Surgical Resection is Preferred in Selected Solitary Hepatocellular Carcinoma with Portal Vein Tumor Thrombosis

Backgrounds: Sorafenib is the standard care for hepatocellular carcinoma (HCC) patients with portal vein tumor thrombosis (PVTT), though it offers limited survival. This study was designed to compare clinical outcomes between liver resection (surgery) and trans-arterial chemoembolization plus radiotherapy (TACE-RT) as the initial treatment modality for resectable treatment-naïve solitary HCC combined with subsegmental (Vp1), segmental (Vp2), and lobar (Vp3) PVTT. Methods: From the institutional HCC registry, we identified 116 patients diagnosed with resectable treatment-naïve HCC with Vp1-Vp3 PVTT based on radiologic images who received surgery (n=44) or TACE-RT (n=72) as a primary treatment between 2010 and 2015. A propensity score matching (PSM) model was created. Results: The TACE-RT group had a higher tumor burden (tumor size, extent, and markers) than the surgery group. Cumulative patient survival curve in the surgery group was significantly higher than in the TACE-RT group before and after PSM. Liver function was relatively well-preserved in the surgery group compared with the TACE-RT group. TACE-RT group, male, increased alkaline phosphatase, and increased platelet count were predisposing factors for patient death in resectable treatment-naïve solitary HCC with PVTT. Conclusions: The present study suggests that surgery should be considered as an initial treatment in resectable treatment-naïve solitary HCC with Vp1-Vp3 PVTT.

Medical Tourism Patient Mortality

Medical tourism is a process in which a consumer travels from one's place of residence and receives medical treatment, thus becoming a patient. Patients Beyond Borders (PBB) forecasts some 1.9 million Americans will travel outside the United States for medical care in 2019. This chapter explores media representations of patient mortality associated with medical tourism within the global news media occurring between 2009-2019. A qualitative content analysis of 50 patient mortality cases found that (1) a majority of media representations of medical tourism patient death are of middle-class, minority females between 25-55 years of age who seek cosmetic surgery internationally; (2) sudden death, grief, and bereavement counseling is noticeably absent from medical tourism providers (MTPs); and (3) risk information from authority figures within the media reports is often vague and abstract. A detailed list of health communication recommendations and considerations for future medical tourists and their social support systems are provided.

Evaluation of Four Lymph Node Classifications for the Prediction of Survival in Hilar Cholangiocarcinoma

Background An important prognostic indicator of hilar cholangiocarcinoma (HCCA) in patients after surgery is metastasis of lymph nodes (LN). However, there are many types of LN staging systems to the issue of a better determination of the prognosis of patients through the lymphatic staging system which needs research. Based on the above, we tried to re-evaluate the staging system of HCCA LNs. We compared the American Joint Committee on Cancer (AJCC), number of metastatic LNs (MLN), ratio of LN (LNR), and log odds of MLNs (LODDS) in individuals undergoing curative resection to determine the best LN staging system. Methods In the current study, we retrospectively analyzed 229 patients undergoing curative resection. We evaluated the impact of the stage of AJCC pN, LNR, LODDS, and MLN on OS (overall survival) and RFS (recurrence-free survival). According to the curve of receiver operating characteristic (ROC), we compared the predictive capacity of different staging systems of LN for survival and recurrence. Results Multivariate analysis results revealed that LODDS > − 0.45 (95% CI = 1.115–2.709, P = 0.015; 95% CI = 1.187–2.780, P = 0.006) are independent risk factors affecting OS and RFS, respectively. Compared with LN status, AJCC pN stage, MLN, and LNR, the variable having the highest area under the ROC curve (AUC) was LODDS when predicting 1-year, 3-year, and 5-year OS and RFS. Conclusion This study shows that metastasis of LNs is a key indicator for predicting patient death and recurrence. Among them, LODDS is the best LN staging system for the prognostic evaluation of HCCA patients after surgery. Clinicians can incorporate LODDS into HCCA patient lymphatic staging system for a more accurate prognosis of HCCA patients post-surgery.

Association Among End-Of-Life Discussions, Cancer Patients’ Quality of Life at End of Life, and Bereaved Families’ Mental Health

End-of-life discussions are essential for patients with advanced cancer, but there is little evidence about whether these discussions affect general ward patients and family outcomes. We investigated the status of end-of-life discussions and associated factors and their effects on patients’ quality of death and their families’ mental health. Participants in this retrospective cross-sectional observational study were 119 bereaved family members. Data were collected through a survey that included questions on the timing of end-of-life discussions, quality of palliative care, quality of patient death, and depression and grief felt by the families. Approximately 64% of the bereaved family members participated in end-of-life discussions between the patient and the attending physician, and 55% of these discussions took place within a month before death. End-of-life discussions were associated with the patients’ prognostic perception as “incurable, though there is hope for a cure” and “patients’ experience with end-of-life discussions with family before cancer.” There was a small decrease in depression and grief for families of patients who had end-of-life discussions. Those who did not have end-of-life discussions reported lower quality of end-of-life care.

tRNAGlyGCC-Derived Internal Fragment (i-tRF-GlyGCC) in Ovarian Cancer Treatment Outcome and Progression

Epithelial ovarian cancer (EOC) remains a highly-lethal gynecological malignancy, characterized by frequent recurrence, chemotherapy resistance and poor 5-year survival. Identifying novel predictive molecular markers remains an overdue challenge in the disease’s clinical management. Herein, in silico analysis of TCGA-OV highlighted the tRNA-derived internal fragment (i-tRF-GlyGCC) among the most abundant tRFs in ovarian tumors, while target prediction and gene ontology (GO) enrichment analysis predicted its implication in key biological processes. Thereafter, i-tRF-GlyGCC levels were quantified in a screening EOC (n = 98) and an institutionally-independent serous ovarian cancer (SOC) validation cohort (n = 100, OVCAD multicenter study). Disease progression and patient death were used as clinical endpoints for the survival analysis. Internal validation was performed by bootstrap analysis and the clinical net benefit was estimated by decision curve analysis. The analysis highlighted the significant association of i-tRF-GlyGCC with advanced FIGO stages, suboptimal debulking and most importantly, with early progression and poor overall survival of EOC patients. The OVCAD validation cohort corroborated the unfavorable predictive value of i-tRF-GlyGCC in EOC. Ultimately, evaluation of i-tRF-GlyGCC with the established/clinically used prognostic markers offered superior patient risk-stratification and enhanced clinical benefit in EOC prognosis. In conclusion, i-tRF-GlyGCC assessment could aid towards personalized prognosis and support precision medicine decisions in EOC.

Bone Cancer Detection Using Feature Extraction Based Machine Learning Model

Bone cancer is considered a serious health problem, and, in many cases, it causes patient death. The X-ray, MRI, or CT-scan image is used by doctors to identify bone cancer. The manual process is time-consuming and required expertise in that field. Therefore, it is necessary to develop an automated system to classify and identify the cancerous bone and the healthy bone. The texture of a cancer bone is different compared to a healthy bone in the affected region. But in the dataset, several images of cancer and healthy bone are having similar morphological characteristics. This makes it difficult to categorize them. To tackle this problem, we first find the best suitable edge detection algorithm after that two feature sets one with hog and another without hog are prepared. To test the efficiency of these feature sets, two machine learning models, support vector machine (SVM) and the Random forest, are utilized. The features set with hog perform considerably better on these models. Also, the SVM model trained with hog feature set provides an F 1 -score of 0.92 better than Random forest F 1 -score 0.77.

Anti-Leishmania infantum Antibody-Producing Plasma Cells in the Spleen in Canine Visceral Leishmaniasis

The spleen is involved in visceral leishmaniasis immunopathogenesis, and presents alterations in white-pulp microenvironments that are associated with an increased susceptibility to coinfections and patient death. Plasmacytosis in splenic red pulp (RP) is one observed alteration, but the specificity of antibody-secreting cells and the distribution of them has not yet been evaluated. We biotinylated soluble L. infantum membrane antigens (bSLMA) used as probes in modified immunohistochemistry, and detected the presence of anti-L. infantum antibody-secreting cells. Were used spleens from eight dogs from the endemic area for canine visceral leishmaniasis (CanL), and three healthier controls. The spleen sections were cryopreserved, and we performed modified immunohistochemistry. The ratio of plasma cells which were reactive to bSLMA (Anti-Leish-PC) in the spleen RP and periarteriolar lymphatic sheath (PALS) were calculated. Dogs with CanL present hyperglobulinemia and more plasma cells in their RP than the controls. Furthermore, dogs with CanL presented a lower proportion of Anti-Leish-PC in their RP than in PALS. Likewise, dysproteinemia was related to RP and PALS plasmacytosis, and a more severe clinical profile.

Moderate Static Magnet Fields Suppress Ovarian Cancer Metastasis via ROS-Mediated Oxidative Stress

Metastasis is the leading cause of cancer patient death, which is closely correlated with reactive oxygen species (ROS) levels. It is well known that the effects of ROS on tumors are diverse, depending on ROS concentration and cell type. We found that ovarian cancer cells have significantly lower levels of ROS than normal ovarian cells. Moreover, increased ROS levels in ovarian cancer cells can substantially inhibit their migration and invasion ability. Furthermore, the results show that moderate static magnetic field (SMF) can inhibit ovarian cancer cell migration, invasion, and stemness in a ROS-dependent manner. RNA sequencing results confirm that SMFs increased the oxidative stress level and reduced the stemness of ovarian cancer cells. Consistently, the expressions of stemness-related genes were significantly decreased, including hyaluronan receptor (CD44), SRY-box transcription factor 2 (Sox2), and cell myc proto-oncogene protein (C-myc). Furthermore, moderate SMFs provided by a superconducting magnet and permanent magnet have good biosafety and can both inhibit ovarian cancer metastasis in mice. Therefore, our study demonstrates the effects of SMFs on oxidative stress and metastasis in the ovarian cancer cells, which reveals the potential of applying SMF as a physical method in cancer therapy in the future.

Antirheumatic Drugs against COVID-19 from the Perspective of Rheumatologists

Coronavirus disease 2019 (COVID-19) remains a global threat to humanity. Its pathogenesis and different phases of disease progression are being elucidated under the pandemic. Active viral replication activates various immune cells and produces large amounts of inflammatory cytokines, which leads to the cytokine storm, a major cause of patient death. Therefore, viral inhibition is expected to be the most effective early in the course of the disease, while immunosuppressive treatment may be useful in the later stages to prevent disease progression. Based on the pathophysiology of rheumatic diseases, various immunomodulatory and immunosuppressive drugs are used for the diseases. Due to their mechanism of action, the antirheumatic drugs, including hydroxychloroquine, chloroquine, colchicine, calcineurin inhibitors (e.g., cyclosporine A and tacrolimus), glucocorticoids, cytokines inhibitors, such as anti-tumor necrosis factor-α (e.g., infliximab), anti-interleukin (IL)-6 (e.g., tocilizumab, sarilumab, and siltuximab), anti-IL-1 (e.g., anakinra and canakinumab) and Janus kinase inhibitors (e.g., baricitinib and tofacitinib), cytotoxic T lymphocyte-associated antigen 4 blockade agents (e.g., abatacept), and phosphodiesterase 4 inhibitors (e.g., apremilast), have been tried as a treatment for COVID-19. In this review, we discuss the mechanisms of action and clinical impact of these agents in the management of COVID-19.

Automatically hemodynamic analysis of AAA from CT images based on deep learning and CFD approaches

Abdominal aortic aneurysm is a serious disease which course is accompanied by the development of health complications and often leads to patient death due to aortic rupture. One of the powerful methods to estimate the risk of rupture is three-dimensional patient-specific hemodynamic analysis. In this study, we develop a software tool based on deep learning and CFD methods to perform automated computational hemodynamics with patient-specific geometry reconstructed from computed tomography images.