Mucinous Cystadenoma of the Appendix in a Patient with Systemic Lupus Erthematosus

A 38-year-old female with systemic lupus erythematosus presented with abdominal pain, diarrhea and iron-deficient anemia. Computed tomogram showed a 2x4 cm inhomogeneous lesion of the right adnexa. An unusual mass was identified extending from the appendiceal orifice at colonoscopy, and an 8 cm tubular appendix, apparently prolapsed into the cecum, was identified at celiotomy. An appendectomy with cecectomy was performed. On cut section, mucin was extruded from the lumen of the appendix. A mucinous neoplasm of the appendix with mucinous dissection to the serosal surface was reported at the time of frozen section. No gross ovarian pathology or peritoneal implants were noted. Cystadenoma with associated mucocele formation was verified by permanent histology. Mucocele of the vermiform appendix is a rare condition associated with neoplastic transformation in approximately 75% of all cases. Benign mucinous cystadenoma of the appendix should be differentiated from cystadenocarcinoma by frozen section at the time of celiotomy to ensure appropriate treatment. While systemic lupus erythematosus can lead to cutaneous mucinosis, an association with mucinous cystadenoma of the appendix has not been previously reported. Surveillance for metachronous colonic neoplasms is warranted in patients diagnosed with a mucinous neoplasm of the appendix

Characterizing the tumor microenvironment in rare renal cancer histological types

The tumor microenvironment (TME), including immune cells, cancer-associated fibroblasts, endothelial cells, adjacent normal cells, and others, plays a crucial role in influencing tumor behavior and progression. Here, we characterized the TME in 83 primary renal tumors and matched metastatic or recurrence tissue samples (n = 15) from papillary renal cell carcinoma (pRCC) types 1 (n = 20) and 2 (n = 49), collecting duct carcinomas (CDC; n = 14), and high-grade urothelial carcinomas (HGUC; n = 5). We investigated 10 different markers of immune infiltration, vasculature, cell proliferation, and epithelial-to-mesenchymal transition by using machine learning image analysis in conjunction with immunohistochemistry. Marker expression was compared by Mann-Whitney and Kruskal-Wallis tests and correlations across markers using Spearman's rank correlation coefficient. Multivariable Poisson regression analysis was used to compare marker expression between histological types, while accounting for variation in tissue size. Several immune markers showed different rates of expression across histological types of renal carcinoma. Using pRCC1 as reference, the incidence rate ratio (IRR) of CD3+ T cells (IRR [95% confidence interval, CI] = 2.48 [1.53-4.01]) and CD20+ B cells (IRR [95% CI] = 4.38 [1.22-5.58]) was statistically significantly higher in CDC. In contrast, CD68+ macrophages predominated in pRCC1 (IRR [95% CI] = 2.35 [1.42-3.9]). Spatial analysis revealed CD3+ T-cell and CD20+ B-cell expressions in CDC to be higher at the proximal (p < 0.0001) and distal (p < 0.0001) tumor periphery than within the central tumor core. In contrast, expression of CD68+ macrophages in pRCC2 was higher in the tumor center compared to the proximal (p = 0.0451) tumor periphery and pRCC1 showed a distance-dependent reduction, from the central tumor, in CD68+ macrophages with the lowest expression of CD68 marker at the distal tumor periphery (p = 0.004). This study provides novel insights into the TME of rare kidney cancer types, which are often understudied. Our findings of differences in marker expression and localization by histological subtype could have implications for tumor progression and response to immunotherapies or other targeted therapies

Endometrial carcinoma, grossing and processing issues: recommendations of the International Society of Gynecologic Pathologists.

Endometrial cancer is the most common gynecologic neoplasm in developed countries; however, updated universal guidelines are currently not available to handle specimens obtained during the surgical treatment of patients affected by this disease. This article presents recommendations on how to gross and submit sections for microscopic examination of hysterectomy specimens and other tissues removed during the surgical management of endometrial cancer such as salpingo-oophorectomy, omentectomy, and lymph node dissection-including sentinel lymph nodes. In addition, the intraoperative assessment of some of these specimens is addressed. These recommendations are based on a review of the literature, grossing manuals from various institutions, and a collaborative effort by a subgroup of the Endometrial Cancer Task Force of the International Society of Gynecological Pathologists. The aim of these recommendations is to standardize the processing of endometrial cancer specimens which is vital for adequate pathological reporting and will ultimately improve our understanding of this disease

Pathologic Prognostic Factors in Endometrial Carcinoma (Other Than Tumor Type and Grade)

Although endometrial carcinoma (EC) is generally considered to have a good prognosis, over 20% of women with EC die of their disease, with a projected increase in both incidence and mortality over the next few decades. The aim of accurate prognostication is to ensure that patients receive optimal treatment and are neither overtreated nor undertreated, thereby improving patient outcomes overall. Patients with EC can be categorized into prognostic risk groups based on clinicopathologic findings. Other than tumor type and grade, groupings and recommended management algorithms may take into account age, body mass index, stage, and presence of lymphovascular space invasion. The molecular classification of EC that has emerged from the Cancer Genome Atlas (TCGA) study provides additional, potentially superior, prognostic information to traditional histologic typing and grading. This classifier does not, however, replace clinicopathologic risk assessment based on parameters other than histotype and grade. It is envisaged that molecular and clinicopathologic prognostic grouping systems will work better together than either alone. Thus, while tumor typing and grading may be superseded by a classification based on underlying genomic abnormalities, accurate assessment of other pathologic parameters will continue to be key to patient management. These include those factors related to staging, such as depth of myometrial invasion, cervical, vaginal, serosal surface, adnexal and parametrial invasion, and those independent of stage such as lymphovascular space invasion. Other prognostic parameters will also be discussed. These recommendations were developed from the International Society of Gynecological Pathologists Endometrial Carcinoma project

Circulating tumor DNA is readily detectable among Ghanaian breast cancer patients supporting non-invasive cancer genomic studies in Africa.

Circulating tumor DNA (ctDNA) sequencing studies could provide novel insights into the molecular pathology of cancer in sub-Saharan Africa. In 15 patient plasma samples collected at the time of diagnosis as part of the Ghana Breast Health Study and unselected for tumor grade and subtype, ctDNA was detected in a majority of patients based on whole- genome sequencing at high (30×) and low (0.1×) depths. Breast cancer driver copy number alterations were observed in the majority of patients

Precise mapping of the magnetic field in the CMS barrel yoke using cosmic rays

This is the Pre-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2010 IOPThe CMS detector is designed around a large 4 T superconducting solenoid, enclosed in a 12 000-tonne steel return yoke. A detailed map of the magnetic field is required for the accurate simulation and reconstruction of physics events in the CMS detector, not only in the inner tracking region inside the solenoid but also in the large and complex structure of the steel yoke, which is instrumented with muon chambers. Using a large sample of cosmic muon events collected by CMS in 2008, the field in the steel of the barrel yoke has been determined with a precision of 3 to 8% depending on the location.This work is supported by FMSR (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MoST, and NSFC (China); COLCIENCIAS (Colombia); MSES (Croatia); RPF (Cyprus); Academy of Sciences and NICPB (Estonia); Academy of Finland, ME, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NKTH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); NRF (Korea); LAS (Lithuania); CINVESTAV, CONACYT, SEP, and UASLP-FAI (Mexico); PAEC (Pakistan); SCSR (Poland); FCT (Portugal); JINR (Armenia, Belarus, Georgia, Ukraine, Uzbekistan); MST and MAE (Russia); MSTDS (Serbia); MICINN and CPAN (Spain); Swiss Funding Agencies (Switzerland); NSC (Taipei); TUBITAK and TAEK (Turkey); STFC (United Kingdom); DOE and NSF (USA)

PandemCap: decision support tool for epidemic management

Pandemics or high impact epidemics are one of the biggest threats facing humanity today. While a complete elimination of the occurrence of such threats is improbable, it is possible to contain their impact by efficient management which in turn depends on effective decision-making. In the event of a pandemic the data flows are enormous and pose severe cognitive overload to the public health decision-makers. In this context, this paper presents PandemCap, an innovative decision support tool that can be used by the public health officials for making better and well informed decisions in the event of pandemics or high impact epidemics. PandemCap provides an interactive, flexible platform to public health decision-makers by making extensive use of techniques from the domains of visual analytics and epidemic modeling. In addition, the tool also allows for the study of the impact of various interventions or control measures such as the use of vaccines, anti-virals, hospital beds, and ventilators.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight). Part of the research was conducted by the PANDEM project which has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no 652868). The authors also want to thank Andrea Barraza-Urbina for her comments on our work