Transcriptomic Mapping of Human Parotid Gland at Single-Cell Resolution

As the largest salivary gland in oral cavity, the parotid gland plays an important role in initial digesting and lubricating food. The abnormal secretory function of the parotid gland can lead to dental caries and oral mucosal inflammation. In recent years, single-cell RNA sequencing (scRNA-seq) has been used to explore the heterogeneity and diversity of cells in various organs and tissues. However, the transcription profile of the human parotid gland at single-cell resolution has not been reported yet. In this study, we constructed the cell atlas of human parotid gland using the 10× Genomics platform. Characteristic gene analysis identified the biological functions of serous acinar cell populations in secreting digestive enzymes and antibacterial proteins. We revealed the specificity and similarity of the parotid gland compared to other digestive glands through comparative analyses of other published scRNA-seq data sets. We also identified the cell-specific expression of hub genes for Sjögren syndrome in the human parotid gland by integrating the results of genome-wide association studies and bulk RNA-seq, which highlighted the importance of immune cell dysfunction in parotid Sjögren syndrome pathogenesis.

[Current status and research advances on the use of assisted traction technique in endoscopic full-thickness resection]

Endoscopic full-thickness resection (EFTR) allows completely resecting deep submucosal tumors (SMTs) in the gastrointestinal wall, which has a broad application prospect in clinic. However, its application and promotion are limited by complex surgical procedures and high surgical risk. Various auxiliary traction techniques are expected to reduce the operation difficulty and risk of EFTR and improve its operative success rate. To provide a reference for clinicians, we summarize various auxiliary traction techniques in EFTR in this article. The clip-with-line method is simple to operate and widely used, whereas its traction is limited and there is a risk of clip falling off. The snare traction method and the clip-snare traction method has advantage of large traction force, but its thrust is affected by the hardness of snare. The traction point of the grasping forceps traction method is flexible and easy to adjust. Nevertheless, it requires the use of a dual-channel upper endoscope, which is difficult to operate. The transparent cap traction method and the full-thickness resection device traction method takes a short time and is easy to promote, whereas the resectable lesion is limited, and the size of the lesion may affect the success rate. In contrast, the suture loop needle-T-tag tissue anchors assisted method has a large resection range, but the operation is complicated and the feasibility has not been verified. The robot-assisted method has flexible operation and excellent visualization, whereas it is expensive and difficult to operate. There is no report of the application of magnetic anchor technology in EFTR, but it may have good application prospects in the auxiliary traction of EFTR.

Deep learning for automatic calcium scoring in population based cardiovascular screening

Background

High volumes of standardized coronary artery calcium (CAC) scans are generated in screening that need to be scored accurately and efficiently to risk stratify individuals.

Purpose

To evaluate the performance of deep learning based software for automatic coronary calcium scoring in a screening setting.

Methods

Participants from the Robinsca trial that underwent low-dose ECG-triggered cardiac CT for calcium scoring were included. CAC was measured with fully automated deep learning prototype and compared to the original manual assessment of the Robinsca trial. Detection rate, positive Agatston score and risk categorization (0–99, 100–399, ≥400) were compared using McNemar test, ICC, and Cohen's kappa. False negative (FN), false positive (FP) rate and diagnostic accuracy were determined for preventive treatment initiation (cut-off ≥100 AU).

Results

In total, 997 participants were included between December 2015 and June 2016. Median age was 61.0 y (IQR: 11.0) and 54.4% was male. A high agreement for detection was found between deep learning based and manual scoring, κ=0.87 (95% CI 0.85–0.89). Median Agatston score was 58.4 (IQR: 12.3–200.2) and 61.2 (IQR: 13.9–212.9) for deep learning based and manual assessment respectively, ICC was 0.958 (95% CI 0.951–0.964). Reclassification rate was 2.0%, with a very high agreement with κ=0.960 (95% CI: 0.943–0.997), p<0.001. FN rate was 0.7% and FP rate was 0.1% and diagnostic accuracy was 99.2% for initiation of preventive treatment.

Conclusion

Deep learning based software for automatic CAC scoring can be used in a cardiovascular CT screening setting with high accuracy for risk categorization and initiation of preventive treatment.

Funding Acknowledgement

Type of funding sources: Public grant(s) – EU funding. Main funding source(s): Robinsca trial was supported by advanced grant of European Research Council

Deep Learning in Biomedical Optics

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Unusually thick shear-softening surface of micrometer-size metallic glasses

The surface of glass is crucial for understanding many fundamental processes in glassy solids. A common notion is that a glass surface is a thin layer with liquid-like atomic dynamics and a thickness of a few tens of nanometers. Here, we measured the shear modulus at the surface of both millimeter-size and micrometer-size metallic glasses (MGs) through high-sensitivity torsion techniques. We found a pronounced shear-modulus softening at the surface of MGs. Compared with the bulk, the maximum decrease in the surface shear modulus (G) for the micro-scale MGs reaches ~27%, which is close to the decrease in the G upon glass transition, yet it still behaves solid-like. Strikingly, the surface thickness estimated from the shear-modulus softening is at least 400 nm, which is approximately one order of magnitude larger than that revealed from the glass dynamics. The unusually thick surface is also confirmed by measurements using X-ray nano-computed tomography, and this may account for the brittle-to-ductile transition of the MGs with size reductions. The unique and unusual properties at the surface of the micrometer-size MGs are physically related to the negative pressure effect during the thermoplastic formation process, which can dramatically reduce the density of the proximate surface region in the supercooled liquid state.

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The shear modulus and thickness of metallic glass (MG) surface is determined through torsion testing on micrometer-size wires

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The surface region of MG wires has a significant shear-modulus softening close to the supercooled liquid, yet still behaves solid-like

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The thickness of the soft surface of MG wires is at least 400 nm, which is about one order of magnitude larger than those revealed from surface dynamics

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The unusually thick surface accounts for the brittle-to-ductile transition of the MGs with size reduction

[Correlation between compassion fatigue and workplace violence in emergency department nurses]

Objective: To investigate the workplace violence and compassion fatigue of nurses in emergency department and to explore the relationship between the two. Methods: The general information questionnaire, workplace violence scale and professional quality of life scale were used to investigate 957 emergency department nurses of 28 Level II hospitals and above. Results: The scores of each dimension of the professional quality of life scale for nurses in the emergency department were: compassion satisfaction score was 29.91±7.82, the burnout score was 26.63±5.66, and the second trauma score was 23.17±5.94. The total score of compassion fatigue is 49.80±10.42. The incidence of workplace violence was 77.6%. Workplace violence was negatively correlated with compassion satisfaction (r=-0.250, P<0.01) , and positively correlated with burnout, secondary trauma, and total compassion fatigue (r=0.349、0.340、0.384, P<0.01) . Whether there is only non-physical violence in the compassion satisfaction, burnout, secondary trauma, compassion fatigue total score is not statistically significant. Conclusion: Compassion fatigue is more serious in emergency department nurses, and the incidence of workplace violence is higher. Workplace violence has a positive effect on compassion fatigue. Nursing managers should actively prevent workplace violence and improve the working environment, thus reducing empathy fatigue.

Effect of miR-101 on proliferation and oxidative stress-induced apoptosis of breast cancer cells via Nrf2 signaling pathway

OBJECTIVE

To explore the influence of micro ribonucleic acid (miR)-101 on breast cancer cell proliferation and apoptosis via nuclear factor (erythroid-derived 2)-like 2 (Nrf2) signaling pathway.

MATERIALS AND METHODS

All MCF-7 cells were divided into 3 groups, namely control group, miR-101 mimic group (the cells were treated with 50 nmol/L miR-101 mimic), and miR-101 inhibitor group (the cells were treated with 50 nmol/L miR-101 inhibitor). The impact of miR-101 expression level on MCF-7 cell proliferation was evaluated via cell counting kit-8 (CCK-8) and colony formation assays. After the MCF-7 cells in the three groups were treated with 100 nM H2O2 for 12 h, the change in the apoptosis rate was detected via flow cytometry. Moreover, the influence of miR-101 expression level on the Nrf2 signaling pathway was detected via reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting.

RESULTS

According to the CCK-8 assay results, compared with that in control group, the proliferation rate of cells notably declined at 48, 72, and 96 h in miR-101 mimic group, and the difference was statistically significant (p<0.01), while it was substantially raised in miR-101 inhibitor group, showing a statistically significant difference (p<0.01). Compared that in control group, the cell colony formation rate was remarkably lowered in miR-101 mimic group, and the difference was statistically significant (p<0.01), while it was substantially raised in miR-101 inhibitor group (p<0.01). According to the flow cytometry assay results, compared with that in control group, the apoptosis of MCF-7 cells was markedly enhanced in miR-101 mimic group, showing a statistically significant difference (p<0.01), while it was weakened in miR-101 inhibitor group, with a statistically significant difference (p<0.01). The influence of miR-101 on the expression level of Nrf2 was detected via RT-PCR, and it was found that the messenger RNA (mRNA) expression level of Nrf2 was notably lower in miR-101 mimic group than that in control group (p<0.01), while it was raised in miR-101 inhibitor group. Western blotting results showed that compared with control group, miR-101 mimic group had a substantially lowered protein expression level of Nrf2 in the cell nucleus, with a statistically significant difference (p<0.01), while it was notably raised in miR-101 inhibitor group and the difference was statistically significant (p<0.01), indicating that miR-101 can remarkably lower the nucleoprotein expression level of Nrf2.

CONCLUSIONS

The results of this study imply that miR-101 can inhibit the expression of Nrf2 to suppress the proliferation of breast cancer cells and enhance their sensitivity to oxidative stress, which provides a theoretical basis for reversal of tumor resistance.