Here is a recap of the stories that appeared last week at Science-Based Medicine, a multi-author skeptical blog that separates the science from the woo in medicine.

Placebo effects without deception? Well, not exactly… (David Gorski) A new study claims that placebos work even when patients are told they are placebos; but they deceived subjects by misrepresenting placebos as having been rigorously shown by science to produce healing processes.

Lest We Forget: Influenza Can Be Devastating (Harriet Hall) A review of the book The Great Influenza, which explains the history, the science, and the deadly potential of influenza. A cautionary tale with horror stories from the 1918 pandemic that killed more people in 24 weeks than AIDS did in 24 years.

CAM Use by Brain Tumor Patients (Steven Novella) A new study shows that 40% of patients with incurable brain gliomas sought some type of complementary or alternative treatment. The popularity of CAM is generally exaggerated, primarily by expanding the loose definition of CAM to include common activities, and ignoring the fact that most people use it in addition to conventional treatment.

The Acupuncture and Fasciae Fallacy (Ben Kavoussi) Efforts to relate acupuncture points and meridians to connective tissue planes are not only unconvincing but misguided. Acupuncture was based on a rudimentary and prescientific model of blood vessels and nerves, on astrology, and on bloodletting.

A Disconnect between cell phone fears and science (Lorne Trottier) Devra Davis’ book Disconnect is a tract that conspiracy theorists will love. It sheds no objective light on the often confusing scientific data in this area. It misstates the facts and misrepresents the scientific findings.

Compare and Contrast (Mark Crislip) Dr. Crislip describes his experience in quality improvement as chair of his institution’s Infection Control program.  Science-based medicine takes safety and quality seriously and strives constantly with research and its application to improve care, while alternative medicine is immune to new data and unwilling to change.