Comparison of an artificial neural network and Gompertz model for predicting the dynamics of deaths from COVID-19 in México.

The present work is focused on modeling and predicting the cumulative number of deaths from COVID-19 in México by comparing an artificial neural network (ANN) with a Gompertz model applying multiple optimization algorithms for the estimation of coefficients and parameters, respectively. For the modeling process, the data published by the daily technical report COVID-19 in Mexico from March 19th to September 30th were used. The data published in the month of October were included to carry out the prediction. The results show a satisfactory comparison between the real data and those obtained by both models with a R2 > 0.999. The Levenberg-Marquardt and BFGS quasi-Newton optimization algorithm were favorable for fitting the coefficients during learning in the ANN model due to their fast and precision, respectively. On the other hand, the Nelder-Mead simplex algorithm fitted the parameters of the Gompertz model faster by minimizing the sum of squares. Therefore, the ANN model better fits the real data using ten coefficients. However, the Gompertz model using three parameters converges in less computational time. In the prediction, the inverse ANN model was solved by a genetic algorithm obtaining the best precision with a maximum error of 2.22% per day, as opposed to the 5.48% of the Gompertz model with respect to the real data reported from November 1st to 15th. Finally, according to the coefficients and parameters obtained from both models with recent data, a total of 109,724 cumulative deaths for the inverse ANN model and 100,482 cumulative deaths for the Gompertz model were predicted for the end of 2020.

Cyto-injury factors in urine: a possible mechanism for the development of interstitial cystitis.

PURPOSE: In most of our patients with interstitial cystitis (IC), the disease is associated with an increased urothelial permeability whose cause has not been identified. We postulate that both normal urine and the urine of IC patients contains factors capable of injuring the mucosa and causing an increased permeability that would allow urine components to leak into the bladder muscle. To test this hypothesis, we examined fractions of normal urine for toxic effects on bladder smooth muscle and epithelial cells in vitro. In the same in vitro system, we measured the effects of Tamm-Horsfall protein (THP), a normal urinary glycoprotein that may be a scavenger of injurious agents capable of "detoxifying" normal metabolic products. MATERIALS AND METHODS: Human urothelial cells (T24) and rabbit bladder smooth muscle cells were incubated overnight with various fractions prepared from healthy volunteers' urine. The urine fractions of molecular weights >100 Da were incubated overnight with either urothelial or smooth muscle target cells after no treatment or after heating to 56C, preincubation with THP, exposure to heparin, or elution from heparin. Cytotoxicity was determined for each group using a neutral red uptake assay. RESULTS: Urine fractions of molecular weight 500 to 1000 Da were cytotoxic to smooth muscle cells (39%) and urothelial cells (50%). Cytotoxicity levels for THP-treated fractions were significantly lower than those for untreated fractions in both urothelial cells (7% versus 89%, p <0. 001) and smooth muscle cells (8% versus 70%, p <0.01). Fractions exposed to heparin were less cytotoxic to smooth muscle cells (20%) than were untreated fractions (27%). Fractions eluted from heparin were also cytotoxic to urothelial cells (42%). CONCLUSIONS: Normal human urine contains heat labile, cationic components of low molecular weight that bind to heparin. These components, when separated from the bulk of the urinary wastes, are cytotoxic to urothelial cells as well as underlying smooth muscle cells, indicating their potential for causing bladder mucosal injury. The cytotoxic activity can be blocked by the presence of THP. This urinary cytoprotective activity of THP may play an important but unrecognized role in the development of IC.

Miller-Dieker syndrome with microdeletion of chromosome 17p13.3: report of one case.

Miller-Dieker syndrome (MDS) consists of lissencephaly, characteristic craniofacial appearance and sometimes other birth defects. Since 1983, it has been shown that most cases of MDS are caused by deletion of chromosome 17p13.3. Herein, we present a case of MDS in which the patient had characteristic craniofacial appearance in addition to lissencephaly. Although routine chromosome study showed a normal karyotype, deletion of chromosome 17p13.3 was suggested by high resolution GTG-banding and confirmed by FISH. About 36% of the cases reported by Dobyns had submicroscopic deletions of chromosome 17p13.3 in spite of normal karyotypes in routine chromosome studies. The high frequency of submicroscopic deletion in Dobyn's cases and our present case strongly suggests that chromosomal studies, including high-resolution banding and molecular genetic approaches such as FISH, are mandatory whenever MDS is suspected in cases of lissencephaly with normal karyotypes in routine chromosomal work-up.