Polyps

ChIP–chip dataset. A number of assays have been recently developed that use immunopercipitation-based enrichment of cellular DNA for the purpose of identifying binding or other chemical events and the genomic locations at which they occur. Location analysis, also known as ChIP–chip, is a technique that enables the mapping of transcription binding events to genomic locations at which they occur [1 (link),54 ]. The output of the assay is a fluorescence dye ratio at each spot of the array. If spots are taken to represent genomic regions, then we can regard the ratio and p-value associated with each spot as an indication of TF binding in the corresponding genomic region. We applied DRIM to S. cerevisiae genome-wide location data reported in Harbison et al. [25 (link)] and Lee et al. [28 (link)]. The first consists of the genomic occupancy of 203 putative TFs in rich media conditions (YPD). In addition, the genomic occupancy of 84 of these TFs was measured in at least one other condition (OC). In each of the experiments, the genomic sequences were ranked according to the TF binding p-value. Surprisingly, we observed that 69 of the 203 ranked sequence lists of YPD had significantly longer sequences at the top of the list (first 300 sequences) compared with the rest of the list with t-test p-value ≤ 10⁻³. We observed a similar phenomenon in 76 of the 148 ranked sequence lists of OC experiments (see Figure S1). In other words, for some TFs, longer sequences are biased toward stronger binding signals. This observation is unexpected since, although longer probes hybridize more labeled material than shorter probes, the increase should be proportional in both channels. This type of length bias may cause spurious results under our model assumptions and hence the final dataset, termed “Harbison filtered dataset,” refers to the remaining 207 experiments (135 YPD, and 72 OC) of 162 unique TFs that did not have length bias (Table S1).
An additional ChIP–chip dataset was constructed using the data reported in Lee et al. [28 (link)] containing 113 experiments in rich media. The data is partially exclusive to the data of Harbison et al. [25 (link)]. The same filtering procedure was performed, resulting in a set of 65 experiments, termed “Lee filtered dataset.”
Methylated CpG dataset. Using a technique similar to ChIP–chip, termed methyl-DNA immunoprecipitation (mDIP), enables the measurement of methylated CpG island patterns [2 (link),55 (link)]. The third dataset contains the CpG island methylation patterns of four different human cancer cell lines (Caco-2, Polyp, Carcinoma, PC3) where several replicate experiments were done for each of the cell lines. In each of these experiments, the CpG methylation signal was measured in ∼13,000 gene promoters as reported in [2 (link)].

Place, duration, and design of the study
This prospective single-center study was performed in our department between May 2021 and December 2021.
Ethics
Informed consent was obtained for all patients. The examinations were only performed after a careful explanation of the characteristics, non-invasiveness, and aim of the study. The study was approved by the Ethics Committee of Centro Hospitalar Universitário do Porto (Number: 2021.93 [075-DEFI/078-CE]) and the design complies with the Declaration of Helsinki ethical standards.
Inclusion criteria
Adulthood, OD concomitant with SARS-CoV-2 documented infection), subjective persistence of OD, and a cognitive status that allowed the patient to sign an informed consent and to self-treat with the medical therapeutic proposed.
Exclusion criteria
Chronic rhinosinusitis, recent head trauma with loss of consciousness, olfactory complaints before documented COVID-19, gestation, prior nasal surgery, known olfactory bulb lesion on imaging, neurologic or psychiatric disease, or inability to tolerate nasal endoscopy.
Evaluation
Our evaluation consisted of several steps: A general assessment of days before the onset of hyposmia, co-morbidities, a subjective assessment using the Portuguese Language Olfactory Disorders Questionnaire [12 (link)], and a VAS toward subjective impairment of hyposmia in quality of life. Our VAS consisted of an 11-point scale ranging between 0 and 10, being “not a problem” on the left end of the scale (number 0) and “worst problem in my life” on the right end of the scale (number 10). An objective assessment of olfactory thresholds using the Sniffin´ Sticks threshold test with n-butanol: 16 levels in 48 pens were also performed [13 (link)]. The nasal status assessment was performed by nasal endoscopy for exclusion of nasal pathology and evaluation of Lund-Kennedy score - when a polyp score ≥ 1 was seen, the patient was excluded from our cohort while follow-up and further management were maintained in parallel. Also, all patients underwent olfactory training and adjuvant therapy using the strategy described in the protocol described by Sousa et al. [14 (link)].
Variables evaluated
Age, gender, relevant comorbidities, date of perceived onset of OD, olfactory thresholds, and VAS (related to OD). Patients were re-evaluated after three months, and data was collected.
Statistical analysis
Collected data were analyzed using SPSS version 26 (Statistical Package for Social Studies) - IBM, USA. For numerical values, the range, mean, and standard deviations were calculated. The differences between the two mean values were used using the Mann-Whitney U test. Differences in mean values before and after the intervention were done by Wilcoxon signed ranks test. The correlation between VAS and olfactory thresholds was done using Pearson’s correlation coefficient. To access the confounding variables, ANCOVA analysis was also performed. All reported p-values are two-tailed, with a p-value ≤ 0.05 indicating statistical significance.

(1) Benign colorectal diseases: colorectal polyps, familial polyposis, ulcerative colitis, Crohn’s disease. (2) Other diseases of the colorectum: neuroendocrine tumors, lymphoma, intestinal tuberculosis, typhoid fever, intestinal amebiasis, Intestinal schistosomiasis, etc. (3) Serious lack of clinical data: such as age, gender, primary tumor location, SLM information, etc. (4) Combined with other archenteric malignant tumors. (5) Patients who had undergone surgery or radiotherapy and chemotherapy at the time of admission. (6) Patients who had lung metastasis and concomitant metastases of other organs, such as liver metastasis.