Fatal canine parvovirus type 2a and 2c infections in wild Chinese pangolins (Manis pentadactyla) in southern China.

The Chinese pangolin (Manis pentadactyla) is a critically endangered scale-covered mammal belonging to the order Pholidota. Wild pangolins are notably susceptible to pathogen infection and are typically characterized by impoverished health. However, little is currently known regarding the viruses prevalent among pangolins. In this study, we report the detection of two subtypes of canine parvovirus type 2 (CPV-2), namely CPV-2a and CPV-2c, both of which caused severe diarrheal disease in two post-rescue pangolins with fatal consequences. As in CPV-2-infected dogs, intensive lesion of the mucosal layer of the small intestines is a prominent feature in infected pangolins. Moreover, the immunochemistry results demonstrated that CPV-2 antigens were distributed in the crypts of small intestine. Additionally, typical parvovirus-associated CPV-2 were detected after four passages in F81 cells, and typical parvovirus-like particles, approximately 20 nm in diameter, were observed in the cell supernatants. Phylogenetic analysis revealed that the VP2 viral protein sequences (GenBank accession number OP208805) isolated from one pangolin (termed P1) were classified as CPV-2c, with 99.8% identity to a CPV-2c strain (MN832850) isolated from a Taiwanese pangolin found in Taiwan Province. In contrast, VP2 sequences (#OP208806) obtained from the second pangolin (P2) were classified as CPV-2a, with 99.8% identity to a CPV-2a strain (KY386858) isolated from southern China. In this study, we thus confirmed the infection of pangolins with CPV-2c in mainland China and demonstrated that CPV-2a also can infect pangolins. Based on these findings, we recommend that further investigations should be conducted to establish the interspecies transmission of these viruses among wild pangolins, wild carnivores, and stray dogs.

Characterizing the critical features when personalizing antihypertensive drugs using spectrum analysis and machine learning methods.

Globally, methods of controlling blood pressure in hypertension patients remain inefficient. The difficulty of prescribing appropriate drugs specific to a patient's clinical features serves as one of the most important factors. Characterizing the critical drug-related features, just like that of the antibacterial spectrum (where each item is sensitive to the targeted drug's effectiveness or a specified indication), may help a doctor easily prescribe appropriate drugs by matching a patient's attributes with drug-related features, and effectiveness of the selected drugs would also be ascertained. In this study, we aimed to apply data mining methods to obtain the clinical characteristics spectrum or important clinical features of five frequently used drugs (Irbesartan, Metoprolol, Felodipine, Amlodipine, and Levamlodipine) for hypertension control by comparing successful and unsuccessful cases. Spectrum analysis based on a statistical method and five algorithms based on machine learning were used to extract the critical clinical features. A visualized relative weight matrix was then achieved by combining the results from the characteristic spectrum and machine learning-based methods. Our results indicated that the five targeted antihypertension agents had different importance orders of the 15 relative clinical features. Clinical analysis showed that the extracted important clinical attributes of the five drugs were both reasonable and meaningful in the selection of hypertension treatment. Therefore, our study provided a data-driven reference for the personalization of clinical antihypertensive drugs.

A simple method for assessing free brain/free plasma ratios using an in vitro model of the blood brain barrier.

Historically, the focus has been to use in vitro BBB models to optimize rate of drug delivery to the CNS, whereas total in vivo brain/plasma ratios have been used for optimizing extent. However, these two parameters do not necessarily show good correlations with receptor occupancy data or other pharmacological readouts. In line with the free drug hypothesis, the use of unbound brain concentrations (Cu,br) has been shown to provide the best correlations with pharmacological data. However, typically the determination of this parameter requires microdialysis, a technique not ideally suited for screening in early drug development. Alternative, and less resource-demanding methodologies to determine Cu,br employ either equilibrium dialysis of brain homogenates or incubations of brain slices in buffer to determine fraction unbound brain (fu,br), which is subsequently multiplied by the total brain concentration to yield Cu,br. To determine Cu,br/Cu,pl ratios this way, still requires both in vitro and in vivo experiments that are quite time consuming. The main objective of this study was to explore the possibility to directly generate Cu,br/Cu,pl ratios in a single in vitro model of the BBB, using a co-culture of brain capillary endothelial and glial cells in an attempt to mimick the in vivo situation, thereby greatly simplifying existing experimental procedures. Comparison to microdialysis brain concentration profiles demonstrates the possibility to estimate brain exposure over time in the BBB model. A stronger correlation was found between in vitro Cu,br/Cu,pl ratios and in vivo Cu,br/Cu,pl obtained using fu,br from brain slice than with fu,br from brain homogenate for a set of 30 drugs. Overall, Cu,br/Cu,pl ratios were successfully predicted in vitro for 88% of the 92 studied compounds. This result supports the possibility to use this methodology for identifying compounds with a desirable in vivo response in the CNS early on in the drug discovery process.

Delayed cerebrospinal fluid rhinorrhea after gamma knife surgery in a patient with a growth hormone-secreting adenoma.

We report a patient who developed delayed cerebrospinal fluid (CSF) rhinorrhea 11 years after gamma knife radiosurgery for a growth hormone (GH)-secreting adenoma. The treatment dose was 18 Gy for the tumor margin (50% isodose). One year later, an MRI of the head revealed that the tumor size had decreased. Eleven years later, the patient developed CSF rhinorrhea from the left nostril. Subsequent MRI examination revealed complete remission of the tumor in the sella turcica and the empty sella. The patient was admitted for direct endoscopic surgical repair of the skull base. We suggest that the cause of the CSF rhinorrhea is secondary empty sella. The other potential causes may be the original invasiveness of the tumor or delayed radiation damage to the mucous membranes of the skull. Long-term follow-up is required to monitor recurrence of CSF rhinorrhea.