BackgroundAlthough laparoscopic surgery has been available for a long time and laparoscopic cholecystectomy has been performed universally, it is still not clear whether open appendectomy (OA) or laparoscopic appendectomy (LA) is the most appropriate surgical approach to acute appendicitis. The purpose of this work is to compare the therapeutic effects and safety of laparoscopic and conventional "open" appendectomy by means of a meta-analysis.MethodsA meta-analysis was performed of all randomized controlled trials published in English that compared LA and OA in adults and children between 1990 and 2009. Calculations were made of the effect sizes of: operating time, postoperative length of hospital stay, postoperative pain, return to normal activity, resumption of diet, complications rates, and conversion to open surgery. The effect sizes were then pooled by a fixed or random-effects model.ResultsForty-four randomized controlled trials with 5292 patients were included in the meta-analysis. Operating time was 12.35 min longer for LA (95% CI: 7.99 to 16.72, p < 0.00001). Hospital stay after LA was 0.60 days shorter (95% CI: -0.85 to -0.36, p < 0.00001). Patients returned to their normal activity 4.52 days earlier after LA (95% CI: -5.95 to -3.10, p < 0.00001), and resumed their diet 0.34 days earlier(95% CI: -0.46 to -0.21, p < 0.00001). Pain after LA on the first postoperative day was significantly less (p = 0.008). The overall conversion rate from LA to OA was 9.51%. With regard to the rate of complications, wound infection after LA was definitely reduced (OR = 0.45, 95% CI: 0.34 to 0.59, p < 0.00001), while postoperative ileus was not significantly reduced(OR = 0.91, 95% CI: 0.57 to 1.47, p = 0.71). However, intra-abdominal abscess (IAA), intraoperative bleeding and urinary tract infection (UIT) after LA, occurred slightly more frequently(OR = 1.56, 95% CI: 1.01 to 2.43, p = 0.05; OR = 1.56, 95% CI: 0.54 to 4.48, p = 0.41; OR = 1.76, 95% CI: 0.58 to 5.29, p = 0.32).ConclusionLA provides considerable benefits over OA, including a shorter length of hospital stay, less postoperative pain, earlier postoperative recovery, and a lower complication rate. Furthermore, over the study period it was obvious that there had been a trend toward fewer differences in operating time for the two procedures. Although LA was associated with a slight increase in the incidence of IAA, intraoperative bleeding and UIT, it is a safe procedure. It may be that the widespread use of LA is due to its better therapeutic effect.

Soil moisture content (SMC) is an important factor that affects agricultural development in arid regions. Compared with the space-borne remote sensing system, the unmanned aerial vehicle (UAV) has been widely used because of its stronger controllability and higher resolution. It also provides a more convenient method for monitoring SMC than normal measurement methods that includes field sampling and oven-drying techniques. However, research based on UAV hyperspectral data has not yet formed a standard procedure in arid regions. Therefore, a universal processing scheme is required. We hypothesized that combining pretreatments of UAV hyperspectral imagery under optimal indices and a set of field observations within a machine learning framework will yield a highly accurate estimate of SMC. Optimal 2D spectral indices act as indispensable variables and allow us to characterize a model’s SMC performance and spatial distribution. For this purpose, we used hyperspectral imagery and a total of 70 topsoil samples (0–10 cm) from the farmland (2.5 × 104 m2) of Fukang City, Xinjiang Uygur AutonomousRegion, China. The random forest (RF) method and extreme learning machine (ELM) were used to estimate the SMC using six methods of pretreatments combined with four optimal spectral indices. The validation accuracy of the estimated method clearly increased compared with that of linear models. The combination of pretreatments and indices by our assessment effectively eliminated the interference and the noises. Comparing two machine learning algorithms showed that the RF models were superior to the ELM models, and the best model was PIR (R2val = 0.907, RMSEP = 1.477, and RPD = 3.396). The SMC map predicted via the best scheme was highly similar to the SMC map measured. We conclude that combining preprocessed spectral indices and machine learning algorithms allows estimation of SMC with high accuracy (R2val = 0.907) via UAV hyperspectral imagery on a regional scale. Ultimately, our program might improve management and conservation strategies for agroecosystem systems in arid regions.

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Despite decades of intense global effort, no disease-modifying drugs for Alzheimer’s disease have emerged. Molecules targeting catalytic activities of γ-secretase or β-site APP-cleaving enzyme 1 (BACE1) have been beset by undesired side effects. We hypothesized that blocking the interaction between BACE1 and γ-secretase subunit presenilin-1 (PS1) might offer an alternative strategy to selectively suppress Aβ generation. Through high-throughput screening, we discovered that 3-α-akebonoic acid (3AA) interferes with PS1/BACE1 interaction and reduces Aβ production. Structural analogs of 3AA were systematically synthesized and the functional analog XYT472B was identified. Photo-activated crosslinking and biochemical competition assays showed that 3AA and XYT472B bind to PS1, interfere with PS1/BACE1 interaction, and reduce Aβ production, whereas sparing secretase activities. Furthermore, treatment of APP/PS1 mice with XYT472B alleviated cognitive dysfunction and Aβ-related pathology. Together, our results indicate that chemical interference of PS1/BACE1 interaction is a promising strategy for Alzheimer’s disease therapeutics.