Gram stain to the rescue: a case report of cerebral phaeohyphomycosis by Cladophialophora bantiana in an immunocompetent 24-year-old.

BACKGROUND: Fungal brain abscesses in immunocompetent patients are exceedingly rare. Cladophialophora bantiana is the most common cause of cerebral phaeohyphomycosis, a dematiaceous mold. Radiological presentation can mimic other disease states, with diagnosis through surgical aspiration and growth of melanized fungi in culture. Exposure is often unknown, with delayed presentation and diagnosis. CASE PRESENTATION: We present a case of cerebral phaeohyphomycosis in a 24-year-old with no underlying conditions or risk factors for disease. He developed upper respiratory symptoms, fevers, and headaches over the course of 2 months. On admission, he underwent brain MRI which demonstrated three parietotemporal rim-enhancing lesions. Stereotactic aspiration revealed a dematiaceous mold on staining and the patient was treated with liposomal amphotericin B, 5-flucytosine, and posaconazole prior to culture confirmation. He ultimately required surgical excision of the brain abscesses and prolonged course of antifungal therapy, with clinical improvement. CONCLUSIONS: Culture remains the gold standard for diagnosis of infection. Distinct microbiologic findings can aid in identification and guide antimicrobial therapy. While little guidance exists on treatment, patients have had favorable outcomes with surgery and combination antifungal therapy. In improving awareness, clinicians may accurately diagnose disease and initiate appropriate therapy in a more timely manner.

PTEN expression and morphological patterns in prostatic adenocarcinoma.

AIMS: Cribriform morphology, which includes intraductal carcinoma (IDCP) and invasive cribriform carcinoma, is an indicator of poor prognosis in prostate cancer. Phosphatase and tensin homologue (PTEN) loss is a predictor of adverse clinical outcomes. The association between PTEN expression and morphological patterns of prostate cancer is unclear. METHODS AND RESULTS: We explored the association between PTEN expression by immunohistochemistry, Gleason pattern 4 morphologies, IDCP and biochemical recurrence (BCR) in 163 radical prostatectomy specimens. IDCP was delineated from invasive cribriform carcinoma by p63 positive immunohistochemical staining in basal cells. Combined invasive cribriform carcinoma and IDCP were associated with a higher cumulative incidence of BCR [hazard ratio (HR) = 5.06; 2.21, 11.6, P < 0.001]. When including PTEN loss in the analysis, invasive cribriform carcinoma remained predictive of BCR (HR = 3.72; 1.75, 7.94, P = 0.001), while PTEN loss within invasive cribriform carcinoma did not. Glomeruloid morphology was associated with lower odds of cancer stage pT3 and lower cumulative incidence of BCR (HR = 0.27; 0.088, 0.796, P = 0.018), while PTEN loss within glomeruloid morphology was associated with a higher cumulative incidence of BCR (HR = 4.07; 1.04, 15.9, P = 0.043). CONCLUSIONS: PTEN loss within glomeruloid pattern was associated with BCR. The presence of any cribriform pattern was associated with BCR, despite PTEN loss not significantly associated with invasive cribriform carcinoma. We speculate that other drivers independent from PTEN loss may contribute to poor prognostic features in cribriform carcinoma.

Open surgical disconnection for congenital, multi-hole, pial arteriovenous fistulae in non-eloquent cortex.

Intracranial pial arteriovenous fistulae (pAVFs), a direct shunt between a feeding artery and a venous channel with the absence of a true nidus characteristic of other types of arteriovenous malformations, are rare. We report a seven-year-old girl with an incidental intracranial pAVF. Following partial embolization with a combination of platinum coils and liquid embolic material, this lesion was surgically disconnected and a definitive cure was achieved. Based on the particular characteristics of this lesion-multiple, small arterial feeders, superficial location, and proximity to the non-eloquent cortex-we feel this vascular lesion represents a subset of pAVFs that may be most reasonably and safely treated by open surgery. While staged embolization has recently gained popularity as a treatment option, the additive risk of multiple embolizations as well as repeated exposure to ionizing radiation should not be understated, especially in the pediatric population. Furthermore, given the paucity of data on the long-term effectiveness of embolization, surgery remains an elegant and durable treatment option for pAVFs in carefully selected patients.

Artificial Intelligence in Plasma Cell Myeloma: Neural Networks and Support Vector Machines in the Classification of Plasma Cell Myeloma Data at Diagnosis.

BACKGROUND: Plasma cell neoplasm and/or plasma cell myeloma (PCM) is a mature B-cell lymphoproliferative neoplasm of plasma cells that secrete a single homogeneous immunoglobulin called paraprotein or M-protein. Plasma cells accumulate in the bone marrow (BM) leading to bone destruction and BM failure. Diagnosis of PCM is based on clinical, radiologic, and pathological characteristics. The percent of plasma cells by manual differential (bone marrow morphology), the white blood cell (WBC) count, cytogenetics, fluorescence in situ hybridization (FISH), microarray, and next-generation sequencing of BM are used in the risk stratification of newly diagnosed PCM patients. The genetics of PCM is highly complex and heterogeneous with several genetic subtypes that have different clinical outcomes. National Comprehensive Cancer Network guidelines recommend targeted FISH analysis of plasma cells with specific DNA probes to detect genetic abnormalities for the staging of PCM (4.2021). Recognition of risk categories through training software for classification of high-risk PCM and a novel way of addressing the current approaches through bioinformatics will be a significant step toward automation of PCM analysis. METHODS: A new artificial neural network (ANN) classification model was developed and tested in Python programming language with a first data set of 301 cases and a second data set of 176 cases for a total of 477 cases of PCM at diagnosis. Classification model was also developed with support vector machines (SVM) algorithm in R studio and interactive data visuals using Tableau. RESULTS: The resulting ANN algorithm had 94% accuracy for the first and second data sets with a classification summary of precision (PPV): 0.97, recall (sensitivity): 0.76, f1 score: 0.83, and accuracy of logistic regression of 1.0. SVM of plasma cells versus TP53 revealed a 95% accuracy level. CONCLUSION: A novel classification model based only on specific morphological and genetic variables was developed using a machine learning algorithm, the ANN. ANN identified an association of WBC and BM plasma cell percentage with two of the high-risk genetic categories in the diagnostic cases of PCM. With further training and testing of additional data sets that include morphologic and additional genetic rearrangements, the newly developed ANN model has the potential to develop an accurate classification of high-risk categories of PCM.

Rat model of blood-brain barrier disruption to allow targeted neurovascular therapeutics.

Endothelial cells with tight junctions along with the basement membrane and astrocyte end feet surround cerebral blood vessels to form the blood-brain barrier(1). The barrier selectively excludes molecules from crossing between the blood and the brain based upon their size and charge. This function can impede the delivery of therapeutics for neurological disorders. A number of chemotherapeutic drugs, for example, will not effectively cross the blood-brain barrier to reach tumor cells(2). Thus, improving the delivery of drugs across the blood-brain barrier is an area of interest. The most prevalent methods for enhancing the delivery of drugs to the brain are direct cerebral infusion and blood-brain barrier disruption(3). Direct intracerebral infusion guarantees that therapies reach the brain; however, this method has a limited ability to disperse the drug(4). Blood-brain barrier disruption (BBBD) allows drugs to flow directly from the circulatory system into the brain and thus more effectively reach dispersed tumor cells. Three methods of barrier disruption include osmotic barrier disruption, pharmacological barrier disruption, and focused ultrasound with microbubbles. Osmotic disruption, pioneered by Neuwelt, uses a hypertonic solution of 25% mannitol that dehydrates the cells of the blood-brain barrier causing them to shrink and disrupt their tight junctions. Barrier disruption can also be accomplished pharmacologically with vasoactive compounds such as histamine(5) and bradykinin(6). This method, however, is selective primarily for the brain-tumor barrier(7). Additionally, RMP-7, an analog of the peptide bradykinin, was found to be inferior when compared head-to-head with osmotic BBBD with 25% mannitol(8). Another method, focused ultrasound (FUS) in conjunction with microbubble ultrasound contrast agents, has also been shown to reversibly open the blood-brain barrier(9). In comparison to FUS, though, 25% mannitol has a longer history of safety in human patients that makes it a proven tool for translational research(10-12). In order to accomplish BBBD, mannitol must be delivered at a high rate directly into the brain's arterial circulation. In humans, an endovascular catheter is guided to the brain where rapid, direct flow can be accomplished. This protocol models human BBBD as closely as possible. Following a cut-down to the bifurcation of the common carotid artery, a catheter is inserted retrograde into the ECA and used to deliver mannitol directly into the internal carotid artery (ICA) circulation. Propofol and N2O anesthesia are used for their ability to maximize the effectiveness of barrier disruption(13). If executed properly, this procedure has the ability to safely, effectively, and reversibly open the blood-brain barrier and improve the delivery of drugs that do not ordinarily reach the brain (8,13,14).