Protective role of nutritional plants containing flavonoids in hair follicle disruption: a review

Hair loss is a disorder in which the hair falls out from skin areas such as the scalp and the body. Several studies suggest the use of herbal medicine to treat related disorders, including alopecia. Dermal microcirculation is essential for hair maintenance, and an insufficient blood supply can lead to hair follicles (HF) diseases. This work aims to provide an insight into the ethnohistorical records of some nutritional compounds containing flavonoids for their potential beneficial features in repairing or recovering from hair follicle disruption. We started from a query for “alopecia” OR “hair loss” AND “Panax ginseng C.A. Mey.“ (or other six botanicals) terms included in Pubmed and Web of Sciences articles. The activities of seven common botanicals introduced with diet (Panax ginseng C.A. Mey., Malus pumila Mill cultivar Annurca, Coffea arabica, Allium sativum L., Camellia sinensis (L.) Kuntze, Rosmarinum officinalis L., Capsicum annum L.) are discussed, which are believed to reduce the rate of hair loss or stimulate new hair growth. In this review, we pay our attention on the molecular mechanisms underlying the bioactivity of the aforementioned nutritional compounds in vivo, ex vivo and in vitro studies. There is a need for systematic evaluation of the most commonly used plants to confirm their anti-hair loss power, identify possible mechanisms of action, and recommend their best adoption

Decentralized Trajectory Tracking Control for Soft Robots Interacting With the Environment

Despite the classic nature of the problem, trajectory tracking for soft robots, i.e., robots with compliant elements deliberately introduced in their design, still presents several challenges. One of these is to design controllers which can obtain sufficiently high performance while preserving the physical characteristics intrinsic to soft robots. Indeed, classic control schemes using high-gain feedback actions fundamentally alter the natural compliance of soft robots effectively stiffening them, thus de facto defeating their main design purpose. As an alternative approach, we consider here using a low-gain feedback, while exploiting feedforward components. In order to cope with the complexity and uncertainty of the dynamics, we adopt a decentralized, iteratively learned feedforward action, combined with a locally optimal feedback control. The relative authority of the feedback and feedforward control actions adapts with the degree of uncertainty of the learned component. The effectiveness of the method is experimentally verified on several robotic structures and working conditions, including unexpected interactions with the environment, where preservation of softness is critical for safety and robustness

Erratum to nodal management and upstaging of disease. Initial results from the Italian VATS Lobectomy Registry

[This corrects the article DOI: 10.21037/jtd.2017.06.12.]