Beginning in December 2019, the world faced a critical new public health stressor with the emergence of SARS-CoV-2. Its spread was extraordinarily rapid, and in a matter of weeks countries across the world were affected, notably in their ability to manage health care needs. While many sectors of public structures were impacted by the pandemic, it particularly highlighted shortcomings in medical care infrastructures around the world that underscored the need to reorganize medical systems, as they were vastly unprepared and ill-equipped to manage a pandemic and simultaneously provide general and specialized medical care. This paper presents modalities in approaches to the pandemic by various countries, and the triaged reorganization of medical sections not considered first-line in the pandemic that was in many cases transformed into wards for treating COVID-19 cases. As new viruses and structural variants emerge, it is important to find solutions to streamline medical care in hospitals, which includes the expansion of digital network medicine (i.e., telemedicine and mobile health apps) for patients to continue to receive appropriate care without risking exposure to contagions. Mobile health app development continues to evolve with specialized diagnostics capabilities via external attachments that can provide rapid information sharing between patients and care providers while eliminating the need for office visits. Telemedicine, still in the early stages of adoption, especially in the developing world, can ensure access to medical information and contact with care providers, with the potential to release emergency rooms from excessive cases, and offer multidisciplinary access for patients and care providers that can also be a means to avoid contact during a pandemic. As this pandemic illustrated, an overhaul to streamline health care is essential, and a move towards greater use of mobile health and telemedicine will greatly benefit public health to control the spread of new variants and future outbreaks.

/pdf/global-challenges-to-public-health-care-systems-during-the-3h1auga8.pdf

Global Challenges to Public Health Care Systems during the COVID-19 Pandemic: A Review of Pandemic Measures and Problems

Abstract Background To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes. Main body A systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points extracted included model type, input features, validation strategies, and key performance metrics. Results In total, 29 studies were analyzed, out of which 21 focused on diagnosis, seven on prognosis, and one on both. Artificial neural networks (ANNs) were the most commonly employed algorithm for diagnosis. Both ANN and logistic regression were also widely used for categorizing types of AA. ANNs showed high performance in most cases, with accuracy rates often exceeding 80% and AUC values peaking at 0.985. The models also demonstrated promising results in predicting postoperative outcomes such as sepsis risk and ICU admission. Risk of bias was identified in a majority of studies, with selection bias and lack of internal validation being the most common issues. Conclusion AI algorithms demonstrate significant promise in diagnosing and prognosticating AA, often surpassing traditional methods and clinical scores such as the Alvarado scoring system in terms of speed and accuracy. 

Artificial Intelligence and Acute Appendicitis: A Systematic Review of Diagnostic and Prognostic Models

Breast cancer (BC) is a multifaceted disease characterized by distinct molecular subtypes and varying responses to treatment. In BC, the phosphatidylinositol 3-kinase (PI3K) pathway has emerged as a crucial contributor to the development, advancement, and resistance to treatment. This review article explores the implications of the PI3K pathway in predictive, preventive, and personalized medicine for BC. It emphasizes the identification of predictive biomarkers, such as PIK3CA mutations, and the utility of molecular profiling in guiding treatment decisions. The review also discusses the potential of targeting the PI3K pathway for preventive strategies and the customization of therapy based on tumor stage, molecular subtypes, and genetic alterations. Overcoming resistance to PI3K inhibitors and exploring combination therapies are addressed as important considerations. While this field holds promise in improving patient outcomes, further research and clinical trials are needed to validate these approaches and translate them into clinical practice. 

pdf/predictive-preventive-and-personalized-medicine-in-breast-1t0bag81vw.pdf

Predictive, preventive, and personalized medicine in breast cancer: targeting the PI3K pathway

Background: Given the significance of the preparedness and responsiveness of healthcare systems in relation to epidemics, this study aimed to determine their influencing factors during epidemic crises with a view to utilizing the findings in the battle against the coronavirus disease 2019 (COVID-19) outbreak.Methods: This scoping study was conducted in 2020 via the Arksey and O’Malley approach. A systematic search was conducted on five online databases from January 2000 to June 15, 2020. Initially, 1926 English articles were retrieved based on their abstracts. After the screening process, 60 articles were considered for the final analysis. Data were charted by applying Microsoft Office Excel 2013 and were synthesized via thematic analysis. Results: Five main factors have affected the responsiveness and preparedness of countries during the epidemics of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19: community-related interventions, managerial interventions, socioeconomic factors, the readiness of hospitals and health centers, and environmental factors. These themes are associated with 38 related sub-themes. The thematic framework shows that interactions between these five determinantes can affect the preparedness and responsiveness of healthcare systems during pandemics/epidemics. Conclusion: According to the results, healthcare systems need to pay attention to their internal capacities, managerial interventions, and health centers to overcome the current pandemic. They should also consider such external factors as socioeconomic and environmental determinants that can affect their potential preparedness against pandemic/epidemic crises. Community-related interventions such as improvement of the community health literacy, teamwork, and social responsibility can enhance the readiness of healthcare systems against the COVID-19 outbreak.

https://ijms.sums.ac.ir/article_47263_a84ed774b8bef461a6f7f059e4d60a4e.pdf

Main Factors Affecting the Readiness and Responsiveness of Healthcare Systems during Epidemic Crises: A Scoping Review on Cases of SARS, MERS, and COVID-19

Simple Summary One out of 8 breast cancers is of a particular type called “HER2-positive”, which is more aggressive and is treated by surgery and a medical treatment associating chemotherapy and a targeted drug against the protein HER2, possibly followed by radiotherapy and endocrine therapy. When the medical treatment is performed before others (neoadjuvant) and that all cancer cells are gone, this is called “pathological complete response”, which is an important good-prognosis marker. This article studied on a group of 112 patients with HER2-positive breast cancer, the presence of a protein called STARD3, which has a strong biological and genetic association with HER2. It found that STARD3 was strongly associated with pathological complete response and could predict this response. It also investigated if the presence of STARD3 had an impact on prognosis (such as survival and the risk of cancer recurrence). This work suggests that the study of STARD3 for HER2-positive breast cancers could lead to a better treatment planning, and further studies are needed. Abstract Pathological complete response (pCR) after neoadjuvant systemic treatment (NST) is an important prognostic factor in HER2-positive breast cancer. The majority of HER2-positive breast cancers are amplified at the HER2 gene locus, several genes are co-amplified with HER2, and a subset of them are co-expressed. The STARD3 gene belongs to the HER2 amplicon, and its role as a predictive marker was never addressed. The objective of this study was to investigate the predictive value of STARD3 protein expression on NST pathological response in HER2-positive breast cancer. In addition, we studied the prognostic value of this marker. Methods. We conducted a retrospective study between 2007 and 2020 on 112 patients with non-metastatic HER2-positive breast cancer treated by NST and then by surgery. We developed an immunohistochemistry assay for STARD3 expression and subcellular localization and determined a score for STARD3-positivity. As STARD3 is an endosomal protein, its expression was considered positive if the intracellular signal pattern was granular. Results: In this series, pCR was achieved in half of the patients. STARD3 was positive in 86.6% of cases and was significantly associated with pCR in univariate analysis (p = 0.013) and after adjustment on other known pathological parameters (p = 0.044). Performances on pCR prediction showed high sensitivity (96%) and negative predictive value (87%), while specificity was 23% and positive predictive value was 56%. Overall, specific, relapse-free, and distant metastasis-free survivals were similar among STARD3 positive and negative groups, independently of other prognosis factors. Conclusion: NST is an opportunity for HER2-positive cancers. In this series of over a hundred HER2-positive and non-metastatic patients, a STARD3-negative score was associated with the absence of pathological complete response. This study suggests that determining STARD3 overexpression status on initial biopsies of HER2-positive tumors is an added value for the management of a subset of patients with high probability of no pathological response.

/pdf/stard3-a-new-biomarker-in-her2-positive-breast-cancer-3cvv6ikj.pdf

STARD3: A New Biomarker in HER2-Positive Breast Cancer

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ijgo.14719

Establishment of predictive models for acute complicated appendicitis during pregnancy—A retrospective case–control study

Tanshinone IIA improves sepsis-induced acute lung injury through the ROCK2/NF-κB axis.

The recent outbreak of coronavirus in Wuhan, China, has imposed challenges on the Chinese medical system. Not only the dramatically increasing number of infected cases and insufficient medical resources, but also the peoples' panic throughout the whole country have made medical services extremely difficult. To respond to these challenges effectively, our hospital implemented an urgent response strategy, including human resources and medical resources preparation and re-allocation, immediate fever screening, strict patient-visiting flow management, and reasonable information communication. Our experience and response measures could provide a reference for other hospitals in the current situation.

/pdf/challenges-and-responses-a-tertiary-hospital-in-2019-ncov-2xik2ejaim.pdf

Challenges and Responses: A Tertiary Hospital in 2019-nCoV Epidemic.

To explore the mechanism of steroidogenic acute regulatory (StAR)-related lipid transfer domain containing 3 (STARD3) in breast cancer (BC).We analysed the differential mRNA expressions of BC using ER+and ER-BC expression profiles from the cancer genome atlas (TCGA). Expression and correlation between salient genes was visualized using microarray volcano plots and a protein-protein interaction (PPI) network map. Survival analyses were performed to identify the potential for STARD3 to serve as a prognostic biomarker. The expression of STARD3 was examined by immunohistochemistry (IHC). The effects of STARD3 on apoptosis and proliferation of BC (MCF-7) cell line were deduced by flow cytometry, CCK8, and western blot (WB).STARD3 was the most differentially expressed gene (DEG). Patients in the STARD3 high expression group had significantly lower survival than those in the low expression group. The expression of STARD3 was significantly higher in BC tissues than controls. Inhibiting STARD3 expression significantly increased apoptosis, decreased proliferation, activated PI3K/AKT/mTOR pathway CONCLUSION: Inhibiting the expression of STARD3 induced apoptosis via the inactivation of PI3K/AKT/mTOR pathway on BC inhibits tumour growth, which can be an effective therapeutic strategy. 

Inhibiting the expression of STARD3 induced apoptosis via the inactivation of PI3K/AKT/mTOR pathway on ER+ breast cancer.

Purpose To explore the prognostic value of albumin corrected anion gap (ACAG) within 24 hours of admission to the intensive care unit (ICU) for acute pancreatitis (AP). Patients and Methods This was a retrospective cohort study. Adult AP patients admitted to ICU from June 2016 to December 2019 were included in the study, who were divided into three groups according to initial serum ACAG within 24 hours upon ICU admission: ACAG ≤ 14.87 mmol/L, 14.87 < ACAG ≤ 19.03 mmol/L, and ACAG > 19.03 mmol/L. The primary study outcome indicator was in-hospital mortality. Age, sex, Glasgow Coma Scale score, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score were matched through propensity score matching (PSM) method to balance the baseline between the survivors and non-survivors. Multivariate Cox regression was used to determine the relationship between ACAG and in-hospital mortality. Results A total of 344 patients (of them 81 non-survivors) were analyzed in this study. Patients with higher ACAG intended to present significantly higher in-hospital mortality, APACHE II score, creatine, lower albumin, and bicarbonate. Multivariate Cox regression analysis after matching demonstrated that white blood cell count, platelet count, and higher ACAG were independently associated with higher in-hospital mortality (ACAG ≤ 14.87 as a reference, 14.87 < ACAG ≤ 19.03 mmol/L with HR of 2.34 and 95% CI of 1.15–4.76, ACAG >19.03 with HR of 3.46 and 95% CI of 1.75–6.84). Conclusion Higher ACAG was independently associated with higher in-hospital mortality in patients with AP after matching the baseline between the survivors and non-survivors.

Albumin Corrected Anion Gap and the Risk of in-Hospital Mortality in Patients with Acute Pancreatitis: A Retrospective Cohort Study

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