Impact of the COVID-19 pandemic on the hospital attendance of patients with primary cervical cancer in Heilongjiang, China.

Information regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on cervical cancer in mainland China is lacking. We explored its impact on the hospital attendance of patients with primary cervical cancer. We included 1918 patients with primary cervical cancer who initially attended Harbin Medical University Cancer Hospital between January 23, 2019, and January 23, 2021. Attendance decreased by 31%, from 1135 in 2019 to 783 in 2020, mainly from January to June (𝜒2 = 73.362, P < .001). The percentage of patients detected by screening decreased from 12.1% in January-June 2019 to 5.8% in January-June 2020 (𝜒2 = 7.187, P = .007). Patients with stage I accounted for 28.4% in 2020 significantly lower than 36.6% in 2019 (𝜒2 = 14.085, P < .001), and patients with stage III accounted for 27.1% in 2020 significantly higher than 20.5% in 2019 (𝜒2 = 11.145, P < .001). Waiting time for treatment was extended from 8 days (median) in January-June and July-December 2019 to 16 days in January-June (𝜒2 = 74.674, P < .001) and 12 days in July-December 2020 (𝜒2 = 37.916, P < .001). Of the 179 patients who delayed treatment, 164 (91.6%) were for the reasons of the healthcare providers. Compared to 2019, the number of patients in Harbin or non-Harbin in Heilongjiang Province and outside the province decreased, and cross-regional medical treatment has been hindered. The COVID-19 pandemic has negatively impacted cervical cancer patient attendance at the initial phase. These results are solid evidence that a strategy and mechanism for the effective attendance of cervical cancer patients in response to public health emergencies is urgently needed.

Stable expression of large transgenes via the knock-in of an integrase-deficient lentivirus.

The targeted insertion and stable expression of a large genetic payload in primary human cells demands methods that are robust, efficient and easy to implement. Large payload insertion via retroviruses is typically semi-random and hindered by transgene silencing. Leveraging homology-directed repair to place payloads under the control of endogenous essential genes can overcome silencing but often results in low knock-in efficiencies and cytotoxicity. Here we report a method for the knock-in and stable expression of a large payload and for the simultaneous knock-in of two genes at two endogenous loci. The method, which we named CLIP (for 'CRISPR for long-fragment integration via pseudovirus'), leverages an integrase-deficient lentivirus encoding a payload flanked by homology arms and 'cut sites' to insert the payload upstream and in-frame of an endogenous essential gene, followed by the delivery of a CRISPR-associated ribonucleoprotein complex via electroporation. We show that CLIP enables the efficient insertion and stable expression of large payloads and of two difficult-to-express viral antigens in primary T cells at low cytotoxicity. CLIP offers a scalable and efficient method for manufacturing engineered primary cells.

Perceived professional benefits and associated factors among nurses during the COVID-19 pandemic: A cross-sectional study.

AIMS: To examine the perceived professional benefits (PPB) and associated factors among nurses during the coronavirus disease 2019 (COVID-19) pandemic in China. DESIGN: Cross-sectional study. METHODS: Using the snowball sampling method, 492 nurses (478 females, 14 males) were recruited. Data were collected using an online survey, including participants' socio-demographic and working characteristics, psychological distress related to the COVID-19 pandemic, dealing with professional frustration, professional self-reflection and PPB from 1-30 April 2020. RESULTS: Nurses experienced high levels of PPB. In linear regression analysis, self-perceived concerns about COVID-19, emotional shock caused by it, risk perception towards their occupations, dealing with professional frustration and professional self-reflection were positively associated with PPB among nurses. These factors explained 84% variance in PPB. CONCLUSIONS: This study highlighted that although the nurses experienced psychological distress, they gained high PPB during the COVID-19 pandemic. Additionally, to facilitate nurses' efforts to achieve professional growth, more educational resources and opportunities for engaging in reflective practices could be provided.

SARS-CoV-2 escapes direct NK cell killing through Nsp1-mediated downregulation of ligands for NKG2D.

Natural killer (NK) cells are cytotoxic effector cells that target and lyse virally infected cells; many viruses therefore encode mechanisms to escape such NK cell killing. Here, we interrogate the ability of SARS-CoV-2 to modulate NK cell recognition and lysis of infected cells. We find that NK cells exhibit poor cytotoxic responses against SARS-CoV-2-infected targets, preferentially killing uninfected bystander cells. We demonstrate that this escape is driven by downregulation of ligands for the activating receptor NKG2D (NKG2D-L). Indeed, early in viral infection, prior to NKG2D-L downregulation, NK cells are able to target and kill infected cells; however, this ability is lost as viral proteins are expressed. Finally, we find that SARS-CoV-2 non-structural protein 1 (Nsp1) mediates downregulation of NKG2D-L and that Nsp1 alone is sufficient to confer resistance to NK cell killing. Collectively, our work demonstrates that SARS-CoV-2 evades direct NK cell cytotoxicity and describes a mechanism by which this occurs.

Crosslink-Net: Double-Branch Encoder Network via Fusing Vertical and Horizontal Convolutions for Medical Image Segmentation.

Accurate image segmentation plays a crucial role in medical image analysis, yet it faces great challenges caused by various shapes, diverse sizes, and blurry boundaries. To address these difficulties, square kernel-based encoder-decoder architectures have been proposed and widely used, but their performance remains unsatisfactory. To further address these challenges, we present a novel double-branch encoder architecture. Our architecture is inspired by two observations. (1) Since the discrimination of the features learned via square convolutional kernels needs to be further improved, we propose utilizing nonsquare vertical and horizontal convolutional kernels in a double-branch encoder so that the features learned by both branches can be expected to complement each other. (2) Considering that spatial attention can help models to better focus on the target region in a large-sized image, we develop an attention loss to further emphasize the segmentation of small-sized targets. With the above two schemes, we develop a novel double-branch encoder-based segmentation framework for medical image segmentation, namely, Crosslink-Net, and validate its effectiveness on five datasets with experiments. The code is released at https://github.com/Qianyu1226/Crosslink-Net.

Broad-spectrum CRISPR-mediated inhibition of SARS-CoV-2 variants and endemic coronaviruses in vitro.

A major challenge in coronavirus vaccination and treatment is to counteract rapid viral evolution and mutations. Here we demonstrate that CRISPR-Cas13d offers a broad-spectrum antiviral (BSA) to inhibit many SARS-CoV-2 variants and diverse human coronavirus strains with >99% reduction of the viral titer. We show that Cas13d-mediated coronavirus inhibition is dependent on the crRNA cellular spatial colocalization with Cas13d and target viral RNA. Cas13d can significantly enhance the therapeutic effects of diverse small molecule drugs against coronaviruses for prophylaxis or treatment purposes, and the best combination reduced viral titer by over four orders of magnitude. Using lipid nanoparticle-mediated RNA delivery, we demonstrate that the Cas13d system can effectively treat infection from multiple variants of coronavirus, including Omicron SARS-CoV-2, in human primary airway epithelium air-liquid interface (ALI) cultures. Our study establishes CRISPR-Cas13 as a BSA which is highly complementary to existing vaccination and antiviral treatment strategies.

Multi-color super-resolution imaging to study human coronavirus RNA during cellular infection.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the third human coronavirus within 20 years that gave rise to a life-threatening disease and the first to reach pandemic spread. To make therapeutic headway against current and future coronaviruses, the biology of coronavirus RNA during infection must be precisely understood. Here, we present a robust and generalizable framework combining high-throughput confocal and super-resolution microscopy imaging to study coronavirus infection at the nanoscale. Using the model human coronavirus HCoV-229E, we specifically labeled coronavirus genomic RNA (gRNA) and double-stranded RNA (dsRNA) via multi-color RNA immunoFISH and visualized their localization patterns within the cell. The 10-nm resolution achieved by our approach uncovers a striking spatial organization of gRNA and dsRNA into three distinct structures and enables quantitative characterization of the status of the infection after antiviral drug treatment. Our approach provides a comprehensive imaging framework that will enable future investigations of coronavirus fundamental biology and therapeutic effects.

A comprehensive analysis and resource to use CRISPR-Cas13 for broad-spectrum targeting of RNA viruses.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and variants has led to significant mortality. We recently reported that an RNA-targeting CRISPR-Cas13 system, called prophylactic antiviral CRISPR in human cells (PAC-MAN), offered an antiviral strategy against SARS-CoV-2 and influenza A virus. Here, we expand in silico analysis to use PAC-MAN to target a broad spectrum of human- or livestock-infectious RNA viruses with high specificity, coverage, and predicted efficiency. Our analysis reveals that a minimal set of 14 CRISPR RNAs (crRNAs) is able to target >90% of human-infectious viruses across 10 RNA virus families. We predict that a set of 5 experimentally validated crRNAs can target new SARS-CoV-2 variant sequences with zero mismatches. We also build an online resource (crispr-pacman.stanford.edu) to support community use of CRISPR-Cas13 for broad-spectrum RNA virus targeting. Our work provides a new bioinformatic resource for using CRISPR-Cas13 to target diverse RNA viruses to facilitate the development of CRISPR-based antivirals.

A novel multiple instance learning framework for COVID-19 severity assessment via data augmentation and self-supervised learning.

How to fast and accurately assess the severity level of COVID-19 is an essential problem, when millions of people are suffering from the pandemic around the world. Currently, the chest CT is regarded as a popular and informative imaging tool for COVID-19 diagnosis. However, we observe that there are two issues - weak annotation and insufficient data that may obstruct automatic COVID-19 severity assessment with CT images. To address these challenges, we propose a novel three-component method, i.e., 1) a deep multiple instance learning component with instance-level attention to jointly classify the bag and also weigh the instances, 2) a bag-level data augmentation component to generate virtual bags by reorganizing high confidential instances, and 3) a self-supervised pretext component to aid the learning process. We have systematically evaluated our method on the CT images of 229 COVID-19 cases, including 50 severe and 179 non-severe cases. Our method could obtain an average accuracy of 95.8%, with 93.6% sensitivity and 96.4% specificity, which outperformed previous works.

Anatomic Repair of Left Main Coronary Artery Atresia: Coronary Ostioplasty With Autologous Pulmonary Artery.

BACKGROUND: Left main coronary arterial (LMCA) atresia is a rare coronary arterial anomaly with extremely limited data on the optimal management. We aimed to report our single-surgeon experience of the ostioplasty in patients with LMCA atresia. METHODS: From July 2018 to December 2019, pediatric patients who presented with LMCA atresia and subsequently underwent surgical coronary ostioplasty were recruited into this retrospective study. Concomitant mitral repair was applied when the regurgitation was moderate or more severe. RESULTS: A total of 9 patients diagnosed with LMCA atresia were included. Mitral regurgitation was found in all of them, including 6 (66.7%) severe, 1 (11.1%) moderate, and 2 (22.2%) mild. In addition to ischemic lesions, which were found in 7 (77.8%) patients, structural mitral problems were also common (presented in 7 [77.8%] patients). All the patients underwent coronary ostioplasty with autologous pulmonary arterial patch augmenting the anterior wall of the neo-ostium. Mean aortic cross clamp time and cardiopulmonary bypass time was 88.1 ± 18.9 and 124.6 ± 23.6 minutes, respectively. During a median of 10.9 (range: 3.3 to 17.2) months' follow-up, there was only 1 death at 5 months after surgery. All survivors were recovered uneventfully with normal left-ventricular function; however, with 4 (50.0%) having significant recurrence of mitral regurgitation. CONCLUSIONS: With favourable surgical outcomes, coronary ostioplasty for LMCA atresia may be an option of revascularization. Structural mitral problems presented in majority patients, resulting in the requirement of concomitant mitral repair. However, the optimal technique of mitral repair remains unclear.

Development of CRISPR as an Antiviral Strategy to Combat SARS-CoV-2 and Influenza.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, has highlighted the need for antiviral approaches that can target emerging viruses with no effective vaccines or pharmaceuticals. Here, we demonstrate a CRISPR-Cas13-based strategy, PAC-MAN (prophylactic antiviral CRISPR in human cells), for viral inhibition that can effectively degrade RNA from SARS-CoV-2 sequences and live influenza A virus (IAV) in human lung epithelial cells. We designed and screened CRISPR RNAs (crRNAs) targeting conserved viral regions and identified functional crRNAs targeting SARS-CoV-2. This approach effectively reduced H1N1 IAV load in respiratory epithelial cells. Our bioinformatic analysis showed that a group of only six crRNAs can target more than 90% of all coronaviruses. With the development of a safe and effective system for respiratory tract delivery, PAC-MAN has the potential to become an important pan-coronavirus inhibition strategy.