Determination of the active components of elderberry extracts on immune function and tumor cell growth

Present cancer treatments cause the cessation of the body\u27s own natural defenses, resulting in the susceptibility of patients to other illnesses, namely infection, during therapy. Contemporary research must focus on developing treatments to preserve or even augment the body\u27s natural defenses by pursuing naturally-derived elements devoid of such adverse effects. Seeking more natural treatments, Sambucus Nigra (elderberry) proves to be an important source of known immune stimulators including anthocyanins, catechins, and tannins, as wells as several known antioxidants and tumor suppressive agents in the form of flavonoids and proanthocyanidins. Our primary goal was to separate the distinctive components of an elderberry extract using gravity column chromatography and examine their proliferative effects on T lymphocytes as well as their inhibitory effects on the growth of human skin melanoma cells. Due to the successful effects of crude elderberry extracts on both immune enhancement and tumor suppression, we concluded that there must be specific components within the berry that enables its therapeutic value. The effects on immune cell stimulation were assessed through the quantitative analysis of spleen cell proliferation, which yielded significantly positive spleen cell stimulation following the addition of and concanavalin A, a known mitogen, as compared to the spleen cells incubated solely with concanavalin A. The inhibitory effect of the extract fractions was examined on a melanoma cell line. The successful suppression of tumor cell growth by several of the elderberry extract fractions, without mass suppression, was observed. In vivo studies using specific elderberry fractions may validate the use of the resolved components as viable therapeutic agents both in immunotherapy as well as chemotherapy

Determination of the active components of elderberry extracts on immune function and tumor cell growth

Present cancer treatments cause the cessation of the body\u27s own natural defenses, resulting in the susceptibility of patients to other illnesses, namely infection, during therapy. Contemporary research must focus on developing treatments to preserve or even augment the body\u27s natural defenses by pursuing naturally-derived elements devoid of such adverse effects. Seeking more natural treatments, Sambucus Nigra (elderberry) proves to be an important source of known immune stimulators including anthocyanins, catechins, and tannins, as wells as several known antioxidants and tumor suppressive agents in the form of flavonoids and proanthocyanidins. Our primary goal was to separate the distinctive components of an elderberry extract using gravity column chromatography and examine their proliferative effects on T lymphocytes as well as their inhibitory effects on the growth of human skin melanoma cells. Due to the successful effects of crude elderberry extracts on both immune enhancement and tumor suppression, we concluded that there must be specific components within the berry that enables its therapeutic value. The effects on immune cell stimulation were assessed through the quantitative analysis of spleen cell proliferation, which yielded significantly positive spleen cell stimulation following the addition of and concanavalin A, a known mitogen, as compared to the spleen cells incubated solely with concanavalin A. The inhibitory effect of the extract fractions was examined on a melanoma cell line. The successful suppression of tumor cell growth by several of the elderberry extract fractions, without mass suppression, was observed. In vivo studies using specific elderberry fractions may validate the use of the resolved components as viable therapeutic agents both in immunotherapy as well as chemotherapy

Jeelo Dobara (Live Life Again): a cross-sectional survey to understand the use of social media and community experience and perceptions around COVID-19 vaccine uptake in three low vaccine uptake districts in Karachi, Pakistan

Objective To gather preliminary insights through formative research on social media usage, and experiences, attitudes and perceptions around COVID-19 and COVID-19 vaccination in three high-risk, underserved districts in Karachi, Pakistan.Design Cross-sectional mixed-method design.Participants 392 adults (361 surveys and 30 in-depth interviews (IDI)) from districts South, East and Korangi in Karachi, Pakistan.Main outcome measures Social media usage and knowledge, perception and behaviour towards COVID-19 infection and vaccination.Results Using social media was associated with an increased probability of getting vaccinated by 1.61 units. Most of the respondents (65%) reported using social media, mainly to watch videos and/or keep in touch with family/friends. 84.76% knew of COVID-19 while 88.37% knew about the COVID-19 vaccination, with 71.19% reported vaccine receipt; reasons to vaccinate included belief that vaccines protect from the virus, and vaccination being mandatory for work. However, only 56.7% of respondents believed they were at risk of disease. Of the 54 unvaccinated individuals, 27.78% did not vaccinate as they did not believe in COVID-19. Despite this, 78.38% of respondents scored high on vaccine confidence. In IDIs, most respondents knew about COVID-19 vaccines: ‘This vaccine will create immunity in your body. Therefore, I think we should get vaccinated’, and over half knew how COVID-19 spreads. Most considered COVID-19 a serious public health problem and thought it important that people get vaccinated. However, there was a low-risk perception of self as only a little over half felt that they were at risk of contracting COVID-19.Conclusion With our conflicting results regarding COVID-19 vaccine confidence, that is, high vaccine coverage but low perception of risk to self, it is likely that vaccine coverage is more a result of mandates and coercion than true vaccine confidence. Our findings imply that interactive social media could be valuable in fostering provaccine sentiment

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community