Acne inversa (AI), also known as hidradenitis suppurativa, is a chronic, recurrent, inflammatory disease of hair follicles that often runs in families. We studied six Chinese families with features of AI as well as additional skin lesions on back, face, nape, and waist and found independent loss-of-function mutations in PSENEN, PSEN1, or NCSTN, the genes encoding essential components of the γ-secretase multiprotein complex. Our results identify the γ-secretase component genes as the culprits for a subset of familial AI, implicate the γ-secretase-Notch pathway in the molecular pathogenesis of AI, and demonstrate that familial AI can be an allelic disorder of early-onset familial Alzheimer's disease.

SignificanceAnomalous sulfur isotopic compositions preserved in sedimentary rocks older than ∼2.5 billion years have been widely interpreted as the products of UV photolysis of sulfur dioxide in an anoxic atmosphere and used to track the history of primitive Earth and evolution of early life. In this study, we present strong observational evidence that there is an additional process that produces similar anomalous sulfur isotope signatures. This previously unknown origin not only offers a tool for quantifying the present-day atmospheric sulfur budget and evaluating its influences on climate and public health but also implies that anomalous sulfur isotopic compositions in some of the oldest rocks on Earth might have been produced in a way different from that previously thought.

Cycloplegia affected ACD and WTW but not AL or corneal curvature measurements. Generally, good agreement was found between the Lenstar and the IOLMaster, although not for WTW. Differences between these devices do not produce a clinically significant impact on IOL power.

Lower body segment trajectory and gait phase prediction is crucial for the control of assistance-as-needed robotic devices, such as exoskeletons. In order for a powered exoskeleton with phase-based control to determine and provide proper assistance to the wearer during gait, we propose an approach to predict segment trajectories up to 200 ms ahead (angular velocity of the thigh, shank and foot segments) and five gait phases (loading response, mid-stance, terminal stance, preswing and swing), based on collected data from inertial measurement units placed on the thighs, shanks, and feet. The approach we propose is a long-short term memory (LSTM)-based network, a modified version of recurrent neural networks, which can learn order dependence in sequence prediction problems. The algorithm proposed has a weighted discount loss function that places more weight in predicting the next three to five time frames but also contributes to an overall prediction performance for up to 10 time frames. The LSTM model was designed to learn lower limb segment trajectories using training samples and was tested for generalization across participants. All predicted trajectories were strongly correlated with the measured trajectories, with correlation coefficients greater than 0.98. The proposed LSTM approach can also accurately predict the five gait phases, particularly swing phase with 95% accuracy in inter-subject implementation. The ability of the LSTM network to predict future gait trajectories and gait phases can be applied in designing exoskeleton controllers that can better compensate for system delays to smooth the transition between gait phases.

Background/aimsTo evaluate the predictive performance of various predictors, including non-cycloplegic refractive error, for risk of myopia onset under pragmatic settings.MethodsThe Wenzhou Medical University Essilor Progression and Onset of Myopia Study is a prospective cohort study of schoolchildren aged 6–10 years from two elementary schools in Wenzhou, China. Non-cycloplegic refraction, ocular biometry and accommodation measurements were performed. Myopia was defined as spherical equivalent (SE) ≤−0.5 diopter (D). ORs using multivariable logistic regression were determined. Area under the curve (AUC) evaluation for predictors was performed.ResultsSchoolchildren who attended both baseline and 2-year follow-up were analysed (N=1022). Of 830 non-myopic children at baseline, the 2-year incidence of myopia was 27.6% (95% CI, 24.2% to 31.3%). Female gender (OR=2.2), more advanced study grades (OR=1.5), less hyperopic SE (OR=11.5 per D), longer axial length (AL; OR=2.3 per mm), worse presenting visual acuity (OR=2.3 per decimal), longer near work time (OR=1.1 per hour/day) and lower magnitude of positive relative accommodation (PRA; OR=1.4 per D) were associated with myopia onset. PRA (AUC=0.66), SE (AUC=0.64) and AL (AUC=0.62) had the highest AUC values. The combination of age, gender, parental myopia, SE, AL and PRA achieved an AUC of 0.74.ConclusionApproximately one in four schoolchildren had myopia onset over a 2-year period. The predictors of myopia onset include lower magnitude of PRA, less hyperopic SE, longer AL and female gender. Of these, non-cycloplegic SE and PRA were the top single predictors, which can facilitate risk profiling for myopia onset.

In this paper, we study the robust beamforming design for a simultaneous wireless information and power transfer (SWIPT) enabled system, with cooperative nonorthogonal multiple access (NOMA) protocol applied. A novel cooperative NOMA scheme is proposed, where the strong user with better channel conditions adopts power splitting (PS) scheme and acts as an energy-harvesting relay to transmit information to the weak user. The presence of channel uncertainties is considered and incorporated in our formulations to improve the design robustness and communication reliability. Specifically, only imperfect channel state information (CSI) is assumed to be available at the base station (BS), due to the reason that the BS is far away from both users and suffers serious feedback delay. To comprehensively address the channel uncertainties, two major design criteria are adopted, which are the outage-based constraint design and the worst-case based optimization. Then, our aim is to maximize the strong user's data rate, by optimally designing the robust transmit beamforming and PS ratio, while guaranteeing the correct decoding of the weak user. With two different channel uncertainty models respectively incorporated, the proposed formulations yield to challenging nonconvex optimization problems. For the outage-based constrained optimization, we first conservatively approximate the probabilistic constraints with the Bernstein-type inequalities, which are then globally solved by two-dimensional exhaustive search. To further reduce the complexity, an efficient low-complexity algorithm is then proposed with the aid of successive convex approximation (SCA). For the worst-case based scenario, we firstly apply semidefinite relaxation (SDR) method to relax the quadratic terms and prove the rank-one optimality. Then the nonconvex max-min optimization problem is readily transformed into convex approximations based on S-procedure and SCA. Simulation results show that for both channel uncertainty models, the proposed algorithms can converge within a few iterations, and the proposed SWIPT-enabled robust cooperative NOMA system achieves better system performance than existing protocols. Index Terms-Non-orthogonal multiple access, simultaneous wireless information and power transfer (SWIPT), outage-based constrained optimization, worst-case based optimization.

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Germline mutation in EXPH5 implicates the Rab27B effector protein Slac2-b in inherited skin fragility. Am J Hum Genet 2012;91:1115e21.