Application of multiple InSAR techniques and SAR data from multi-sources to landslide deformation monitoring: A case study of the Zhixincun landslide in Jilin Province

In order to realize effective monitoring of Zhixincun landslide, this paper selected 27 sentinel-1A data in 2017, and conducted deformation monitoring of Zhixincun landslide based on small baseline radar interferometry technology (SBAS-InSAR), and analyzed its temporal evolution situation. Using ALOS-2 data from 2016 and 2017, differential radar interferometry (D-InSAR) was used to monitor the characteristics of the landslide variant. SBAS-InSAR monitors the temporal evolution situation of landslide deformation, while D-InSAR mainly monitors the deformation of specific landslide shape and variation. Moreover, the penetration of L-band ALOS-2 data is stronger than that of C-band sentinel-1A data, which can obtain more complete interference information. The monitoring results of both can be cross-verified. Improve the reliability of the results. The SBAS-InSAR monitoring results showed that the slope end of the landslide catchment area in Zhixincun had subsidence during the monitoring period, and the surface subsidence at the landslide end reached 12.47mm from July 5 to July 29, with an average subsidence rate of 2.88mm/a during the monitoring period. Uplift occurred in the threatened residential areas in the valley, with an average cumulative uplift of 19.59mm on December 8 and an average uplift rate of 19.99mm/a during the monitoring period. The D-InSAR results showed that there were five major deformations on the slope of Zhixincun landslide catchment area. The largest deformations with an area of 17 973m2 were located on the west side of the slope, and the most unstable deformations were located on the east side of the slope. The average cumulative shape variable reached 49.9mm during the monitoring period. Both monitoring methods showed that the threat of landslide disaster mainly came from the west slope with poor vegetation cover, and the rainy season was the key period of landslide disaster prevention and control in Zhixincun

DAFNet: A dual attention-guided fuzzy network for cardiac MRI segmentation

Background: In clinical diagnostics, magnetic resonance imaging (MRI) technology plays a crucial role in the recognition of cardiac regions, serving as a pivotal tool to assist physicians in diagnosing cardiac diseases. Despite the notable success of convolutional neural networks (CNNs) in cardiac MRI segmentation, it remains a challenge to use existing CNNs-based methods to deal with fuzzy information in cardiac MRI. Therefore, we proposed a novel network architecture named DAFNet to comprehensively address these challenges. Methods: The proposed method was used to design a fuzzy convolutional module, which could improve the feature extraction performance of the network by utilizing fuzzy information that was easily ignored in medical images while retaining the advantage of attention mechanism. Then, a multi-scale feature refinement structure was designed in the decoder portion to solve the problem that the decoder structure of the existing network had poor results in obtaining the final segmentation mask. This structure further improved the performance of the network by aggregating segmentation results from multi-scale feature maps. Additionally, we introduced the dynamic convolution theory, which could further increase the pixel segmentation accuracy of the network. Result: The effectiveness of DAFNet was extensively validated for three datasets. The results demonstrated that the proposed method achieved DSC metrics of 0.942 and 0.885, and HD metricd of 2.50mm and 3.79mm on the first and second dataset, respectively. The recognition accuracy of left ventricular end-diastolic diameter recognition on the third dataset was 98.42%. Conclusion: Compared with the existing CNNs-based methods, the DAFNet achieved state-of-the-art segmentation performance and verified its effectiveness in clinical diagnosis

Unraveling the pathogenic potential of the Pentatrichomonas hominis PHGD strain: impact on IPEC-J2 cell growth, adhesion, and gene expression

Pentatrichomonas hominis, a flagellated parasitic protozoan, predominantly infects the mammalian digestive tract, often causing symptoms such as abdominal pain and diarrhea. However, studies investigating its pathogenicity are limited, and the mechanisms underlying P. hominis-induced diarrhea remain unclear. Establishing an in vitro cell model for P. hominis infection is imperative. This study investigated the interaction between P. hominis and IPEC-J2 cells and its impact on parasite growth, adhesion, morphology, and cell viability. Co-cultivation of P. hominis with IPEC-J2 cells resulted in exponential growth of the parasite, with peak densities reaching approximately 4.8 × 105 cells/mL and 1.2 × 106 cells/mL at 48 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. The adhesion rate of P. hominis to IPEC-J2 cells reached a maximum of 93.82% and 86.57% at 24 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. Morphological changes in IPEC-J2 cells co-cultivated with P. hominis were observed, manifesting as elongated and irregular shapes. The viability of IPEC-J2 cells exhibited a decreasing trend with increasing P. hominis concentration and co-cultivation time. Additionally, the mRNA expression levels of IL-6, IL-8, and TNF-α were upregulated, whereas those of CAT and CuZn-SOD were downregulated. These findings provide quantitative evidence that P. hominis can promote its growth by adhering to IPEC-J2 cells, inducing morphological changes, reducing cell viability, and triggering inflammatory responses. Further in vivo studies are warranted to confirm these results and enhance our understanding of P. hominis infection

Association of inpatient use of angiotensin converting enzyme inhibitors and angiotensin II receptor blockers with mortality among patients with hypertension hospitalized with COVID-19

Rationale: Use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) is a major concern for clinicians treating coronavirus disease 2019 (COVID-19) in patients with hypertension. Objective: To determine the association between in-hospital use of ACEI/ARB and all-cause mortality in COVID-19 patients with hypertension. Methods and Results: This retrospective, multi-center study included 1128 adult patients with hypertension diagnosed with COVID-19, including 188 taking ACEI/ARB (ACEI/ARB group; median age 64 [IQR 55-68] years; 53.2% men) and 940 without using ACEI/ARB (non-ACEI/ARB group; median age 64 [IQR 57-69]; 53.5% men), who were admitted to nine hospitals in Hubei Province, China from December 31, 2019 to February 20, 2020. Unadjusted mortality rate was lower in the ACEI/ARB group versus the non-ACEI/ARB group (3.7% vs. 9.8%; P = 0.01). In mixed-effect Cox model treating site as a random effect, after adjusting for age, gender, comorbidities, and in-hospital medications, the detected risk for all-cause mortality was lower in the ACEI/ARB group versus the non-ACEI/ARB group (adjusted HR, 0.42; 95% CI, 0.19-0.92; P =0.03). In a propensity score-matched analysis followed by adjusting imbalanced variables in mixed-effect Cox model, the results consistently demonstrated lower risk of COVID-19 mortality in patients who received ACEI/ARB versus those who did not receive ACEI/ARB (adjusted HR, 0.37; 95% CI, 0.15-0.89; P = 0.03). Further subgroup propensity score-matched analysis indicated that, compared to use of other antihypertensive drugs, ACEI/ARB was also associated with decreased mortality (adjusted HR, 0.30; 95%CI, 0.12-0.70; P = 0.01) in COVID-19 patients with hypertension. Conclusions: Among hospitalized COVID-19 patients with hypertension, inpatient use of ACEI/ARB was associated with lower risk of all-cause mortality compared with ACEI/ARB non-users. While study interpretation needs to consider the potential for residual confounders, it is unlikely that in-hospital use of ACEI/ARB was associated with an increased mortality risk

Redefining cardiac biomarkers in predicting mortality and adverse outcomes of inpatients with COVID-19

The prognostic power of circulating cardiac biomarkers, their utility and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multi-centered retrospective study, we enrolled 3,219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effect Cox model, after adjusting for age, gender and comorbidities, the adjusted hazard ratios of 28-day mortality for high-sensitivity cardiac troponin I (hs-cTnI) was 7.12 (95%CI, 4.60-11.03; P<0.001), NT-proB-type natriuretic peptide (NT-proBNP) was 5.11 (95%CI, 3.50-7.47; P<0.001), CK-MB was 4.86 (95%CI, 3.33-7.09; P<0.001), myoglobin was 4.50 (95%CI, 3.18-6.36; P < 0.001), and CK was 3.56 (95%CI, 2.53-5.02; P < 0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 49% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoffs for of these values might be much lower than the current reference standards. These findings can assist better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19 associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials

Redefining Cardiac Biomarkers in Predicting Mortality of Inpatients With COVID-19

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P\u3c0.001), (NT-pro)BNP (N-terminal pro-B-type natriuretic peptide or brain natriuretic peptide) was 5.11 ([95% CI, 3.50-7.47] P\u3c0.001), CK (creatine phosphokinase)-MB was 4.86 ([95% CI, 3.33-7.09] P\u3c0.001), MYO (myoglobin) was 4.50 ([95% CI, 3.18-6.36] P\u3c0.001), and CK was 3.56 ([95% CI, 2.53-5.02] P\u3c0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 19%-50% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoff values of these biomarkers might be much lower than the current reference standards. These findings can assist in better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19-associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials