Nonparametric ridge estimation

We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the data are noisy measurements of a manifold, we show that the ridges are close and topologically similar to the hidden manifold. To find the estimated ridges in practice, we adapt the modified mean-shift algorithm proposed by Ozertem and Erdogmus [J. Mach. Learn. Res. 12 (2011) 1249-1286]. Some numerical experiments verify that the algorithm is accurate.Comment: Published in at http://dx.doi.org/10.1214/14-AOS1218 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

On the path density of a gradient field

We consider the problem of reliably finding filaments in point clouds. Realistic data sets often have numerous filaments of various sizes and shapes. Statistical techniques exist for finding one (or a few) filaments but these methods do not handle noisy data sets with many filaments. Other methods can be found in the astronomy literature but they do not have rigorous statistical guarantees. We propose the following method. Starting at each data point we construct the steepest ascent path along a kernel density estimator. We locate filaments by finding regions where these paths are highly concentrated. Formally, we define the density of these paths and we construct a consistent estimator of this path density.Comment: Published in at http://dx.doi.org/10.1214/08-AOS671 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Manifold estimation and singular deconvolution under Hausdorff loss

We find lower and upper bounds for the risk of estimating a manifold in Hausdorff distance under several models. We also show that there are close connections between manifold estimation and the problem of deconvolving a singular measure.Comment: Published in at http://dx.doi.org/10.1214/12-AOS994 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Italian immunization calendar implementation: Time to optimize number of vaccination appointments?

In the Italian vaccination schedule, at least six vaccination appointments are scheduled in the first year of life. This implies more discomfort for both the patient and the parents. This was particularly evident during the COVID-19 pandemic, during which several appointments were missed. A UK experience with three injectable vaccines and an oral one co-administered at the same appointment (4-in-1) at 2 and 4 months of age showed interesting results. The vaccination coverage was high, consistent with previous practice, and no relevant increase in adverse events was reported. Translating the UK experience into the Italian context would not be immediate, due to several organizational and social issues. Nevertheless, this option warrants some further considerations, which are discussed in this manuscript

Minimax Manifold Estimation

We find the minimax rate of convergence in Hausdorff distance for estimating a manifold M of dimension d embedded in R-D given a noisy sample from the manifold. Under certain conditions, we show that the optimal rate of convergence is n(-2/(2+d)). Thus, the minimax rate depends only on the dimension of the manifold, not on the dimension of the space in which M is embedded

Nonparametric Ridge Estimation

We study the problem of estimating the ridges of a density function. Ridge estimation is an extension of mode finding and is useful for understanding the structure of a density. It can also be used to find hidden structure in point cloud data. We show that, under mild regularity conditions, the ridges of the kernel density estimator consistently estimate the ridges of the true density. When the data are noisy measurements of a manifold, we show that the ridges are close and topologically similar to the hidden manifold. To find the estimated ridges in practice, we adapt the modified mean-shift algorithm proposed by Ozertem and Erdogmus [J. Mach. Learn. Res. 12 (2011) 1249–1286]. Some numerical experiments verify that the algorithm is accurate

COMPUTER-CONTROLLED GAS CHROMATOGRAPH CAPABLE OF ''REAL-TIME'' READOUT OF HIGH-PRECISION DATA.

A gas chromatograph has been assembled which provides computer control of sample injection, column temperature, and flow rate, plus direct computer readout of inlet pressure, mass flow rate, and detector response. Data processing yields, in real-time, a standard deviation of less than 0.05% in retention time, which is comparable to previous results obtained using an off-line computer. However, corrected retention volumes determined in real-time had a standard deviation of about 0.4% which reflected primarily the uncertainty in flow measurement

Hydatid disease of the liver: thirty years of surgical experience.

Hydatid disease of the liver is a relatively frequent disease. Although the natural history is almost completely known, several complications may occur. The aim of this study was to show that radical surgical resection of the hepatic hydatid cyst is a safe and very effective technique, based on our results after 30-year experience. A review of most significant studies was carried out. We retrospectively evaluated our surgical cases. From January 1973 to December 2003 we treated 216 patients, 98 males and 118 females. Survival was compared with the Kaplan-Meier test, using log-rank analysis to compare data. Differences with a p value less than 0.05 were considered significant. A total of 279 cysts were excised. We performed pericystectomy in 122 cases, 73 of which closed. We also performed 19 atypical resections, 10 segmentectomies, 20 lobectomies and 2 percutaneous treatments. In more than 90% of cases, preoperative data collection was completed by preoperative ultrasound. The cumulative morbidity was 13%. The recurrence rate amounted to 4.3% at 5 years and 7% at 10 years: of these, 6 occurred after non-radical surgery and 2 after total pericystectomy or liver resection (p < 0.001). Technical advances and accumulated experience permit safe treatment of hepatic hydatid cysts by radical resection, with an almost zero recurrence rate, making it the treatment of choice over partial resection. The utility of percutaneous treatment remains confined to limited indications, such as laparoscopy

Design and in vitro study of a dual drug-loaded delivery system produced by electrospinning for the treatment of acute injuries of the central nervous system

Vascular and traumatic injuries of the central nervous system are recognized as global health priorities. A polypharmacology approach that is able to simultaneously target several injury factors by the combination of agents having synergistic effects appears to be promising. Herein, we designed a polymeric delivery system loaded with two drugs, ibuprofen (Ibu) and thyroid hormone triiodothyronine (T3) to in vitro release the suitable amount of the anti-inflammation and the remyelination drug. As a production method, electrospinning technology was used. First, Ibuloaded micro (diameter circa 0.95–1.20 µm) and nano (diameter circa 0.70 µm) fibers were produced using poly(L-lactide) PLLA and PLGA with different lactide/glycolide ratios (50:50, 75:25, and 85:15) to select the most suitable polymer and fiber diameter. Based on the in vitro release results and in-house knowledge, PLLA nanofibers (mean diameter = 580 ± 120 nm) loaded with both Ibu and T3 were then successfully produced by a co-axial electrospinning technique. The in vitro release studies demonstrated that the final Ibu/T3 PLLA system extended the release of both drugs for 14 days, providing the target sustained release. Finally, studies in cell cultures (RAW macrophages and neural stem cell-derived oligodendrocyte precursor cells—OPCs) demonstrated the anti-inflammatory and promyelinating efficacy of the dual drug-loaded delivery platform