Predicting the wicking rate of nitrocellulose membranes from recipe data: a case study using ANN at a membrane manufacturing in South Korea.

Lateral flow assays have been widely used for detecting coronavirus disease 2019 (COVID-19). A lateral flow assay consists of a Nitrocellulose (NC) membrane, which must have a specific lateral flow rate for the proteins to react. The wicking rate is conventionally used as a method to assess the lateral flow in membranes. We used multiple regression and artificial neural networks (ANN) to predict the wicking rate of NC membranes based on membrane recipe data. The developed ANN predicted the wicking rate with a mean square error of 0.059, whereas the multiple regression had a square error of 0.503. This research also highlighted the significant impact of the water content on the wicking rate through images obtained from scanning electron microscopy. The findings of this research can cut down the research and development costs of novel NC membranes with a specific wicking rate significantly, as the algorithm can predict the wicking rate based on the membrane recipe.

A method for early diagnosis of lung cancer from tumor originated DNA fragments using plasma cfDNA methylome and fragmentome profiles.

Early detection is critical for minimizing mortality from cancer. Plasma cell-free DNA (cfDNA) contains the signatures of tumor DNA, allowing us to quantify the signature and diagnose early-stage tumors. Here, we report a novel tumor fragment quantification method, TOF (Tumor Originated Fragment) for the diagnosis of lung cancer by quantifying and analyzing both the plasma cfDNA methylation patterns and fragmentomic signatures. TOF utilizes the amount of ctDNA predicted from the methylation density information of each cfDNA read mapped on 6243 lung-tumor-specific CpG markers. The 6243 tumor-specific markers were derived from lung tumor tissues by comparing them with corresponding normal tissues and healthy blood from public methylation data. TOF also utilizes two cfDNA fragmentomic signatures: 1) the short fragment ratio, and 2) the 5' end-motif profile. We used 298 plasma samples to analyze cfDNA signatures using enzymatic methyl-sequencing data from 201 lung cancer patients and 97 healthy controls. The TOF score showed 0.98 of the area under the curve in correctly classifying lung cancer from normal samples. The TOF score resolution was high enough to clearly differentiate even the early-stage non-small cell lung cancer patients from the healthy controls. The same was true for small cell lung cancer patients.

Temporal triggers of N2O emissions during cyclical and seasonal variations of a full-scale sequencing batch reactor treating municipal wastewater.

To investigate the major triggers of nitrous oxide (N2O) production in a full-scale wastewater treatment plant, N2O emissions and wastewater characteristics (ammonia, nitrite, nitrate, total nitrogen, dissolved inorganic carbon, dissolved organic carbon, pH, temperature, dissolved oxygen and specific oxygen uptake rate), the results of variations in the cycling of a sequential batch reactor (SBR, where only full nitrification was performed), were monitored seasonally for 16 months. Major triggers of N2O production were investigated based on a seasonal measured database using a random forest (RF) model and sensitivity analysis, which was applied to identify important input variables. As the result of seasonal monitoring in the full-scale SBR, the N2O emission factor relative to daily total nitrogen removal ranged from 0.05 to 2.68%, corresponding to a range of N2O production rate from 0.02 to 0.70 kg-N/day. Results from the RF model and sensitivity analysis revealed that emissions during nitrification were directly or indirectly related to nitrite accumulation, temperature, ammonia loading rate and the specific oxygen uptake rate ratio between ammonia oxidizing bacteria and nitrite oxidizing bacteria (sOUR-ratio). However, changes in the microbial community did not significantly impact N2O emissions. Based on these results, the sOUR-ratio could represent the major trigger for N2O emission in a full-scale BNR system: a higher sOUR-ratio value with an average of 3.13 ± 0.23 was linked to a higher N2O production rate with an average value of 1.27 ± 0.12 kg-N/day (corresponding to 3.96 ± 1.20% of N2O emission factor relative to daily TN removal), while a lower sOUR-ratio with an average value of 2.39 ± 0.27 was correlated with a lower N2O production average rate of 0.17 ± 0.11 kg-N/day (corresponding to 0.74 ± 0.69% of N2O emission factor) (p-value = 0.00001, Mann-Whitney test).