Extensive lesions and a positive cone margin are strong predictors of residual disease in subsequent hysterectomy following conization for squamous intraepithelial lesion grade 2 or 3 study design.

BACKGROUND: This study aimed to determine the predictive factors for post-conization of residual disease in subsequent hysterectomy for cervical intraepithelial neoplasia grade 2 or 3. METHODS: This retrospective study included 267 patients with histologically confirmed cervical intraepithelial neoplasia grade 2 or 3 who underwent hysterectomy within 7 months after conization. Clinical data (e.g., age, menopausal status, gravidity, parity, type of transformation zone, conization method) as well as pathological data pertaining to conization and hysterectomy were collected from medical records. A logistic regression model was used to analyze the relationship between the variables and risk of residual lesions in hysterectomy samples. RESULTS: Overall, 70 (26.2%) patients had residual lesions in their hysterectomy specimens. Univariate analyses revealed that age ≥ 50 years (p=0.019), endocervical gland involvement(p=0.013), positive margin(p < 0.001), and involvement of 3-4 quadrants(p < 0.001) were risk factors for residual lesions. Conversely, postmenopausal status, gravidity ≥ 3, parity ≥ 2, loop electrosurgical excision procedure, and type III transformation zone were not risk factors for residual lesions. A positive margin(p < 0.001) and multiple-quadrant involvement(p < 0.001) were identified as independent risk factors for residual lesions on multivariate analysis. CONCLUSIONS: Multiple-quadrant involvement and a positive cone margin were reliable predictive factors for residual disease. Total hysterectomy or repeated cervical conization should be considered for patients with these two risk factors. The identification of high-risk patients with extensive lesions by colposcopic examination before conization is indispensable, as it will enable surgeons to perform conization with consideration of risk factors and possibly improve the approach used for the excisional procedure. For high-risk patients, colposcope-guided cold-knife conization is preferred when resources permit.

C-DONN: compact diffractive optical neural network with deep learning regression.

A new method to improve the integration level of an on-chip diffractive optical neural network (DONN) is proposed based on a standard silicon-on-insulator (SOI) platform. The metaline, which represents a hidden layer in the integrated on-chip DONN, is composed of subwavelength silica slots, providing a large computation capacity. However, the physical propagation process of light in the subwavelength metalinses generally requires an approximate characterization using slot groups and extra length between adjacent layers, which limits further improvements of the integration of on-chip DONN. In this work, a deep mapping regression model (DMRM) is proposed to characterize the process of light propagation in the metalines. This method improves the integration level of on-chip DONN to over 60,000 and elimnates the need for approximate conditions. Based on this theory, a compact-DONN (C-DONN) is exploited and benchmarked on the Iris plants dataset to verify the performance, yielding a testing accuracy of 93.3%. This method provides a potential solution for future large-scale on-chip integration.

Efficient removal of naphthalene-2-ol from aqueous solutions by solvent extraction.

Naphthalene-2-ol is a typical biologically recalcitrant pollutant in dye wastewater. Solvent extraction of naphthalene-2-ol from aqueous solutions using mixed solvents was investigated. Various extractants and diluents were evaluated, and the effects of volume ratio of extractant to diluent, initial pH, initial concentration of naphthalene-2-ol in aqueous solution, extraction time, temperature, volume ratio of organic phase to aqueous phase (O/A), stirring rate and extraction stages, on extraction efficiency were examined separately. Regeneration and reuse of the spent extractant were also investigated. Results showed that tributyl phosphate (TBP) achieved 98% extraction efficiency for naphthalene-2-ol in a single stage extraction, the highest among the 12 extractants evaluated. Extraction efficiency was optimized when cyclohexane and n-octane were used as diluents. The solvent combination of 20% TBP, 20% n-octanol and 60% cyclohexane (V/V) obtained the maximum extraction efficiency for naphthalene-2-ol, 99.3%, within 20min using three cross-current extraction stages under the following extraction conditions: O/A ratio of 1:1, initial pH of 3, 25°C and stirring rate of 150r/min. Recovery of mixed solvents was achieved by using 15% (W/W) NaOH solution at an O:A ratio of 1:1 and a contact time of 15min. The mixed solvents achieved an extraction capacity for naphthalene-2-ol stably higher than 90% during five cycles after regeneration.