Reconsider photoplethysmogram signal quality assessment in the free living environment.

Objective.Assessing signal quality is crucial for biomedical signal processing, yet a precise mathematical model for defining signal quality is often lacking, posing challenges for experts in labeling signal qualities. The situation is even worse in the free living environment.Approach.We propose to model a PPG signal by the adaptive non-harmonic model (ANHM) and apply a decomposition algorithm to explore its structure, based on which we advocate a reconsideration of the concept of signal quality.Main results.We demonstrate the necessity of this reconsideration and highlight the relationship between signal quality and signal decomposition with examples recorded from the free living environment. We also demonstrate that relying on mean and instantaneous heart rates derived from PPG signals labeled as high quality by experts without proper reconsideration might be problematic.Significance.A new method, distinct from visually inspecting the raw PPG signal to assess its quality, is needed. Our proposed ANHM model, combined with advanced signal processing tools, shows potential for establishing a systematic signal decomposition based signal quality assessment model.

Two variants on T2DM susceptible gene HHEX are associated with CRC risk in a Chinese population.

Increasing amounts of evidence has demonstrated that T2DM (Type 2 Diabetes Mellitus) patients have increased susceptibility to CRC (colorectal cancer). As HHEX is a recognized susceptibility gene in T2DM, this work was focused on two SNPs in HHEX, rs1111875 and rs7923837, to study their association with CRC. T2DM patients without CRC (T2DM-only, n=300), T2DM with CRC (T2DM/CRC, n=135), cancer-free controls (Control, n=570), and CRC without T2DM (CRC-only, n=642) cases were enrolled. DNA samples were extracted from the peripheral blood leukocytes of the patients and sequenced by direct sequencing. The χ2 test was used to compare categorical data. We found that in T2DM patients, rs1111875 but not the rs7923837 in HHEX gene was associated with the occurrence of CRC (p= 0.006). for rs1111875, TC/CC patients had an increased risk of CRC (p=0.019, OR=1.592, 95%CI=1.046-2.423). Moreover, our results also indicated that the two variants of HEEX gene could be risk factors for CRC in general population, independent on T2DM (p< 0.001 for rs1111875, p=0.001 for rs7923837). For rs1111875, increased risk of CRC was observed in TC or TC/CC than CC individuals (p<0.001, OR= 1.780, 95%CI= 1.385-2.287; p<0.001, OR= 1.695, 95%CI= 1.335-2.152). For rs7923837, increased CRC risk was observed in AG, GG, and AG/GG than AA individuals (p< 0.001, OR= 1.520, 95%CI= 1.200-1.924; p=0.036, OR= 1.739, 95%CI= 0.989-3.058; p< 0.001, OR= 1.540, 95%CI= 1.225-1.936). This finding highlights the potentially functional alteration with HHEX rs1111875 and rs7923837 polymorphisms may increase CRC susceptibility. Risk effects and the functional impact of these polymorphisms need further validation.

Quantitative differentiation of dendritic cells in lung tissues of smokers with and without chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is thought to be an inflammatory immune response disease. In most cases, the disease is caused by cigarette smoke, but it has been demonstrated that only 10% to 20% of smokers will definitely suffer from COPD. Dendritic cells (DCs) are considered to be the promoter of immune responses. However, the underlying mechanisms involved are still unrevealed. In this study, we aimed to investigate the quantitative differentiation of pulmonary DC in smokers with or without COPD to explore the possible role of DCs in smokers suffering COPD. METHODS: Peripheral lung specimens from non-smokers without airflow obstruction (control group, n = 7), smokers without airflow obstruction (smoker group, n = 7) and patients with COPD (COPD group, n = 7) were investigated to detect the quantity of S-100 and CD1a positive cells by immunohistochemical or immunofluorescent assay. RESULTS: In smokers with COPD, the number of S-100(+) DCs was higher than in the controls and smokers without COPD (P < 0.01 and P < 0.05) and there was a higher number of S-100(+) DCs in smokers with COPD than in smokers without COPD, but without a significant difference (P > 0.05). An inverse correlation was found between the number of DCs and forced expiratory volume in the first second (FEV(1))% pred (r = -0.75, P < 0.05), which was also found between the number of DCs and FEV(1)/forced vital capacity (FVC) (r = -0.72, P < 0.05). The mean number of CD1a(+) DCs, increased from non-smokers to non-COPD smokers to COPD patients, with significant differences between each group (P < 0.01). CONCLUSIONS: The quantity of DCs significantly increased in smokers with COPD compared with non-smokers or smokers without COPD. The results suggest that DCs may play an important role in the pathogenesis of smoking-induced COPD, and the upregulation of DCs may be a potential maker to identify the smokers who have more liability to suffer from COPD.