Distribution of pediatric keratoconus by different age and gender groups

PurposeTo evaluate the distribution of pediatric keratoconus patients and the disease severity based on different age and gender groups in China.Materials and methodsA total of 446 keratoconus eyes in 266 pediatric patients from January 2019 to January 2022 were included in the cross-sectional study. The clinical findings and severity of keratoconus were recorded and Kruskal–Wallis test, chi-squared test, and Cochran-Mantel-Haenszel (CMH) test were used to compare the parameters between different gender and age groups.ResultsThe male/female ratio was 353/93 (3.8:1), and the median age was 16 years (range: 6–17 years). Male patients were statistically younger than female patients (P = 0.041). The male/female ratio decreased with age (P for trend = 0.011). The distribution of the topographic keratoconus classification (TKC) stage was significantly different between gender and age groups (all P < 0.05). Male patients had a higher ratio of advanced keratoconus eyes (TKC ≥ 3) than female patients (P < 0.001), and CMH analysis indicated that being a male was a risk factor for advanced keratoconus after controlling for age (odds ratio: 2.581, P < 0.001).ConclusionMale keratoconus patients were younger, with a higher ratio of advanced keratoconus than female patients in the Chinese pediatric patients evaluated. Multicenter studies with larger sample sizes are necessary in the future

Low Concentrations of Silver Nanoparticles in Biosolids Cause Adverse Ecosystem Responses under Realistic Field Scenario

A large fraction of engineered nanomaterials in consumer and commercial products will reach natural ecosystems. To date, research on the biological impacts of environmental nanomaterial exposures has largely focused on high-concentration exposures in mechanistic lab studies with single strains of model organisms. These results are difficult to extrapolate to ecosystems, where exposures will likely be at low-concentrations and which are inhabited by a diversity of organisms. Here we show adverse responses of plants and microorganisms in a replicated long-term terrestrial mesocosm field experiment following a single low dose of silver nanoparticles (0.14 mg Ag kg−1 soil) applied via a likely route of exposure, sewage biosolid application. While total aboveground plant biomass did not differ between treatments receiving biosolids, one plant species, Microstegium vimeneum, had 32 % less biomass in the Slurry+AgNP treatment relative to the Slurry only treatment. Microorganisms were also affected by AgNP treatment, which gave a significantly different community composition of bacteria in the Slurry+AgNPs as opposed to the Slurry treatment one day after addition as analyzed by T-RFLP analysis of 16S-rRNA genes. After eight days, N2O flux was 4.5 fold higher in the Slurry+AgNPs treatment than the Slurry treatment. After fifty days, community composition and N2O flux of the Slurry+AgNPs treatment converged with the Slurry. However, the soil microbial extracellular enzymes leucine amino peptidase and phosphatase had 52 and 27% lower activities, respectively, while microbial biomass was 35% lower than the Slurry. We also show that the magnitude of these responses was in all cases as large as or larger than the positive control, AgNO3, added at 4-fold the Ag concentration of the silver nanoparticles

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

On Numerical Solution of the Maximum Volume Ellipsoid Problem

In this paper we study practical solution methods for finding the maximum-volume ellipsoid inscribing a given full-dimensional polytope in ! n defined by a finite set of linear inequalities. Our goal is to design a general-purpose algorithmic framework that is reliable and efficient in practice. To evaluate the merit of a practical algorithm, we consider two key factors: the computational cost per iteration and the typical number of iterations required for convergence. In addition, numerical stability is also an important factor. We investigate some new formulations upon which we build primal-dual type, interior-point algorithms, and we provide theoretical justifications for the proposed formulations and algorithmic framework. Extensive numerical experiments have shown that one of the new algorithms should be the method of choice among the tested algorithms

Computational Experience with Lenstra's Algorithm

Integer programming is an important mathematical approach for many decision-making problems. In this field, a major theoretical breakthrough came in 1983 when H. W. Lenstra, Jr. proposed a polynomial-time algorithm for a general integer programming feasibility problem where the number of variables is fixed. Two key ingredients of Lenstra's algorithm are ellipsoidal approximation of polytopes andlattice basis reduction. However, the lack of practically efficient algorithms and software for the ellipsoidal approximation of polytopes had made it difficult to study the computational properties of Lenstra's algorithm. In this paper, using a newly developed ellipsoidal approximation algorithm as a subroutine, we have implemented a version of Lenstra's algorithm for the general integer programming feasibility problem. Our numerical results on small- to medium-sized test instances indicate that Lenstra's algorithm often examines far fewer nodes than the traditional branch-and-bound approach. Currently, the main bottle-neck in the performance of the algorithm lies in the step of lattice basis reduction