To characterize steady-state indinavir pharmacokinetics in cerebrospinal fluid and plasma, 8 adults infected with human immunodeficiency virus underwent intensive cerebrospinal fluid sampling while receiving indinavir (800 mg every 8 hours) plus nucleoside reverse transcriptase inhibitors. Nine and 11 serial cerebrospinal fluid and plasma samples, respectively, were obtained from each subject. Free indinavir accounted for 94.3% of the drug in cerebrospinal fluid and 41.7% in plasma. Mean values of cerebrospinal fluid peak concentration, concentration at 8 hours, and area under the concentration-time profile calculated over the interval 0 to 8 hours [AUC(0-8)] for free indinavir were 294 nmol/L, 122 nmol/L, and 1616 nmol/L x h, respectively. The cerebrospinal fluid-to-plasma AUC(0-8) ratio for free indinavir was 14.7% +/- 2.6% and did not correlate with indexes of blood-brain barrier integrity or intrathecal immune activation. Indinavir achieves levels in cerebrospinal fluid that should contribute to control of human immunodeficiency virus type 1 replication in this compartment. The cerebrospinal fluid-to-plasma AUC(0-8) ratio suggests clearance mechanisms in addition to passive diffusion across the blood-cerebrospinal fluid barrier, perhaps by P-glycoprotein-mediated efflux.

A body of research demonstrates examples of in vitro and in vivo synergy between natural products and anti-neoplastic drugs for some cancers. However, the underlying biological mechanisms are still elusive. To better understand biological entities targeted by natural products and therefore provide rational evidence for future novel combination therapies for cancer treatment, we assess the targetable space of natural products using public domain compound-target information. When considering pathways from the Reactome database targeted by natural products, we found an increase in coverage of 61% (725 pathways), relative to pathways covered by FDA approved cancer drugs collected in the Cancer Targetome, a resource for evidence-based drug-target interactions. Not only is the coverage of pathways targeted by compounds increased when we include natural products, but coverage of targets within those pathways is also increased. Furthermore, we examined the distribution of cancer driver genes across pathways to assess relevance of natural products to critical cancer therapeutic space. We found 24 pathways enriched for cancer drivers that had no available cancer drug interactions at a potentially clinically relevant binding affinity threshold of < 100nM that had at least one natural product interaction at that same binding threshold. Assessment of network context highlighted the fact that natural products show target family groupings both distinct from and in common with cancer drugs, strengthening the complementary potential for natural products in the cancer therapeutic space. In conclusion, our study provides a foundation for developing novel cancer treatment with the combination of drugs and natural products.

Electrodermal screening (EDS) is based on three commonly held assumptions: acupuncture points (APs) have lower electrical resistance than non-APs; resistance at APs varies with health and disease; and effective acupuncture treatments are associated with normalization of resistance at APs. Although evidence confirming these assumptions is limited, EDS is frequently practiced worldwide. Researchers are also beginning to assess EDS' utility as an outcome measure in acupuncture trials. Fundamental in developing EDS as a research tool is the need for an accurate and reliable measurement. We developed an automated multichannel prototype system, the Octopus, and recorded electrical resistance and capacitance at eight skin sites in 33 healthy participants over 2 hours. The Octopus accurately measured against known resistors (within 2.5% of the mean value) and capacitors (within 10% of the mean value), and yielded repeatable readings at all eight skin sites: LR 1 (r = 0.79), SP 1 (r = 0.79), toe non-AP (r = 0.77), LU 9 (r = 0.97), PC 6 (r = 0.96), wrist non-APs (r = 0.97), SP 6 (r = 0.96), and leg non-APs (r = 0.97). Resistance at APs was significantly lower than the nearby non-APs in one out of three comparisons.

Background With the growing adoption of the electronic health record (EHR) worldwide over the last decade, new opportunities exist for leveraging EHR data for detection of rare diseases. Rare diseases are often not diagnosed or delayed in diagnosis by clinicians who encounter them infrequently. One such rare disease that may be amenable to EHR-based detection is acute hepatic porphyria (AHP). AHP consists of a family of rare, metabolic diseases characterized by potentially life-threatening acute attacks and chronic debilitating symptoms. The goal of this study was to apply machine learning and knowledge engineering to a large extract of EHR data to determine whether they could be effective in identifying patients not previously tested for AHP who should receive a proper diagnostic workup for AHP.

Objective There are many commercially available instruments for measuring electrical conductance, but there is little information about their reliability. The aim of this study was to quantify measurement variability and assess reliability of the AcuGraph system—a commonly used electrodermal screening device. Methods Four experiments were conducted to measure variability in electrical conductance readings obtained by the AcuGraph system. The fi rst involved measuring known resistors. The second measured non-human organic matter. The third was a test–retest assessment of the Yuan-Source and Jing-Well points in 30 healthy volunteers who were measured by a single operator. The fourth was an interoperator reliability evaluation of seven acupuncturists at the Yuan-Source and Jing-Well acupoints on four individuals at two time points. Results Against known resistors, the AcuGraph had an average coeffi cient of variability (CV) of 1.8% between operators and test–retests. On non-human organic material the AcuGraph had an average CV of 0.9% and 2.8%. When a single operator tested 30 participants, the average reliability for the Yuan-Source points was 0.86 and 0.76 for Jing-Well points with a CV of 23.2% and 25.9% respectively. The average CV for the seven acupuncturists was 24.5% on Yuan-Source points and 23.7% on Jing-Well points. Conclusions The AcuGraph measures known resistors and organic matter accurately and reliably. Skin conductance at acupoints recorded by one operator was also reliable. There was less consistency in electrodermal recordings obtained by seven different operators. Operator training and technical improvements to the AcuGraph may improve consistency among operators.