Retrospective Analysis of Clostridioides difficile Infection Rates in Hospitalized Patients during COVID-19 Pandemic. A Unicenter Study in Reus, Spain (preprint)

.Background: Clostridioides difficile infections (CDI) vary in severity from mild diarrhea to life-threatening conditions like pseudomembranous colitis or toxic megacolon, often leading to sepsis and death. The COVID-19 pandemic prompted changes in healthcare practices, potentially affecting CDI incidence, though reported data are inconclusive. We studied factors influencing CDI incidence and outcomes at a university hospital throughout the COVID-19 pandemic years. Methods: We conducted a retrospective study on all adult hospitalized CDI cases from January 1, 2020, to December 31, 2022. We collected demographic information, comorbid conditions, and concurrent infections. Results: While overall CDI and COVID-19 rates decreased in 2022, a nota-ble increase in CDI infections was observed among oncological patients and those undergoing some aggressive treatments, such as colon or gastroscopies. The prevalence of comorbidities remained unmodified, and there were declines in prior gastrointestinal surgeries and proton pump inhibitor prescriptions. Factors associated with patient fatality or prolonged hospitaliza-tion included older age, cancer, chronic kidney disease, higher Charlson and McCabe indices, elevated C-reactive protein, and low albumin concentrations. Conclusion: Our study shows the evolving landscape of CDI during the COVID-19 pandemic and emphasizes the impact of de-layed diagnoses and treatments exacerbated by telemedicine adoption. Identified risk factors for CDI-related mortality or prolonged hospital stays underscore the importance of targeted inter-ventions in high-risk populations.

SARS-CoV-2 spike S2 subunit inhibits p53 activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2 proteins in cancer cells (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 infection has led to worsened outcomes for patients with cancer. SARS-CoV-2 spike protein mediates host cell infection and cell-cell fusion that causes stabilization of tumor suppressor p53 protein. In-silico analysis previously suggested that SARS-CoV-2 spike interacts with p53 directly but this putative interaction has not been demonstrated in cells. We examined the interaction between SARS-CoV-2 spike, p53 and MDM2 (E3 ligase, which mediates p53 degradation) in cancer cells using an immunoprecipitation assay. We observed that SARS-CoV-2 spike protein interrupts p53-MDM2 protein interaction but did not detect SARS-CoV-2 spike bound with p53 protein in the cancer cells. We further observed that SARS-CoV-2 spike suppresses p53 transcriptional activity in cancer cells including after nutlin exposure of wild-type p53-, spike S2-expressing tumor cells and inhibits chemotherapy-induced p53 gene activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2. The suppressive effect of SARS-CoV-2 spike on p53-dependent gene activation provides a potential molecular mechanism by which SARS-CoV-2 infection may impact tumorigenesis, tumor progression and chemotherapy sensitivity. In fact, cisplatin-treated tumor cells expressing spike S2 were found to have increased cell viability as compared to control cells. Further observations on gamma-H2AX expression in spike S2-expressing cells treated with cisplatin may indicate altered DNA damage sensing in the DNA damage response pathway. The preliminary observations reported here warrant further studies to unravel the impact of SARS-CoV-2 and its various encoded proteins including spike on pathways of tumorigenesis and response to cancer therapeutics.

Epitope-anchored contrastive transfer learning for paired CD8+ T cell receptor-antigen recognition (preprint)

Understanding the mechanisms of T-cell antigen recognition that underpin adaptive immune responses is critical for the development of vaccines, immunotherapies, and treatments against autoimmune diseases. Despite extensive research efforts, the accurate identification of T cell receptor (TCR)-antigen binding pairs remains a significant challenge due to the vast diversity and cross-reactivity of TCRs. Here, we propose a deep-learning framework termed Epitope-anchored Contrastive Transfer Learning (EPACT) tailored to paired human CD8+ TCRs from single-cell sequencing data. Harnessing the pre-trained representations and the contrastive co-embedding space, EPACT demonstrates state-of-the-art model generalizability in predicting TCR binding specificity for unseen epitopes and distinct TCR repertoires, offering potential values for practical outcomes in real-world scenarios. The contrastive learning paradigm achieves highly precise predictions for immunodominant epitopes and facilitates interpretable analysis of epitope-specific T cells. The TCR binding strength predicted by EPACT aligns well with the surge in spike-specific immune responses targeting SARS-CoV-2 epitopes after vaccination. We further fine-tune EPACT on TCR-epitope structural data to decipher the residue-level interactions involved in T-cell antigen recognition. EPACT not only exhibits superior capabilities in quantifying inter-chain distance matrices and identifying contact residue pairs but also corroborates the presence of molecular mimicry across multiple tumor-associated antigens. Together, EPACT can serve as a useful AI approach with significant potential in practical applications and contribute toward the development of TCR-based diagnostics and immunotherapies.

Uptake of COVID-19 vaccination and associated factors among patients attending oncology services in Dar es Salaam, Tanzania: A mixed design methods’ trajectories (preprint)

Background COVID-19 vaccination campaigns have reduced diseases severity and fatalities around the globe. Global data shows 67.7% of the general population are vaccinated, and Tanzania is reported to have over 70% coverage among individuals more than 18 years of age. However, group-specific assessment of the vaccination coverage is needed in sub-Saharan Africa, and cancer patients constitute a special priority group owing to the vulnerability attributable to this group.Methods A cross-sectional study design was conducted in September 2022 at Ocean Road Cancer Institute (ORCI) in Dar Es Salaam, Tanzania. A stratified sampling technique was used for quantitative data collection involving 479 cancer patients, and convenience sampling was applied for qualitative data collection involving 26 patients. Data were analysed using the statistical software ‘R’ by logistic regression analysis to determine association between socio-demographic, clinical and health belief model (HBM) variables against COVID-19 vaccine uptake among cancer patients.Results A total of 384 (80.2%) participants were female with a mean age (± standard deviation) of 48 ± 12.4 years; ranging from 18 to 83 years. Approximately 58.2% (278/479) of the participants reported to be vaccinated against COVID-19, and among them 79.5% were females. Having secondary school education or higher education (OR 2.26, CI 1.20–4.27 p = 0.011), perception on COVID-19 vaccine (OR 8.86, CI 2.84–32.2, p < 0.001) and perceived severity of COVID-19 (OR 0.56, CI 0.36–0.87, p = 0.010) were significantly associated with vaccine uptake. In the qualitative part, the findings suggest that individuals’ beliefs, perceptions, and external factors play a role in their decision to get vaccinated.Conclusions Approximately 6 out of 10 cancer patients at the ORCI reported to be vaccinated; with patients’ higher education status, perception on COVID-19 vaccine, and perceived severity being significantly associated with COVID-19 vaccination uptake. Public health interventions should leverage these identified factors to promote vaccine uptake through tailoring communication efforts to specific characteristics.

Pre-pandemic Predictivity of Anxious-Depressive Symptoms in Post-surgical Traumatic Distress in Hysterectomy for Benign Disease and COVID-19 Outbreak: A Case-Control Study (preprint)

The Sars-Cov-2 pandemic led to several needed containing measures that conditioned the onset of depressive, anxiety and post-traumatic stress symptoms in population. These symptoms, espe-cially if not diagnosed and treated, can also occur in patients undergoing surgery with high im-pact on people’s lives, like hysterectomy. To evaluate the post-surgical distress and anx-ious-depressive symptoms following hysterectomy for benign disease focusing on the impact of COVID-19 pandemic. The prospective observational cohort study included patients undergoing hysterectomy for benign disease. Psychologic evaluation through social-demographic question-naires was obtained before surgery (T1), postoperatively (T2), and 3 months after surgery (T3). The HADS (Hospital Anxiety and Depression Scale) was used to evaluate anxious-depressive symptoms and the PCL-5 (Post-traumatic Stress Disorder Checklist for DSM-5) compared the on-set of post-surgical distress and anxiety and depressive symptoms. The pre-COVID-19 pan-demic period was compared to the post-COVID-19 pandemic phase. Patients treated after COVID-19 pandemic showed higher depressive symptoms rate compared to those treated before (p-value=0.02); conversely, pre-COVID-19 patients were more prone to develop a PTSD (p-value=0.04). A significative association between the occurrence PTSD and anxiety-depressive symptoms registered at T2 a (p-value=0.007) and T3 (p-value

Respiratory viral infection promotes the awakening and outgrowth of dormant metastatic breast cancer cells in lungs (preprint)

Breast cancer is the second most common cancer globally. Most deaths from breast cancer are due to metastatic disease which often follows long periods of clinical dormancy1. Understanding the mechanisms that disrupt the quiescence of dormant disseminated cancer cells (DCC) is crucial for addressing metastatic progression. Infection with respiratory viruses (e.g. influenza or SARS-CoV-2) is common and triggers an inflammatory response locally and systemically2,3. Here we show that influenza virus infection leads to loss of the pro-dormancy mesenchymal phenotype in breast DCC in the lung, causing DCC proliferation within days of infection, and a greater than 100-fold expansion of carcinoma cells into metastatic lesions within two weeks. Such DCC phenotypic change and expansion is interleukin-6 (IL-6)-dependent. We further show that CD4 T cells are required for the maintenance of pulmonary metastatic burden post-influenza virus infection, in part through attenuation of CD8 cell responses in the lungs. Single-cell RNA-seq analyses reveal DCC-dependent impairment of T-cell activation in the lungs of infected mice. SARS-CoV-2 infected mice also showed increased breast DCC expansion in lungs post-infection. Expanding our findings to human observational data, we observed that cancer survivors contracting a SARS-CoV-2 infection have substantially increased risks of lung metastatic progression and cancer-related death compared to cancer survivors who did not. These discoveries underscore the significant impact of respiratory viral infections on the resurgence of metastatic cancer, offering novel insights into the interconnection between infectious diseases and cancer metastasis.

Causes of death in people living with HIV in the post 95 -95 -95 era: Lessons from five AIDS Healthcare Foundation clinics in Eswatini (preprint)

Background Eswatini has a high HIV prevalence in adults (24.8%), and despite achieving HIV epidemic control, AIDS-related deaths are still high at 200 per 100,000 population. This study, therefore, describes the causes of death among people living with HIV (PLHIV) receiving care at five clinics in Eswatini. Methods Data of clients receiving antiretroviral therapy (ART) from five AIDS Healthcare Foundation (AHF) Clinics in Eswatini who died was analysed to describe the causes of death. Clients' records were included if they received treatment from any of the five clinics from January 1, 2021, to June 30, 2022. Clients' sociodemographic, clinical, and specific cause of death data were extracted from their clinical records into an Excel spreadsheet for mortality reporting and audits. The different causes of death were categorised and descriptive, and comparative analysis was done using Stata 15 and R. Odds ratio significant at p<0.05 (with 95% confidence interval) to estimate the different associations between the client's characteristics and the four leading causes of death. Results Of 257 clients, 52.5% (n=135) were males, and the median age was 47 years (IQR: 38, 59). The leading causes of death were non-communicable diseases (NCDs) (n=59, 23.0%), malignancies (n=37, 14.4%), Covid-19 (n=36, 14.0%) and advanced HIV disease (AHD) (n=24, 9.3%). Patients aged ≥60 years (OR 0.08; 95% CI: 0.004, 0.44) had lower odds of death from AHD than ≥40 years, and those who had been on ART for 12 – 60 months (OR 0.01; 95% CI: 0.0006, 0.06) and >60 months (OR 0.006; 95% CI: 0.0003, 0.029) had lower odds of death from AHD compared to those on ART for <12 months. Patients aged ≥40 years had higher odds of dying from COVID-19, while females (OR 2.64; 95% CI: 1.29, 5.70) had higher odds of death from malignancy. Conclusion Most patients who died were aged 40 years and above and died from an NCD, malignancy, COVID-19 and AHD-related cause. This indicates a need to expandprevention, screening, and integration of treatment for NCDs and cancers into HIV services. Specific interventions targeting younger PLHIV will limit their risks for AHD.

The Critical Issues for Patients and Caregivers in Neuro-Oncology During Covid-19 Pandemic: What We Have Learnt by an Observational Study. (preprint)

Objective: The COVID-19 pandemic inferred on neuro-oncological patients (PTS) and the caregivers regarding tumor care and emotional functioning. This study aimed to understand how COVID-19 affects their psychological state and relations between PTS and health personnel in neuro-oncology. Methods: A cross-sectional study on neuro-oncological PTS and their caregivers. Results: A total of 162 PTS and 66 caregivers completed the questionnaire. The 37.5% of PTS perceived greater risk of contracting the COVID-19 compared to the general population. On the 0-10 scale, PTS tumor-related anxiety score was 5.8 and COVID-related 4.6. The caregivers reported 7.7 and 5.5 respectively. The QoL was described at least as good in 75% of both PTS and caregivers; the caregivers’ care burden increased in 22.7% during the pandemic, with no correlation with QoL. Future perception often changed both in PTS and in the caregivers. Cancer treatment schedule was changed in 18.5%, including for PTS decision. However, the 93.5% of PTS was satisfied with the overall care. Conclusion: A considerable proportion of PTS and caregivers still perceived the tumor disease as more burdensome than the pandemic, and perceived their future as more uncertain. Such data rinforce the need to build a proficient alliance between PTS and health personnel.

A Case Report of Acute Lymphoblastic Leukaemia (ALL)/Lymphoblastic Lymphoma (LBL) Following the Second Dose of Comirnaty®: An Analysis of the Potential Pathogenic Mechanism Based on of the Existing Literature (preprint)

In this report we describe the case of a healthy, young, athletic woman who developed acute lymphoblastic leukaemia (ALL)/lymphoblastic lymphoma (LBL) after receiving the second dose of the Pfizer/BioNTech modified mRNA (modRNA) COVID-19 genetic vaccine (marketed as Comirnaty®). The first dose of the genetic vaccine did not appear to illicit any noticeable side effects, but within 24 hours of the second dose the patient suffered widespread and intensifying bone pain, fever, vomiting, and general malaise. Due to the persistence of the symptoms, the patient underwent a series of tests and examinations including a full laboratory workup, a consult with a clinical immunologist and rheumatologist, a Positron Emission Tomography (PET) imaging, as well as an osteomedullary biopsy. These together led to a definitive diagnosis of ALL. A time interval of 16 weeks from the second vaccination to the diagnosis of cancer was noted. Several similar cases with identical pathology which developed after the modRNA COVID-19 vaccination, are described in case reports in the scientific literature. The massive and indiscriminate use of genetic vaccines to fight COVID-19 is raising serious concerns about their safety and about the technology platform as a whole for this purpose. Growing evidence is accumulating regarding the biodistribution and persistence of the modRNA which can reach, thanks to the lipid nanoparticles, a multitude of tissues and organs of the body, including the bone marrow and other blood-forming organs and tissues. Moreover, there is evidence that the modRNA vaccines display a particular tropism for the bone marrow, influencing the immune system at multiple levels and being able to trigger not only autoimmune-based pathologies, but also neoplastic mechanisms. The aim of this article is to assess, on the basis of the available scientific literature, the risk of developing haematopoietic cancers after modRNA vaccination, and to investigate the potential genetic mechanisms involved in the pathogenesis of disease.

Identifying immune signatures of common exposures through co-occurrence of T-cell receptors in tens of thousands of donors (preprint)

Memory T cells are records of clonal expansion from prior immune exposures, such as infections, vaccines and chronic diseases like cancer. A subset of the receptors of these expanded T cells in a typical immune repertoire are highly public, i.e., present in many individuals exposed to the same exposure. For the most part, the exposures associated with these public T cells are unknown. To identify public T-cell receptor signatures of immune exposures, we mined the immunosequencing repertoires of tens of thousands of donors to define clusters of co-occurring T cells. We first built co-occurrence clusters of T cells responding to antigens presented by the same Human Leukocyte Antigen (HLA) and then combined those clusters across HLAs. Each cross-HLA cluster putatively represents the public T-cell signature of a single prevalent exposure. Using repertoires from donors with known serological status for 7 prevalent exposures (HSV-1, HSV-2, EBV, Parvovirus, Toxoplasma gondii, Cytomegalovirus and SARS CoV-2), we identified a single T-cell cluster strongly associated with each exposure and used it to construct a highly sensitive and specific diagnostic model for the exposure. These T-cell clusters constitute the public immune responses to prevalent exposures, 7 known and many others unknown. By learning the exposure associations for more T cell clusters, this approach could be used to derive a ledger of a person's past and present immune exposures.

Impact of SARS-CoV-2 (COVID-19) Pandemic on Characteristics and Management of Uveal Melanoma in National Referral Center in Poland (preprint)

Background: to analyze the impact of COVID-19 pandemic on characteristics and management of uveal melanoma (UM) in National Referral Center in Poland. Materials and Methods: the retrospective analysis of 1336 patients who were newly diagnosed with UM at Department of Ophthalmology and Ophthalmic Oncology, Jagiellonian University Collegium Medicum Krakow, Poland between January 1, 2018 and December 31, 2021. The demographic and clinical data were compiled including localization, size and treatment methods of tumors. Results: In total, 728 patients with UM were included before COVID-19 pandemic in years 2018-2019 and 608 were included during COVID-19 pandemic in years 2020-2021. Fixed-base dynamics indicators for the incidence of uveal melanoma (base year 2018) in the national referral center in Poland were 80.22% and 86.81% in year 2020 and 2021, respectively. UMs were statistically significantly larger and more frequently localized anterior to the equator of the eye globe in year 2021 than in year 2018 (Chi^2 Pearson test p= 0.0001 and p= 0.0077, respectively). The rate of patients treated with enucleation increased from 15.94% in year 2018 to 26.90% in year 2021 (Chi^2 Pearson test p=0.0005). Conclusions: statistically significant differences were found in the management of uveal melanoma in National Referral Center in Poland during COVID-19 pandemic with tumors being larger, more frequently localized anterior to the equator of the eye globe and more often enucleated.

A pilot of artificial intelligence telephone triage of patients with suspected head and neck cancer (preprint)

1. The overwhelming majority of patients referred into secondary care with suspected head and neck cancer (HNC) do not have cancer (~95%). 2. During the COVID-19 pandemic telephone triage of patients with suspected HNC was necessary. During this time, a validated HNC risk-calculator, HaNC-RC-v2 (a set of symptomatology-based questions) was recommended by ENT UK to stratify patients into high or low risk of having HNC via telephone triage [(1)](#ref-0001) 3. Ufonia, a digital health company which uses an Artificial Intelligence (AI) voice assistant to automate clinical conversations via telephone, and *INSTITUTION*, were awarded an SBRI Healthcare grant to help develop an AI-delivered HNC triage telephone call. This was based on the HaNC-RC-v2 and co-created with HNC patients from the Heads2Gether charity via round-table discussions and one-to-one sessions. 4. Twenty-nine patients underwent a clinician-supervised AI-delivered HNC triage conversation as part of their standard telephone consultation. 100% of calls were completed with an average agreement of 89% between the clinician and the AI system for all symptoms asked. The technology was highly acceptable to patients with a median net promoter score (NPS) score of 8 out of 10. 5. Novel technologies involving AI automated telephone calls can be generated to remotely triage suspected HNC patients. This technology may offer an exciting opportunity to help departments triage suspected HNC referrals in an ever increasingly resource pressurised NHS.

Optimal prevention strategies for chronic diseases in a compartmental disease trajectory model (preprint)

In countries with growing elderly populations, multimorbidity poses a significant healthcare challenge. The trajectories along which diseases accumulate as patients age and how they can be targeted by prevention efforts are still not fully understood. We propose a compartmental model, traditionally used in infectious diseases, describing chronic disease trajectories across 132 distinct multimorbidity patterns (compartments). Leveraging a comprehensive dataset from approximately 45 million hospital stays spanning 17 years in Austria, our compartmental disease trajectory model (CDTM) forecasts changes in the incidence of 131 diagnostic groups and their combinations until 2030, highlighting patterns involving hypertensive diseases with cardiovascular diseases and metabolic disorders. We pinpoint specific diagnoses with the greatest potential for preventive interventions to promote healthy aging. According to our model, a reduction of new onsets by 5% of hypertensive diseases (I10-I15) leads to a reduction in all-cause mortality over a period of 15 years by 0.57 (0.06)% and for malignant neoplasms (C00-C97) mortality is reduced by 0.57 (0.07)%. Furthermore, we use the model to assess the long-term consequences of the Covid-19 pandemic on hospitalizations, revealing earlier and more frequent hospitalizations across multiple diagnoses. Our fully data-driven approach identifies leverage points for proactive preparation by physicians and policymakers to reduce the overall disease burden in the population, emphasizing a shift towards patient-centered care.

COVID-19-associated acute renal failure in critically ill patients correlates with microthrombosis and renal loss of thrombomodulin (preprint)

Critically ill COVID-19 patients have a high degree of acute kidney injury which develops in up to 85% of patients. We have previously shown that circulating levels of angiopoietin-2 increased in critically ill COVID-19 patients correlated to kidney injury, coagulopathy, and mortality. Furthermore, our experiments showed a causal effect on coagulopathy from angiopoietin-2 binding and inhibition of thrombomodulin mediated anticoagulation. In the current study we hypothesize that renal microthrombi may be a mechanism for reduced renal function in critically ill COVID-19 patients, and that local dysregulation of thrombomodulin and angiopoietin-2 may be involved. To investigate our hypothesis, we utilized postmortem kidney tissue from seven COVID-19 patients treated at the intensive care unit. We evaluated kidney function, thrombosis, tubular injury, fibrosis, glomerulosclerosis, glomerular size as well as renal expression of thrombomodulin and angiopoietin-2. Proximity ligation assay was utilized to evaluate the presence of angiopoietin-2 binding to thrombomodulin. Normal kidney tissue came from the healthy part of six nephrectomies due to cancer. Our experiments show renal thrombosis in 6/7 COVID-19 patients, on average 14.7 (6.9-22.5) thrombi per mm2. Most COVID-19 kidneys had extensive kidney injury, especially tubular necrosis, but also glomerular enlargement, glomerulosclerosis, and tubulointerstitial fibrosis which in some cases most likely resulted from underlying disease. Thrombomodulin expression was reduced in glomeruli and peritubular capillaries in kidneys from COVID-19 patients, whereas no change was found for angiopoietin-2. In summary, our study describes a high degree of acute renal failure, renal microthrombosis, and loss of thrombomodulin in postmortem tissue from critically ill COVID-19 patients.

Trustworthiness of Pretrained Transformers for Lung Cancer Segmentation (preprint)

We assessed the trustworthiness of two self-supervision pretrained transformer models, Swin UNETR and SMIT, for fine-tuned lung (LC) tumor segmentation using 670 CT and MRI scans. We measured segmentation accuracy on two public 3D-CT datasets, robustness on CT scans of patients with COVID-19, CT scans of patients with ovarian cancer and T2-weighted MRI of men with prostate cancer, and zero-shot generalization of LC for T2-weighted MRIs. Both models demonstrated high accuracy on in-distribution data (Dice 0.80 for SMIT and 0.78 for Swin UNETR). SMIT showed similar near-out-of-distribution performance on CT scans (AUROC 89.85% vs. 89.19%) but significantly better far-out-of-distribution accuracy on CT (AUROC 97.2% vs. 87.1%) and MRI (92.15% vs. 73.8%). SMIT outperformed Swin UNETR in zero-shot segmentation on MRI (Dice 0.78 vs. 0.69). We expect these findings to guide the safe development and deployment of current and future pretrained models in routine clinical use.

Metastatic sarcoma affecting the heart and presenting as infective endocarditis: about a single medical case (preprint)

Heart sarcomas are scarce neoplasms with various clinical features and are known to be great imitators of several clinical representations. This article presents a case of a cardiac metastatic sarcoma complicated by infective endocarditis in a 35-year-old female patient with a history of rheumatic fever, brain surgery, and Covid-19 infection. The diagnosis was based on echocardiography, computed tomography and biopsy results. Despite receiving six weeks of antibiotic treatment, the patient’s prognosis was bleak due to the lack of effective palliative options. The article underlines the challenges in the management of cardiac sarcomas and the need for further research in this field.

Development of an engineered extracellular vesicles-based vaccine platform for combined delivery of mRNA and protein to induce functional immunity (preprint)

mRNA incorporated in lipid nanoparticles (LNPs) became a new class of vaccine modality for induction of immunity against COVID-19 and ushered in a new era in vaccine development. Here, we report a novel, easy-to-execute, and cost effective engineered extracellular vesicles (EVs)-based combined mRNA and protein vaccine platform (EVX-M+P vaccine) and explore its utility in proof-of-concept immunity studies in the settings of cancer and infectious disease. As a first example, we engineered EVs to contain ovalbumin mRNA and protein (EVOvaM+P) to serve as cancer vaccine against ovalbumin-expressing melanoma tumors. EVOvaM+P administration to mice with established melanoma tumors resulted in tumor regression associated with effective humoral and adaptive immune responses. As a second example, we generated engineered EVs, natural nanoparticle carriers shed by all cells, that contain mRNA and protein Spike (S) protein to serve as a combined mRNA and protein vaccine (EVSpikeM+P vaccine) against SARS-CoV-2 infection. EVSpikeM+P vaccine administration in mice and baboons elicited robust production of neutralizing IgG antibodies against RBD (receptor binding domain) of S protein and S protein specific T cell responses. Our proof-of-concept study describes a new platform with an ability for rapid development of combination mRNA and protein vaccines employing EVs for deployment against cancer and other diseases.

Engineered Migrasomes: A Robust, Thermally Stable Vaccination Platform (preprint)

The burgeoning abilities of pathogens and tumor cells to evade immune responses underscore the urgent need for innovative vaccination platforms based on a variety of biological mechanisms. The current logistical challenges associated with cold-chain (i.e. low-temperature) transportation particularly impacts access to vaccines in the global south. We recently discovered organelles called migrasomes, and herein we investigate the potential of migrasomes as an alternative vaccination platform. Their inherent stability and their enrichment with immune-modulating molecules make migrasomes promising candidates, but their low yield presents a hurdle. We address this problem through our engineered migrasome-like vesicles (eMigrasomes), which emulate the biophysical attributes of natural migrasomes with substantially improved yield. We show that eMigrasomes loaded with a model antigen elicit potent antibody responses and maintain stability at room temperature. We demonstrate that eMigrasomes bearing the SARS-CoV-2 Spike protein induce robust humoral protection against the virus. Our study demonstrates the potential of eMigrasome-based vaccines as a unique, robust, and accessible alternative to traditional methods.

Ethnic inequalities in the access of cancer screening services for women´s in Peru (preprint)

Background Despite guidelines and increased healthcare resources, there are disparities in coverage of screening cancer services for non-white communities, addressing these health inequalities is crucial in multicultural countries like Peru. For this reason, the aim was evaluating ethnic inequalities in the women proportion that use cancer screening services in Peruvians regions.Methods An ecological was used to assess the ethnic inequalities in the proportion of women use of general cancer screening, clinical breast examination, mammography, and pap test in the 25 regions of Peru. The inequalities were approach by estimating the GINI coefficient among ethnic groups based on various sociodemographic characteristics, and the annual variation of the GINI coefficient.Results In Peruvians regions there is greater inequality in general cancer screening services among the indigenous (GINI: 0.321) and afroperuvians (GINI: 0.415), which have a GINI coefficient almost twice that of the white or mestizo group (GINI: 0.183). Also, sociodemographic characteristics such as low educational level, low income, living in rural areas, being over 64 years old, and lack of health insurance mediate these inequalities in the use of cancer screening services. In the temporal variation, an increase in inequality was identified to afroperuvians and indigenous groups after 2020.Conclusion In Peruvian regions there are marked ethnic inequalities in use of cancer screening services for indigenous and afroperuvians groups compared to the white or mestizo group, especially in those regions with larger populations with adverse socioeconomic conditions that have worsened for these ethnic groups after the COVID-19 pandemic in Peru.

Combinatorial biomedicine: A novel discipline (preprint)

Based on the author’s previous work, this article proposed a novel discipline– combinatorial biomedicine. Currently, there are several classical examples. One is a magic “polypill” covering the “Health Essential (HE) 5”, that is, “environment-sleep-emotion-exercise-diet” intervention [E(e)SEEDi] lifestyle; Another is an innovative “traditional Chinese medicine (TCM) Hot Pot”. In addition, the iRT-ABCDEFG program is indeed suitable for better management of human diseases. In fact, combinatorial biomedicine is pivotal in the development of life science, biology and medicine, in particular the pandemic and post-COVID-19 era, and has obvious advantages in screening, diagnosis, treatments, prevention and rehabilitation of both major non-communicable diseases (such as cardiovascular disease, diabetes, cancer, stroke, and neurodegenerative diseases) and major infectious diseases (such as AIDS, Helicobacter pylori infection, and COVID-19). As a novel discipline, combinatorial biomedicine plays a crucial role in combating human diseases and improving population health. It is about time to propose and establish this novel discipline.