Exploring alexithymia profiles and their associations with childhood adversity and COVID-19 burnout among Chinese college students: A person-centered approach

Alexithymia is associated with adverse developmental outcomes. However, this concept has been criticized for being heavily influenced by Western norms of emotional expression and for potentially pathologizing people from different cultural backgrounds. Furthermore, the widely employed variable-centered study approaches hinder research understanding of real-world alexithymia profiles. Using a person-centered approach, the current study investigated the alexithymia profiles among Chinese college students and tested the profiles' relations with childhood adversity and COVID-19 burnout. Four latent alexithymia profiles were identified. The High I profile (particular difficulty identifying feelings) emerged as a risk profile for childhood adversity and COVID-19 burnout. Our findings illustrate the heterogeneity of the alexithymia construct and represent a significant step toward expanding cross-cultural understanding of alexithymia profiles and their associations with related psychological constructs. When dealing with childhood adversity and COVID-19 burnout, health care programs should consider a specific alexithymia profile defined by difficulty identifying feelings. © 2022 Elsevier Inc.

Detection of COVID-19 Through Thermal and Voice Sensing Using Smartphone

Since the end of 2019, the world has been caught in the crisis of the COVID-19 which is a serious epidemic disease. This paper seeks to come up with a fast and efficient COVID-19 detection and monitoring easy to use system which can be used in the facilities of densely populated areas, such as community centers and school clinics, to quickly identify suspected COVID-19 patients. This system could detect the probability of a person getting infected by COVID-19 using an android smartphone and thermal camera. Three types of data are collected from users: breathe sound, thermal video, and health status. Generally, the breathe audio and thermal video are preprocessed into two-time series, which indicate the breath status of the user. Then, the two series are inputted into the Bidirectional Gated Recurrent Unit (BI-GRU) neural network model separately to get the infection rates. Since the real data is difficult to get due to privacy reasons, a synthetic dataset is generated based on mathematical equations to train the model. For health status, the application requires the user to fill a questionnaire and calculates an infection rate through a medical prediction model. Finally, the two values from the machine learning model and the infection rate from the user report are added together with weight to calculate the final predictive infection rate. © 2022 IEEE.

Artificial intelligence and its contribution to overcome COVID-19

Artificial intelligence (AI) has a great impact on our daily living and makes our lives more efficient and productive. Especially during the coronavirus disease (COVID-19) pandemic, AI has played a key role in response to the global health crisis. There has been a boom in AI innovation and its use since the pandemic. However, despite its widespread adoption and great potential, most people have little knowledge of AI concepts and realization of its potential. The objective of this white paper is to communicate the importance of AI and its benefits to society. The report covers AI applications in six different topics from medicine (AI deployment in clinical settings, imaging and diagnostics, and acceleration of drug discovery) to more social aspects (support older adults in long-term care homes, and AI in supporting small and medium enterprises. The report ends with nine steps to consider for moving forward with AI implementation during and post pandemic period. These include legal and ethical data collection and storage, greater data access, multidisciplinary collaboration, and policy reform.

An Image Importance Partition-based Compression Method for COVID-19 Computed Tomography Scan

As the coronavirus disease 2019 (COVID-19) spreads around the world, industrial automated medical diagnosis systems have been developed, which complete a large amount of medical diagnosis work through computed tomography (CT) images. In these systems, how to quickly store and transmit such a large amount of CT image information has important research significance. In this paper, a more targeted COVID-19 chest CT image codec is proposed to make image data not only occupy less space but also have higher image quality. First, the bilateral lung contours are extracted to calculate the position information of the region of interest (ROI). Then, a CT image is classified into four types of non-uniform image blocks according to the characteristics of COVID-19 chest CT images and ROI position information. Next, a series of new transformations are proposed for more efficient transform coding. Finally, a flexible quantization strategy is proposed for the adaptive quantization part. In the experiments, the proposed method is superior to some existing methods with similar computational complexity. At the same bit rate, it significantly improves the image quality. This means that chest CT images can still be used for disease diagnosis while taking up less space. In addition, because of the low computational complexity of the proposed method, it can be more easily embedded into the CT equipment with low computational power. IEEE

Switching from intravenous to subcutaneous infliximab in patients with active inflammatory bowel disease: post-hoc analysis of pre/post switch outcomes from a multicentre, randomised controlled pivotal

Introduction: A subcutaneous (SC) infliximab (IFX), CT-P13 SC, has received regulatory approval from the European Medicines Agency for indications including inflammatory bowel disease.1 In response to the coronavirus disease 2019 (COVID-19) pandemic, clinical guidance has recommended considering switching from intravenous (IV) treatment to SC alternatives to minimise hospital visits.2 Aims & Methods: In this analysis, data from the pivotal randomised controlled trial (NCT02883452) of CT-P13 SC in patients with active Crohn's disease (CD) and ulcerative colitis (UC) were analysed to investigate the clinical impact of switching from IV to SC IFX.3 Patients in the CT-P13 IV arm of the pivotal trial received CT-P13 5 mg/kg IV every 8 weeks from Week (W) 6 until W22. At W30, patients switched to receive CT-P13 SC every 2 weeks up to W54 (dose 120 mg or 240 mg for patients <80 kg or ≥80 kg, respectively).3 This post hoc analysis compared per-patient pairwise data at W30 (pre-switch) and W54 (post-switch) from the CT-P13 IV arm for the following outcomes: trough serum concentration (Ctrough;5 μg/mL was considered to be the target exposure level), clinical response (for CD patients, ≥100-point decrease in Crohn's Disease Activity Index score;for UC patients, ≥2-point decrease in partial Mayo score with accompanying ≥1-point decrease in rectal bleeding subscore or an absolute rectal bleeding subscore of 0 or 1) and immunogenicity (anti-drug antibody [ADA] and neutralising antibody [NAb] positivity;as measured by a drug tolerant assay;ADA negative was regarded as NAb negative). For pairwise comparisons, patients with missing data at either W30 or W54 were excluded from the analysis. Statistical comparisons used Fisher's exact test. The differences are reported in a descriptive manner. Results: Overall, 65 patients (25 CD;40 UC) were included in the CT-P13 IV arm. The proportion of patients with a Ctrough level exceeding target exposure was significantly higher post-switch (36/41, 87.8%) than pre-switch (8/41, 19.5%;p<0.00001) (Table). Clinical response rates were comparable at both pre- and post-switch timepoints (40/49 [81.6%] vs 44/49 [89.8%], respectively;p=0.3873). Positive ADA and NAb rates at pre-switch and post-switch were also comparable, in which some changes were regarded from patients with marginal value (Table). Conclusion: Switching from IV to SC IFX did not detrimentally affect the clinical outcomes of patients with active CD or UC. Further, switching from IV to SC IFX might confer more favourable pharmacokinetic outcomes, although larger comparative studies are warranted. (Table Presented).

Severity Assessment of COVID-19 Based on Feature Extraction and V-Descriptors

Digital image feature recognition is significant to industrial information applications, such as bioengineering, medical diagnosis, and machinery industry. In order to supply an effective and reasonable technology of the severity assessment mission of coronavirus disease (COVID-19), in this article, we propose a new method that identifies rich features of lung infections from a chest computed tomography (CT) image, and then assesses the severity of COVID-19 based on the extracted features. First, in a chest CT image, the lung contours are corrected for the segmentation of bilateral lungs. Then, the lung contours and areas are obtained from the lung regions. Next, the coarseness, contrast, roughness, and entropy texture features are extracted to confirm the COVID-19 infected regions, and then the lesion contours are extracted from the infected regions. Finally, the texture features and V-descriptors are fused as an assessment descriptor for the COVID-19 severity estimation. In the experiments, we show the feature extraction and lung lesion segmentation results based on some typical COVID-19 infected CT images. In the lesion contour reconstruction experiments, the performance of V-descriptors is compared with some different methods, and various feature scores indicate that the proposed assessment descriptor reflects the infected ratio and the density feature of the lesions well, which can estimate the severity of COVID-19 infection more accurately.

Allogeneic Stem Cell Transplantation in a Large Urban Cohort of North-American Adult T-Cell Leukemia/Lymphoma

Introduction: Adult T-cell leukemia lymphoma (ATLL) is a rare hematologic malignancy caused by human T-cell lymphotropic virus (HTLV-1) with dismal cure rates and poor response to conventional chemotherapy. Allogeneic Hematopoietic Stem Cell Transplantation (AlloSCT) is the only therapeutic option which may offer the chance of long-term remission and cures in a subset of patients. We sought to investigate the outcomes of transplantation in one of the largest cohorts in North America. Methods: A retrospective chart review study was conducted using the North-American ATLL and the Hematopoietic Precursor Cell transplantation databases at Montefiore Medical Center from 2011 to 2020. Variables collected include age, sex, ethnicity, ATLL subtype, molecular profile, previous treatments, conditioning regimens, type of transplant, immunosuppressive regimen, progression free survival (PFS) post-transplant and overall survival (OS) post-transplant. Results: Fourteen patients with ATLL who received an AlloSCT from 2011-2020 were identified. Fifty-seven percent (8/14) of patients were male. Seventy-one percent (10/14) of patients were African American and twenty-nine percent (4/14) were Hispanic. Median age was 51 years. Sixty-four percent (9/14) of patients had Stage IV disease at the time of diagnosis. Forty-three percent (6/14) patients had acute and fifty-seven percent (8/14) had lymphomatous ATLL. Almost all patients (92%) were treated initially with EPOCH combination chemotherapy. Twenty-eight percent (4/14) of patients received interferon/zidovudine as bridge-to-transplant. Fifty-seven percent (8/14) of patients achieved complete remission (CR) prior to AlloSCT, 7% (1/14) were in partial remission, and 28% (4/14) were relapsed or refractory. Forty-three percent (6/14) of patients received SCT from a matched-related donor (MRD), 36% (5/14) from a haplo-identical donor and 21% (3/14) from a matched-unrelated donor (MUD). Ninety-three percent (13/14) of patients received a reduced-intensity conditioning (RIC) regimen pre-transplantation. Seven percent (1/14) received a myeloablative conditioning (MAC) regimen. RIC regimens consisted of fludarabine with melphalan +/- anti-thymocyte globulin (ATG) or fludarabine with cyclophosphamide with total-body irradiation in doses less than 500 cGy. Patients receiving haplo-identical SCT also received post-transplant cyclophosphamide (PTCy) for prevention of graft vs host disease (GVHD). The MAC regimen used included busulfan with cyclophosphamide at myeloablative doses. Twenty-eight percent (4/14) of patients relapsed post-alloSCT with a median relapse-free survival of 6 months (range 4-18 months). The median OS of the whole cohort was 27 months (8-82 months). Graft-versus-host disease (GVHD) developed in 28% (4/14) percent of patients. The most common manifestation was skin GVHD. Fifty-percent (7/14) of the patients are surviving to-date. Transplant-related mortality (TRM) at day 100 was 21% (3/14) of patients. Causes of death were complex and included several diagnoses in certain patients. The most frequent diagnoses associated with death were infection (28%), graft failure (14%), GVHD (14%), veno-occlusive disease of the liver (VOD) (7%), disease progression (14%) and unknown due to patient lost to follow-up (14%). The main infectious events included fungal (2), bacterial (1), and COVID-19 (1) infection. Forty-three percent (6/14) of patients remain in complete remission to date. Conclusions: Allogeneic Stem Cell Transplantation offers long-term survival with a TRM of 21% in a disease with an inherently dismal prognosis. AlloSCT using several graft sources, is thus, a safe and well tolerated treatment modality and offers long term remissions. Disclosures: Steidl: Pieris Pharmaceuticals: Consultancy;Aileron Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding;Bayer Healthcare: Research Funding;Stelexis Therapeutics: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advi ory committees. Verma: BMS: Consultancy, Research Funding;acceleron: Consultancy, Honoraria;Janssen: Research Funding;Medpacto: Research Funding;stelexis: Current equity holder in private company. Janakiram: ADC Therapeutics, FATE therapeutics, TAKEDA pharmaceuticals: Research Funding.

Epidemic period of COVID-19: A comparative study of psychological status between breast cancer patients and normal crowd

OBJECTIVE: During the epidemic period of COVID-19, the treatment of breast cancer patients is limited to a great extent. Their psychological changes deserve attention. The purpose of this study was to investigate the psychological health, anxiety and depression of breast cancer patients during COVID-19. Compare them with healthy people in the same period, so as to lay a foundation for psychological intervention of breast cancer before and after the COVID-19 outbreak. METHODS: During 2019-01-10 and 2020-01-13, 128 female breast cancer patients in the First(86 cases) and Second(42 cases) Affiliated Hospitals of the Air Force Military Medical University were selected as the study objects (group A), and 121 social healthy adult women randomly answered by the Internet questionnaire were selected as the control group (group B). SCL-90, SAS and SDS were used to complete the questionnaire survey. RESULTS: The positive results of SCL-90 were as follows: anxiety(21.09%) and depression(17.18%) were the most common in group A;Anxiety(14.88%) and hostility(15.7%) were the most common in group B. Factor score analysis showed that depression(t=2.898, P=0.004), anxiety(t=3. 649, P<0.001) and hostility(t=3.824, P<0.001) in group A were higher than those in group B. The depression and anxiety of group B were higher than that of domestic norm. Further SAS and SDS analysis showed that anxiety(t=11.492, P<0.001) and depression(t=10.871, P<0.001) in group A were significantly higher than those in group B. In each subgroup: The psychological problems of depression(t=2.061, P=0.044), anxiety(t=2.183, P=0.039) and hostility(t=2.028, P=0.048) of patients who were under 45 years were more obvious than those patients who were over 45 years. The psychological problems of depression(t=2.759, P=0.007), anxiety(t=2.348, P=0.018) and fear(t=2.182, P=0.043) of the patients without higher education were more obvious than those of the educated. The psychological problems of depression(t=2.064, P=0.043), anxiety(t=2.581, P=0.017) and fear(t=2.086, P=0.041) of the patients who not received surgical treatment were more obvious than those who received surgical treatment. When it talked about living in a city or a country, it showed that only differences in anxiety(t=2.273, P=0.032). CONCLUSION:S During the period of COVID-19, the anxiety and depression symptoms arise between breast cancer patients. This phenomenon deserves special attention by the society and medical staff.

Evidence-Based Complementary and Alternative Medicine Exploring Active Components and Mechanism of Jinhua Qinggan Granules in Treatment of COVID-19 Based on Virus-Host Interaction

This study aimed at exploring the active components and mechanisms of Jinhua Qinggan granules (JQG) in the prevention and treatment of coronavirus disease 2019 (COVID-19) using network pharmacology and molecular docking technology. These efforts were accomplished by employing the holistic approach of traditional Chinese medicine (TCM) and considering the virus-host interaction consisting of viral characteristics, the entry pathway into the host, and the resulting immune response. The chemical constituents and molecular targets of the 12 herbs from JQG were obtained using the TCM Systems Pharmacology database and analysis platform. UniProt was used to search for genes corresponding to JQG protein targets and Cytoscape 3.7.2 to construct the component-target (gene) network. Database for Annotation, Visualization and Integrated Discovery was used to perform enrichment analysis of gene ontology functions and the Kyoto Encyclopedia of Genes and Genomes pathways to predict the mechanism of action. The components ranked high in the network, and the major active components of the principal medicines, based on published literature, were docked with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3CL hydrolase, SARS-CoV-2 spike glycoprotein (S protein), angiotensin conversion enzyme II (ACE2), and suppressor of cytokine signaling 1 (SOCS1). Visualization analysis demonstrated that the core active components of JQG had a strong affinity for SARS-CoV-2 3CL hydrolase, SARS-CoV-2 S protein, ACE2, and SOCS1. These data imply that the potential active components of JQG may act on multiple signaling pathways by binding to targets such as SARS-CoV-2 3CL hydrolase, S protein, ACE2, and SOCS1, thereby inhibiting virus replication and targeting cell binding, reducing host inflammation, and activating antiviral immunity to a certain extent.