, each simulation of vascular network took approximately 90 s. The system of linear equation generated in the fluid flow model was solved in MATLAB to resolve vascular and vessel surface IFP. The tissue space was discretized into a structured grid with a uniform spacing of 85 μm where at each point the IFP was determined as described in Eq. 30.The angiogenesis and fluid models were implemented in MATLAB and computations were performed using a 64-bit Intel (R) Core (TM) processor (3.40 GHz) with 64 GB RAM. The computational domain was 6 × 6 × 6 mmL = 1.5 mm is assumed in this study.The parameters used to model the tumour geometry are given in Vessel hydraulic conductivity is based on the ability of the vessel to allow fluid movement across the vessel wall. Capillary filtration measurements in rat implanted tumours showed hydraulic conductivity values ten times higher than those reported in normal tissue. Vessels in the normal and tumour tissue region were prescribed vessel hydraulic conductivities. A summary of key parameters used in fluid flow simulations are given in Vt), vascular density (Vd), length density (LD), vessel surface to volume ratio (S/V), and maximum extravascular diffusion distance (R), were determined , mean shear stress (τij), vascular segment transit time (VSTT), and flow weighted mean path length (MPL), were calculated to validate the fluid flow model:where Moath Alamer and Xiao Yun Xu declare that they have no conflict of interest.


Radio/chemotherapy and immune systems provide examples of hormesis, as tumours can be stimulated (or reduced) at low radio/chemical or antibody doses but inhibited (or stimulated) by high doses.Interactions between effector cells, tumour cells and cytokines with pulsed radio/chemo-immunotherapy were modelled using a pulse differential system.Our results show that radio/chemotherapy (dose) response curves (RCRC) and/or immune response curves (IRC) or a combination of both, undergo homeostatic changes or catastrophic shifts revealing hormesis in many parameter regions. Some mixed response curves had multiple humps, posing challenges for interpretation of clinical trials and experimental design, due to a fuzzy region between an hormetic zone and the toxic threshold. Mixed response curves from two parameter bifurcation analyses demonstrated that low-dose radio/chemotherapy and strong immunotherapy counteract side-effects of radio/chemotherapy on effector cells and cytokines and stimulate effects of immunotherapy on tumour growth. The implications for clinical applications were confirmed by good fits to our model of RCRC and IRC data.The combination of low-dose radio/chemotherapy and high-dose immunotherapy is very effective for many solid tumours. The net benefit and synergistic effect of combined therapy is conducive to the treatment and inhibition of tumour cells.The online version contains supplementary material available at 10.1186/s12885-023-11542-6. As the growth and inhibition mechanisms of cancer cells are still not fully understood, cancer remains one of the leading causes of death in the world. Therefore, a variety of therapeutic measures against tumours have been proposed, the most typical of which are radiotherapy, chemotherapy, immunotherapy, virus therapy or combinations of two or more of these treatments –3. ImmunRadiation hormesis and the implications of low-dose radiation applications in cancer risk assessment have been investigated by numerous researchers –12, 20. An effective way to solve these challenging problems is to use combination therapy: combining radio/chemotherapy with immunotherapy can be a promising and synergistic option to treat many cancer types , 4, 5, iWe used values for the parameters from the literature and numerical bifurcation analysis techniques to reveal the parameter space and the mechanism of the paradoxical and hormetic effects produced by radio- and/or chemotherapy, immunotherapy and combination therapy. The main results revealed that the RCRC, IRC and MRC undergo homeostatic changes or catastrophic shifts and show hormetic effects in many parameter regions. The resultant discoveries of a “mixed fuzzy region” between the hormetic zone and the toxic threshold and MRCs with multiple humps bring new challenges for the design and interpretation of clinical trials of anti-tumour therapies. For combination therapy, the main conclusion is that low-dose radio/chemotherapy and high-dose immunotherapy can effectively inhibit the growth of tumour cells, or even eradicate them. The results have implications for potential clinical applications, which we have confirmed by fitting our model to RCRC and IRC data sets.We modelled the interactions between effector cells , both at period P. To determine if this is possible, let the number of tumour cells The ideal outcome of integrated therapies against tumours is to eradicate the tumour cells. This can be realized, from a mathematical point of view, provided that model (1) exists with a stable periodic solution, denoted by In order to reveal the RCRC and/or the IRC implied by the dynamics of model (1), we focus on two cases: 1) Monitoring the outcomes of combination therapy simultaneously, i.e. we monitor the number of effector cells . The tumour cells’ intrinsic reproductive capacity is not fully expressed under natural conditions, but a low dose radio/chemotherapy perturbation may result in hormetic effects such that the tumour size is pushed beyond its previous homeostatic state to a new larger equilibrium . Moreov}Tn Fig. a shows tModel (1) exists with bi-stable regions for a wide range of parameters, which correspond to the hormetic zone and toxic threshold. Thus, a bi-stable region poses new challenges in determining the hormetic zone and toxic threshold, which can change over a wide range of doses and depends strictly on the initial values of effector cells, tumour cells and cytokines. In particular, the existence of bi-stable regions causes the hormetic zone and toxic threshold to have a “fuzzy region”, that is, different clinical trial conditions or small randomness may lead to a large deviation in the monitored hormetic zones and toxic thresholds. Therefore, the bi-stable region can also be referred to as the “mixed fuzzy region” of the hormetic zone and toxic threshold. More detailed bifurcation analyses with respect to four key parameters on” Fig. . Among ton” Fig. f. The siWhen ses Fig. i and j. mentclasspt{minimamentclasspt{minimaOne-parameter bifurcation diagrams for RCRCs or IRCs reveal that dosages of radiation, chemotherapy and immunotherapy have important impacts on the occurrence of paradoxical and hormetic effects. To address this, we employed the two base line parameter sets mentioned above and chose the instant killing rate Intuitively, when radio/chemotherapy does not have side-effects on effector cells and cytokines, high-dose radio/chemotherapy and strong immunotherapy are conducive to the inhibition or even eradication of tumour cells Fig. a. For a ous Fig. c, which The dual effects of radio/chemotherapy on cytokines show that the combined treatment can inhibit cytokine growth during treatment for some tumours, while stimulating their growth during the treatment for some other tumours , 31. TheFor a fixed intensity of radio/chemotherapy : the maximum responses are essentially different, and the mixed fuzzy regions also change slightly, as shown in Fig. S.4. This indicates that the RCRCs can be significantly affected if we record the number of tumour cells at different time points. However, the values of Various anti-tumour cytokines and experimental designs could result in positive or negative signs of parameter ur cells , 31, achur cells .n in two independent random simulations. The final fates of each complete trajectory corresponding to the number of tumour cells is very clear in Fig. Two independent simulations with random initial values and random generated parameters ,nP Fig. a and c. As emphasized in the methods section, we employed the mean value of stable states of the tumour cells in system (1) to fit the RCRC or IRC data sets shown in Fig. Although the modes of action and synergies involved in administering immunotherapy with radiotherapy or chemotherapy are unexplained, it is however clear that such combinations are effective against a variety of cancers , 4–6. HeThe mechanisms involved in this synergy and the clinical implications of RCRCs and/or IRCs of cancer are not yet clear, but there are potential considerations that could either benefit or harm cancer patients. The model revealed that the RCRC and/or the IRC or a combination of the two, termed a mixed response curve (MRC), undergo homeostatic changes or catastrophic shifts and have hormetic effects in many parameter regions. Some of the MRCs have multiple humps which pose challenges for the interpretation of clinical trials and for experimental design, due to a fuzzy region between an hormetic zone and the toxic threshold. MRCs generated by two parameter bifurcation analyses based on radio/chemotherapy and immunotherapy revealed that low-dose radio/chemotherapy and strong immunotherapy can counteract the side-effects of radio/chemotherapy on effector cells and cytokines, as well as stimulating effects of immunotherapy on tumour cell growth. Thus, the net benefit and synergistic effect of combined therapy is conducive to the treatment and inhibition of tumour cells and the implications for potential clinical applications were confirmed by fitting our model to RCRC and IRC data sets.The conclusions of the mathematical model and numerical analysis method developed here are consistent with those revealed by many experiments –12, 20, Whilst the conclusions from our model are optimistic insofar as they show that combination therapy with appropriate parameter values can have net benefits rather than fail, there are some caveats. One of these is the danger of cytokine release syndrome, potentially causing fever and organ failures , that caLow dose radio/chemotherapy has dual effects in the regulation of immune hormesis Fig. , but to As the initial paper to study all kinds of treatment-induced paradoxical and hormetic effects by using the kinetic model, the limitation of this paper is that we only considered the key role played by dose and synergistic effects, and did not systematically study the effect of timing of radio/chemotherapy relative to active immunotherapy on the RCRC, IRC and MRC. Moreover, the model results have not been tested by pre-clinical experimental cell culture or animal models. However, experiments have shown that there is a delay between the initiation of chemotherapy and its immunosuppressive properties becoming evident , 4, 35. Additional file 1:Supplementary Material. Hormesis and synergistic e_ects of cancer treatments revealed by modeling combinations of radio- or chemotherapy with immunotherapy.


For many years, community pharmacies provided mail delivery as a convenience for a small segment of special circumstance patients who requested it. Fueled by a movement among plan sponsors and prescription benefit managers to encourage or require its use, growth in mail service pharmacy began to accelerate in the 1980s and now accounts for nearly 25% of the market in the general population and a much higher percentage of seniors.To assess the attitudes of Medicare-eligible Americans toward concerns that have been raised about mail service pharmacy and its mandated use in the prescription benefit plans of public and private insurance programs.Existing published literature was reviewed, and interviews were conducted with Medicare-eligible persons aged 65 and older to identify potential areas of concern with mail order pharmacy services. A survey was constructed and mailed to a nationally representative random sample of 6,500 persons between the ages of 65 and 79 in July 2012.By the cutoff date, 669 completed surveys had been received, and an additional 221 had been returned as undeliverable, resulting in an overall response rate of 10.7%. Nearly half of respondents listed chain pharmacy as their primary source of prescription medications (47.7%) followed by mail service (34.1%), independent pharmacy (13.1%), and other (5.1%). Responses of seniors residing in rural zip codes compared with those in nonrural zip codes demonstrated significantly higher agreement with several concerns, including lost or stolen medications, receiving the exact medication the physician prescribed, and the effects of exposure to heat, cold, or moisture. Two additional concerns approached statistical significance: the ability to speak with a pharmacist face-to-face and the ability to obtain medications quickly if needed. A total of 533 (83.7%) indicated they would oppose mandated mail order in their current benefit plan if it would cause the local community pharmacy they rely on for immediate medication needs to close. The mean risk of such an eventuality that respondents were willing to accept was 42.2%, indicating they would oppose mandatory mail order if there were greater than about a 4-in-10 chance it would cause the loss of their local pharmacy.Seniors appear to be practical and pragmatic about the sources of their prescription medications. While most see a role for mail service pharmacy, they are also aware of its limitations. Many have needs they believe cannot be adequately met by mail service or have relationships with local pharmacies and pharmacists they believe are important for maintaining their health and well-being. As a result, seniors are relatively risk averse when it comes to the loss of their local community pharmacy, even if they routinely use mail order for most of their medications. Beyond their specific concerns, most seniors oppose any restrictions on their freedom to use the pharmacy of their choice on general principle.


Thaumatotibia leucotreta is a phytosanitary pest in the South African citrus industry, with the baculovirus Cryptophlebia leucotreta granulovirus (CrleGV) being one of the components that can control this pest. Several yeast species were shown to be associated with T. leucotreta larvae, which affected their behaviour and development. A series of detached fruit bioassays were performed to determine whether the combination of yeast with CrleGV enhances its efficacy. These assays included determining the optimal yeast/virus ratio, testing all isolated yeast species in combination with CrleGV, and further improving yeast/virus formulation by adding an adjuvant. The optimal yeast concentration to use alongside CrleGV was determined to be 106 cells·mL−1. Pichia kluyveri, P. kudriavzevii, Kluyveromyces marxianus, and Saccharomyces cerevisiae in combination with CrleGV reduced larval survival compared to CrleGV alone. The addition of molasses and BREAK-THRU® S 240 to P. kudriavzevii and S. cerevisiae in combination with CrleGV did not notably improve their effectiveness; however, there was an observed decrease in larval survival. In future studies, field trials will be conducted with combinations of CrleGV and P. kudriavzevii or S. cerevisiae to investigate whether these laboratory findings can be replicated in orchard conditions.Yeasts associated with lepidopteran pests have been shown to play a role in their survival, development, and oviposition preference. It has been demonstrated that combining these yeasts with existing biological control agents can enhance their efficacy. The tortricid  Thaumatotibia leucotreta (Meyrick) (Lepidoptera: Tortricidae)  is a significant pest of the South African citrus industry and other citrus-producing regions throughout sub-Saharan Africa [T. leucotreta populations in South African orchards [T. leucotreta is now primarily a phytosanitary risk rather than a destructive crop pest, with zero tolerance in the European Union and other export markets [n Africa . The feen Africa . Improveorchards . However markets .T. leucotreta, including chemical, biological, cultural, and pheromone-based methods [T. leucotreta, beginning early in the season [T. leucotreta in South Africa, most notably baculoviruses [Several control options are available to manage  methods ,4. Treate season ,6. IPM pe season . A numbeoviruses ,8.T. leucotreta throughout South Africa [The baculovirus Cryptophlebia leucotreta granulovirus (CrleGV) has been extensively used for more than 15 years to control h Africa ,9. Despih Africa ,9,10,11.T. leucotreta [While CrleGV is an effective biological control agent against ucotreta , continuucotreta . Effortsucotreta ,13. Addiucotreta ,14. Receucotreta .Cydia pomonella (Linnaeus) (Lepidoptera: Tortricidae) neonates, but they have primarily appeared to facilitate host location rather than stimulate feeding behaviour [Cydia pomonella larvae have a close affiliation with yeasts from the genus Metschnikowia, which were isolated from their gut and feeding galleries. Larval feeding assays demonstrated that M. andauensis positively impacted C. pomonella larvae, accelerating their development and lowering mortality rates. Volatiles produced by M. andauensis also elicited upwind flight in adult C. pomonella females, which resulted in an increased number of eggs being oviposited on apples that had been inoculated with yeast [C. pomonella larvae, with CpGV occlusion bodies (OBs) noticeably improved the virus’s efficiency, both in controlled laboratory experiments and in practical field applications [Metschnikowia actively promoted larval feeding and facilitated the ingestion of CpGV [Saccharomyces cerevisiae in commercial use, its combination with CpGV was also evaluated. Larval mortality recorded in CpGV assays using S. cerevisiae closely resembled that of yeasts isolated from C. pomonella larvae [Previous attempts to enhance Cydia pomonella granulovirus (CpGV) performance through the combination of feeding stimulants and larval attractants have not yielded definitive improvements ,16,17. Tehaviour ,19. Micrehaviour . The sigehaviour ,22. Cydith yeast . The comications . Yeasts  of CpGV ,23. Furta larvae .T. leucotreta larvae collected from citrus orchards across South Africa. This led to the identification of six yeast species: Meyerozyma guilliermondii, Pichia kluyveri, Pichia kudriavzevii, Hanseniaspora uvarum, Clavispora lusitaniae, and Kluyveromyces marxianus [M. guilliermondii, H. uvarum, and P. kluyveri accelerated larval development and reduced mortality, while P. kluyveri, H. uvarum, P. kudriavzevii, and K. marxianus were shown to influence the feeding preference of neonate T. leucotreta in larval feeding assays. Additionally, the oviposition preference of adult T. leucotreta females was affected by M. guilliermondii, P. kudriavzevii, and H. uvarum, with an increased number of eggs being oviposited on Navel oranges inoculated with these yeasts.A recent study aimed to identify yeast species present within the digestive tract of arxianus . Larval T. leucotreta larvae increase the efficacy of CrleGV when combined. Furthermore, the addition of an adjuvant (molasses) to improve the yeast/virus mixture efficacy was analysed.Yeast strains hold promising potential as abundant sources of novel biological agents that can be harnessed for the augmentation and improvement of established control agents. In this study, we aimed to determine whether previously isolated yeast species associated with Thaumatotibia leucotreta eggs were obtained from the heterogeneous culture, known as “Mixed Colony”, held at Rhodes University’s Department of Zoology and Entomology, South Africa. Eggs were stored in Petri dishes sealed with parafilm in a 25 °C controlled environment (CE) room with a relative humidity of 30–60%. Once the eggs had turned dark brown, a piece of cotton wool moistened with double distilled water (ddH2O) was placed in the Petri dish to ensure that emerging T. leucotreta neonates did not dehydrate before being used.50 concentration of 9.31 × 107 OBs·mL−1 for all treatments [50 concentration was selected as this would result in 50% mortality of the T. leucotreta population.Three sets of detached fruit bioassays were conducted to (i) determine the optimal yeast concentration to use in combination with CrleGV, (ii) assess the effectiveness of combining each of the isolated yeasts with CrleGV, and (iii) evaluate the efficacy of the yeast/virus mixture through the addition of an adjuvant and surfactant. CrleGV was applied at an LCeatments . The LC5v/v), rinsed twice in ddH2O, and allowed to air dry in a 25 °C CE room overnight.Batches of Navel oranges were collected from orchards in the Sunday’s River Valley in the Eastern Cape Province of South Africa. No postharvest treatments had been applied to the oranges. The Navel oranges were stored in a 4 °C cold room to preserve the fruit until use. The oranges were checked weekly, with fruit showing any sign of disease or mould being discarded. Oranges were stored for a maximum period of 6–8 weeks. Navel oranges were removed from 4 °C cold storage one day prior to being used in a detached fruit bioassay. They were inspected for any sign of disease or mould before being thoroughly washed in a 0.5% bleach solution (−1 of penicillin (Pen) and 40 µg·mL−1 of streptomycin (Strep)  for 20 h at 27 °C while shaking. Cell counts were adjusted appropriately with ddH2O.Yeast cultures were grown in a Yeast extract Peptone Dextrose (YPD) medium containing 40 units·mLT. leucotreta. The first set of bioassay treatments included a ddH2O control, CrleGV alone, P. kudriavzevii at 2 × 108 cells·mL−1 plus CrleGV, P. kudriavzevii at 2 × 106 cells·mL−1 plus CrleGV, and P. kudriavzevii at 2 × 104 cells·mL−1 plus CrleGV. A yeast concentration of 108 cells·mL−1 was selected as a starting point based on prior research on yeast/virus synergism in C. pomonella [Pichia kudriavzevii was selected as the yeast isolate to use during these bioassays due to its attractiveness to T. leucotreta neonates and adult females [M. guilliermondii, P. kluyveri, H. uvarum, and K. marxianus with CrleGV. Saccharomyces cerevisiae was also included as a treatment, as it forms part of the artificial diet on which T. leucotreta larvae are reared [6 cells·mL−1 with CrleGV at 9.31 × 107 OBs·mL−1, as it was previously shown to be the optimal yeast/virus ratio. Finally, detached fruit bioassays were conducted to enhance the efficacy of the yeast/virus mixture by adding molasses and BREAK-THRU® S 240, as these have been shown to enhance the efficacy of the virus in field trials [Pichia kudriavzevii was selected because it has been shown to influence T. leucotreta neonates and adult female behaviour [Saccharomyces cerevisiae was included, as it is a commercially available yeast strain and has previously been shown to enhance the efficacy of CpGV [2O control, CrleGV, P. kudriavzevii (at 2 × 106 cells·mL−1) plus CrleGV, and S. cerevisiae (at 2 × 106 cells·mL−1) plus CrleGV, each with an adjuvant (molasses) and surfactant (BREAK-THRU® S 240)  at 0.25% and 0.005%, respectively.A modified version of the detached fruit bioassay described by Moore et al.  was usedomonella . Pichia  females . The sece reared . Yeasts  of CpGV . The thiT. leucotreta neonates were placed on each fruit. Thirty Navel oranges were used per treatment, with each treatment replicated three times. Detached fruit bioassays were run for 14 days, after which the Navel oranges were dissected and inspected for the presence or absence of live T. leucotreta larvae.Navel oranges were placed onto a sterile metal rack and sprayed with a specific treatment until runoff using a handheld sprayer. The treated oranges were subsequently positioned on a platform with none of the fruit coming into contact with each other, transported to a 25 °C CE room and allowed to dry for 30–45 min. Five T. leucotreta larval survival. The data from the three experiments were individually analysed, as each experiment was conducted sequentially. The GLMM was specified using a binomial error distribution and a logit link function. Significant differences in larval survival between treatments were assessed using likelihood ratio tests. Where significant differences were found, pairwise comparisons were performed using the “emmeans” R package and were adjusted for multiple comparisons using Tukey adjustment [A generalized linear mixed model (GLMM) was utilised to determine whether the inclusion of yeast to CrleGV impacted justment . All stajustment . Graphs 2 = 62.525, df = 4, p < 0.001). The application of P. kudriavzevii at a concentration of 2 × 108 cells·mL−1  in combination with CrleGV did not result in a significant reduction in larval survival when compared to the use of CrleGV alone. However, when P. kudriavzevii was applied at concentrations of 2 × 106 cells·mL−1  and 2 × 104 cells·mL−1 , it led to a notable decrease in larval survival by 23.33% . In comparison to the use of CrleGV alone, the inclusion of P. kluyveri, K. marxianus, and S. cerevisiae alongside the virus resulted in reductions in larval survival by 25.01% , 27.24% , and 21.68% , respectively  and H. uvarum  did not significantly reduce larval survival when applied in combination with CrleGV compared to the virus alone. All treatments were significantly different from the ddH2O control treatment.There was evidence for a statistically significant difference in larval survival between treatments . The addition of molasses and BREAK-THRU® S 240 did not significantly enhance the efficacy of P. kudriavzevii  or S. cerevisiae  formulations compared to CrleGV alone . All treatments were significantly different from the ddH2O control treatment.There was evidence for a statistically significant difference in larval survival between treatments  associated with C. pomonella [Saccharomyces cerevisiae was included here, due to its commercial availability and inclusion in the artificial diet used to rear T. leucotreta [S. cerevisiae. However, M. guilliermondii and H. uvarum did not enhance the efficacy of CrleGV. The positive effects of their ingestion on the development and survival of T. leucotreta larvae may have reduced the effectiveness of CrleGV at the LC50 dose [Previous studies have shown that neonate arxianus . Specifirevisiae . These ccumented ,40,41. Tomonella . Saccharucotreta . A signiC50 dose .T. leucotreta larvae penetrate the fruit’s rind, they are unlikely to ingest any additional OBs [® S240 was included as it decreases the surface tension of spray droplets, leading to enhanced retention and deposition of spray treatments [® S240 to P. kudriavzevii and S. cerevisiae plus CrleGV treatments did decrease larval survival but not significantly, compared to that of the virus alone. The efficacy of CrleGV could be further enhanced by adding molasses to yeast/virus formulations, as it has previously been demonstrated to be an effective adjuvant [® S240 utilized alongside P. kudriavzevii and S. cerevisiae to achieve the ideal working conditions. An LC50 concentration of CrleGV was selected, as this would result in 50% mortality of the T. leucotreta population. Thus, an increase or decrease in mortality could be observed when combining CrleGV with a specific treatment. The mortality rates of T. leucotreta observed in detached fruit bioassays using the LC50 concentration of CrleGV were comparable to previously reported rates [C. pomonella [Once onal OBs . Molasseonal OBs ,13. Furteatments . Additioeatments . Adding adjuvant ,13,14. Ied rates . As prevomonella , the addT. leucotreta to CrleGV formulations proved effective in increasing virus efficacy. Additionally, the inclusion of molasses and BREAK-THRU® S240 further increased the formulation’s effectiveness, compared to CrleGV being applied alone. Taken together, the results of this study indicate that P. kudriavzevii and S. cerevisiae hold potential for use in biocontrol, especially when combined with other well-established control techniques for use against T. leucotreta. These yeasts could potentially serve as a supplement to enhance larval feeding and thus virus ingestion, and as a distinctive approach for pest monitoring and attraction. Future work will entail conducting field trials with P. kudriavzevii and S. cerevisiae to determine whether their ability to increase the effectiveness of CrleGV in laboratory assays can be replicated in citrus orchards.The inclusion of yeast isolated from


Tumour dimension alone was not effective in the prediction of DFS and OS, both when considered as a continuous variable and when considered with a cut-off of 3 and 5 cm. However, with multivariate analysis, it was effective in predicting OS in the aforementioned conditions . Moreover, multivariate analysis was also used in the thymoma and Masaoka I subgroups. In our experience, the role of tumour dimension as a descriptor of the T parameter of the TNM (Tumor Node Metastasis) staging system seemed to be useful in improving this system.According to the different classifications now in use, thymic tumours are staged by the extent of local invasiveness, and tumour size is not included as a major determinant for the T category. The aim of this double-site retrospective study is to analyse the correlation between tumour dimension and overall survival (OS) in patients who underwent surgical treatment. From January 2000 to December 2020, patients with thymic epithelial tumours who underwent surgical resection were included in this study. Data from a total of 332 patients were analysed. Five- and ten-year overall survival (5–10 YOS) was 89.26% and 87.08%, respectively, while five- and ten-year disease-free survival (DFS) was 88.12% and 84.2%, respectively. Univariate analysis showed a significant correlation between male sex ( Thymic epithelial neoplasms are rare organ-specific neoplasms with varying malignant potential that comprise thymomas, thymic carcinomas (TC) and thymic neuroendocrine tumours (NETT).According to the different existing classifications, particularly in the Masaoka–Koga and TNM 8th edition, thymic tumours are staged by the extent of local invasiveness, but size is not considered as a major determinant for the T category ,2,3.The Masaoka staging system for thymoma was presented in 1981 and has been accepted as the global standard staging system for more than 20 years . In 2010In 2022, The International Association for the Study of Lung Cancer Thymic Epithelial Tumour Staging Project  describeIn the making of the 8th edition of the Union for International Cancer Control (UICC)/American Joint Committee on Cancer (AJCC) TNM classification in 2014, in the International Association for the Study of Lung Cancer (IASLC)/International Thymic Malignancy Interest Group (ITMIG) Thymic Epithelial Tumours Staging Project, a database of 5796 patients was analysed and considered one-dimension measurement of the tumour. The analysis showed that tumour size at a 10 cm threshold was only significant in incomplete (R1 and R2) resection and advanced (stages III and IV) tumours [Accordingly, the first issue to be considered is the prognostic role of tumour size itself. To date, no definitive or clear results have revealed the predictive value of tumour size for thymoma prognosis ,6,7,8.Nicholson et al.  did not Moreover, much clarity is still needed on the role of tumour dimension in prognosis, either as an independent risk factor or if it depends on the association with other tumour characteristics . In the IASLC/ITMIG Thymic Epithelial Tumours Staging Project, the 10 cm threshold only had a role in the R1 and R2 tumours as well as in advanced stages (III e IV). Fukui and colleagues , who defThe aim of this study is to analyse the correlation between tumour dimension and OS in patients who underwent surgical treatment.Patients with thymic epithelial tumours who underwent surgical resection were included in this study. Data from a total of 332 patients were analysed.The pre-operative assessment included a contrasted CT scan and magnetic resonance if indicated in the case of suspected infiltration of neighbouring organs.Thymic epithelial tumour was suspected on the basis of radiological characteristics, and a confirmatory biopsy was performed in case of doubt or in the case of patients who may benefit from neoadjuvant treatment.Surgery was performed with general anaesthesia. All patients underwent neurological examination before surgery to investigate the presence of myasthenia gravis. The analysis included the anti-acetylcholine receptor, anti-Mu SK antibodies and electromyography (EMG).Surgery was performed with median sternotomy or the combination of cervicectomy and manubrial section. After the introduction of minimally invasive techniques, in addition, video-assisted thoracic surgery (VATS) and robotic resection were performed in selected cases, mainly for tumours smaller than 3 cm. All the operations were performed with the aim of radical resection. In the case of suspected infiltrations, where possible, infiltrated structures were removed in bloc with the tumour, and the area of removal was signed with titanium clips.The pathological specimen was analysed and staged with the WHO histological classification  and MasaInduction therapy was administrated considering pre-operative imaging, while adjuvant therapy was considered according to the pathological results. The choice of radiotherapy or chemotherapy depended on the pathological stage, patient characteristics and previous treatment. After surgery, follow-up was conducted according to the most recent available guidelines. For instance, a baseline thoracic CT scan was carried out 3 months after surgery. For completely resected stage I/II thymomas, CT scans were performed every year for 5 years and then every 2 years. For stage III/IV thymomas, thymic carcinoma or after R1–2 resection, CT scans were performed every 6 months for 2 years and then annually. Follow-up was continued for 10–15 years .Overall survival (OS).The primary endpoint was the following:Disease free survival (DFS)Correlation between tumour dimension and other pathologic characteristics.Secondary endpoints were the following:Tumour dimension was studied as a continuous variable with two different cut-offs at 3 cm and 5 cm. The variables taken into account were sex, age, presence of myasthenia gravis, kind of surgery, pTNM, Masaoka stage, histology, number of infiltrated organs and recurrence. Through univariate and multivariate analyses, we investigated the prognostic value of tumour size for thymic epithelial tumour (TET) according to tumour stage after complete resection.t test, based on the unequal population variance. In addition, the ANOVA test and non-parametric Kruskal–Wallis test were considered to better explore the association of the features to our conditions of interest, whereas categorical variables were analysed using frequencies and percentages and were compared using the chi-square test. Based on 11% of not available data (NA) for tumour dimension—cm (outcome of interest), imputation with the mice package in R 4.1.2 was performed to obtain a full and complete dataset.Continuous variables were analysed using the mean and standard deviations (SD) and compared using Welch’s MASS, survival, survminer and ggplot2 downloaded from CRAN .Therefore, survival analyses were conducted using the Kaplan–Meier method with the log-rank test. Secondly, a Cox proportional-regression model was performed, considering a cluster model based on the referred Surgical Centre, due to the aim of our study. Overall survival (OS) was calculated from the date of surgery to death for any cause, while DFS was calculated from the time of surgery to the first detection of recurrence. The statistical analysis and the graphical related part were performed with software R 4.1.2, implementing with the libraries The main clinical and pathological characteristics are reported in p-value 0.02), older age , absence of myasthenia gravis , considering non-parametric test with the increase in TNM  and increase in the number of infiltrated organs  with the increase in tumour dimension. In particular, regarding the number of infiltrated organs, it was significant if the number was 3 vs. 0 and 3 vs. 1, considering a Tukey HSD test with family-wise error rate (FWER) correction.All the variables analysed in the univariate models are reported in On the contrary, there was no statistical correlation between the histology (thymoma vs. carcinoma), the status of the capsule (infiltrated or not) and the tumour dimension.p-value 0.0019) and OS  for stage I and II curves overlapped, while a greater difference was evident for stage III and stage IV  and OS  was observed when the number of infiltrated organs was three compared to one and zero , while it was not statistically related to the OS  with an increasing hazard ratio of recurrence (HR) for one (HR: 3.86), two (HR: 4.87) and three (HR: 12.56) infiltrated organs.The TNM staging system was associated only with the prediction of DFS  with a stratification for the number of organs infiltrated, decreasing HR and the number increase (HR was approximately 0 for three organs infiltrated).This variable was also effective in predicting the OS  with the cut-off of 3 cm  and 5 cm   .p-value < 0.01)  with the cut-off of 3  and 5 cm , tumour dimension was involved in the prediction of OS  . As a coon of OS .p-value < 0.01)  . However < 0.01) .In our study, we investigated the survival outcomes for TET in a large two-centred cohort with a particular interest on the tumour dimension.In general, according to previous studies ,13,14, wp-value to be significant when the cut-off was set at 3 cm (p = 0.086) for the OS. This observation was much more evident for the OS when the variable was continuous, even with a p-value of >0.05.In our experience, tumour size was first analysed as an independent factor in the definition of OS and DFS. We considered the dimension with the cut-offs of 3 and 5 cm as a continuous variable. For both DFS and OS, the tumour dimension was not significantly associated with survival outcomes. In contrast, in the K–M curves, we observed the tendency of the p < 0.01).Based on the results obtained in the univariate analysis for the Masaoka–Koga staging system in relation to the number of infiltrated organs and tumour dimension, a multivariate analysis was performed with the Cox regression model. In this case, as a covariate variable continuous with the cut-off of 3 and 5 cm, the tumour dimension was not involved in the prediction of DFS. On the other hand, more encouraging results were obtained with OS. Indeed, in the Cox regression model, the tumour dimension was significant in predicting the OS for the three conditions mentioned above  (p < 0.01). Furthermore, the tumour dimension was significantly associated with OS in all conditions investigated (p < 0.01). In the Masaoka I sub-group, the tumour dimension was not predictive of OS, even when set as a continuous variable with the cut-off of either 3 cm or 5 cm. Instead, the three considered conditions were predictive for DFS (<0.01).Similarly, we performed the same multivariate analysis only in thymoma cases and then in Masaoka I-affected patients. Indeed, the IASLC group of study for the ninth edition of the TNM (1) suspects that the role of tumour size may be different according to the histology and to the level of local invasiveness. In the thymoma sub-group, we found no statistically significant correlation between DFS and tumour dimension set as a continuous variable with the cut-off of 3 cm. However, the tumour dimension with the cut-off set at 5 cm was significant in the prediction of DFS  . ConsequConcerning the definition of a cut-off to better stratify the risk, we considered 3 and 5 cm. Alone, none of the cut-offs was effective in the prediction of OS and DFS. However, the results from the multivariate analysis were encouraging, as these cut-offs were found to be significant for the prediction of OS (in association with the number of infiltrated organs).Our study presents some limitations. First, our study is limited by its retrospective nature. Second, our analysis was performed on a limited number of patients. Although our results are encouraging, further studies with a larger cohort are needed to validate our findings. Tumour dimension may be used to describe the T factor of the TNM staging system to improve survival stratification in these patients. Furthermore, the optimal cut-off value for tumour size has to be defined to distinguish different prognoses in completely resected patients.In our experience, the role of tumour dimension as a descriptor of the T parameter of the pTNM staging system seemed to be a potential factor to improve this system, as it was related to OS and DFS in the multivariate analysis, together with the number of infiltrated organs. Further evaluations in larger cohorts are necessary to define the dimension cut-off for T stratification and the eventual introduction of a composite T parameter.Furthermore, our study confirms the effectiveness of the Masaoka–Koga staging system and number of infiltrated organs for the prediction of OS, and the Masaoka–Koga staging system, number of infiltrated organs and TNM staging system for the prediction of tumour recurrence.