Developing a predictive nomogram and web-based survival calculator for locally advanced hypopharyngeal cancer: A propensity score-adjusted, population-based study

Understanding the clinical features and accurately predicting the prognosis of patients with locally advanced hypopharyngeal squamous cell carcinoma (LA-HPSCC) is important for patient centered decision-making. This study aimed to create a multi-factor nomogram predictive model and a web-based calculator to predict post-therapy survival for patients with LA-HPSCC. A retrospective cohort study analyzing Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 for patients diagnosed with LA-HPSCC was conducted and randomly divided into a training and a validation group (7:3 ratio). The external validation cohort included 276 patients from Sichuan Cancer Hospital, China. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression analysis was used to identify independent factors associated with overall survival (OS) and cancer-specific survival (CSS), and nomogram models and web-based survival calculators were constructed. Propensity score matching (PSM) was used to compare survival with different treatment options. A total of 2526 patients were included in the prognostic model. The median OS and CSS for the entire cohort were 20 (18.6-21.3) months and 24 (21.7-26.2) months, respectively. Nomogram models integrating the seven factors demonstrated high predictive accuracy for 3-year and 5-year survival. PSM found that patients who received surgery-based curative therapy had better OS and CSS than those who received radiotherapy-based treatment (median survival times: 33 months vs 18 months and 40 months vs 22 months, respectively). The nomogram model accurately predicted patient survival from LA-HPSCC. Surgery with adjuvant therapy yielded significantly better survival than definitive radiotherapy. and should be prioritized over definitive radiotherapy

Sexually transmitted infections and semen quality from subfertile men with and without leukocytospermia

Background: The role of sexually transmitted infections (STIs) in semen parameters and male infertility is still a controversial area. Previous studies have found bacterial infection in a minority of infertile leukocytospermic males. This study aims to investigate the prevalence of STIs in semen from subfertile men with leukocytospermia (LCS) and without leukocytospermia (non-LCS) and their associations with sperm quality. Methods: Semen samples were collected from 195 men who asked for a fertility evaluation. Infection with the above 6 pathogens was assessed in each sample. Sperm quality was compared in subfertile men with and without LCS. Results: The LCS group had significantly decreased semen volume, sperm concentration, progressive motility, total motility and normal morphology. The infection rates of Ureaplasma urealyticum (Uuu), Ureaplasma parvum (Uup), Mycoplasma hominis (MH), Mycoplasma genitalium (MG), Chlamydia trachomatis (CT), herpes simplex virus-2 (HSV-2) and Neisseria gonorrhoeae (NG) were 8.7 %, 21.0 %, 8.2 %, 2.1 %, 3.6 %, 1.0 and 0 %, respectively. The STI detection rates of patients with LCS were higher than those of the non-LCS group (52.3 % vs. 39.3 %), although there was no statistically significant difference between the two groups (P = 0.07). All semen parameters were not significantly different between LCS with STIs and without STIs, except the semen volume in the MG-infected patients with LCS was significantly lower than that in the noninfected group. Conclusions: LCS was associated with a reduction in semen quality, but was not associated with STIs

An Effective Method for Computing the Least-Cost Path Using a Multi-Resolution Raster Cost Surface Model

Calculating the least-cost path (LCP) is a fundamental operation in raster-based geographic information systems (GIS). The LCP is applied to raster cost surfaces, in which it determines the most cost-effective path. Increasing the raster resolution results in a longer computation time to obtain LCP. This paper proposes a method for calculating the LCP using a multi-resolution raster cost surface model to enhance computational performance for large-scale grids. The original raster cost surface is progressively downsampled to generate grids of decreasing resolutions. Subsequently, the path is determined on the low-resolution raster. By performing operations such as filtering directional points and mapping path points, the final path on the high-resolution raster can be obtained. The method enables a parallel computation of paths. Therefore, it significantly improves the efficiency for synthetic raster cost surfaces with continuous or discrete characteristics, as well as for raster cost surfaces generated from real terrain datasets, while also providing an end-to-end path output. The experiments show that 80% of the results are very close to the original LCP, and the accuracy of the remaining paths falls within an acceptable range. At the same time, our method greatly improves the efficiency of path solving on a large-scale raster, fulfilling practical application requirements

Co-catalyzed highly selective C(sp³)–H nitration

A Co-catalyzed highly selective C(sp3)–H nitration via a radical pathway was disclosed, overcoming the strong coordination effect of pyrimidine by suppressing C(sp2)–H functionalization as well as proximity C(sp3)–H functionalization.</p