Engineered Migrasomes: A Robust, Thermally Stable Vaccination Platform (preprint)

The burgeoning abilities of pathogens and tumor cells to evade immune responses underscore the urgent need for innovative vaccination platforms based on a variety of biological mechanisms. The current logistical challenges associated with cold-chain (i.e. low-temperature) transportation particularly impacts access to vaccines in the global south. We recently discovered organelles called migrasomes, and herein we investigate the potential of migrasomes as an alternative vaccination platform. Their inherent stability and their enrichment with immune-modulating molecules make migrasomes promising candidates, but their low yield presents a hurdle. We address this problem through our engineered migrasome-like vesicles (eMigrasomes), which emulate the biophysical attributes of natural migrasomes with substantially improved yield. We show that eMigrasomes loaded with a model antigen elicit potent antibody responses and maintain stability at room temperature. We demonstrate that eMigrasomes bearing the SARS-CoV-2 Spike protein induce robust humoral protection against the virus. Our study demonstrates the potential of eMigrasome-based vaccines as a unique, robust, and accessible alternative to traditional methods.

Based on the Theory of Mastery Learning and Reinforcement theory: The relationship between online student engagement and skills test scores in Clinical Skills Course (preprint)

Background:  The sudden outbreak of the COVID-19 pandemic in 2019 has affected our lives in different ways. The teaching method of colleges and universities has changed from traditional face-to-face learning to online learning. Clinical skills teaching is one of the core contents of clinical medical teaching. The key to ensure that students have a good grasp of learning is to ensure that they have enough time to learn effectively.Based on the mastery learning theory and reinforcement theory, the mixed online and offline teaching mode is carried out, which not only has the flexibility and convenience of online teaching, but also provides students with better offline teacher-student interaction and practical operation practice,which is more suitable for practical courses such as clinical skills courses.Studies have shown that student engagement in face-to-face learning is directly related to academic record. Little research has been done on the relationship between online student engagement and academic performance. Objective: Based on mastery learning theory and reinforcement theory in the teaching of clinical skills courses, and to explore the impact of online student engagement on academic performance and its magnitude in Clinical Skills Course by constructing a structural equation model. Methods:  259 fourth-year clinical medicine students volunteered for the study. They watched the video of skill operation on the online learning platform and took the chapter test before the class.Then they entered the face-to-face class with teacher demonstration and guidance to practice the operation.Finally, we arrange an online comprehensive theory test and an offline skill operation test.Throughout the course, they can discuss the course content interactivelyon the online platform.Record their video viewing duration, times of chapter learning, times of discussions, chapter test scores, comprehensive test scores and offline skill test scores.Amos was used to construct structural equation model to analyze the data. Results:  The results showed that the model fits well(`c/df=1.565,GFI=0.984,AGFI=0.958,CFI=0.952,RMSEA=0.047);In Clinical Skills Course, applied learning behaviors (such as times of discussions, chapter test scores, comprehensive test scores) had a direct impact on clinical skills test scores, and the standardized path coefficient was 0.3 (p<0.05). Observational learning behaviors (such as video viewing duration and times of chapter learning) can directly affect applied learning behaviors, with a standardized path coefficient of 0.63 (p<0.05), and then indirectly affect clinical skills test scores through applied learning behaviors. Conclusion:  Based on mastery learning theory and reinforcement theory in the online and offline blended clinical skills course teaching,enhancing observational learning behavior can improve the scores of applied learning behavior, and thus improve the scores of clinical skills examination.

Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

Continuous evolution and emerging lineage of seasonal human coronaviruses: A multicenter surveillance study.

The seasonal human coronaviruses (HCoVs) have zoonotic origins, repeated infections, and global transmission. The objectives of this study are to elaborate the epidemiological and evolutionary characteristics of HCoVs from patients with acute respiratory illness. We conducted a multicenter surveillance at 36 sentinel hospitals of Beijing Metropolis, China, during 2016-2019. Patients with influenza-like illness (ILI) and severe acute respiratory infection (SARI) were included, and submitted respiratory samples for screening HCoVs by multiplex real-time reverse transcription-polymerase chain reaction assays. All the positive samples were used for metatranscriptomic sequencing to get whole genomes of HCoVs for genetical and evolutionary analyses. Totally, 321 of 15 677 patients with ILI or SARI were found to be positive for HCoVs, with an infection rate of 2.0% (95% confidence interval, 1.8%-2.3%). HCoV-229E, HCoV-NL63, HCoV-OC43, and HCoV-HKU1 infections accounted for 18.7%, 38.3%, 40.5%, and 2.5%, respectively. In comparison to ILI cases, SARI cases were significantly older, more likely caused by HCoV-229E and HCoV-OC43, and more often co-infected with other respiratory pathogens. A total of 179 full genome sequences of HCoVs were obtained from 321 positive patients. The phylogenetical analyses revealed that HCoV-229E, HCoV-NL63 and HCoV-OC43 continuously yielded novel lineages, respectively. The nonsynonymous to synonymous ratio of all key genes in each HCoV was less than one, indicating that all four HCoVs were under negative selection pressure. Multiple substitution modes were observed in spike glycoprotein among the four HCoVs. Our findings highlight the importance of enhancing surveillance on HCoVs, and imply that more variants might occur in the future.

Empowering Patients and Transforming Healthcare in the Post-COVID-19 Era: The Role of Digital and Wearable Technologies.

The COVID-19 pandemic has dramatically impacted the global healthcare system, revealing critical gaps in our capacity to provide efficient and effective care to patients, particularly those with chronic diseases [...].

COVID-related dysphonia and persistent long-COVID voice sequelae: A systematic review and meta-analysis.

PURPOSE: Dysphonia is a common symptom due to the coronavirus disease of the 2019 (COVID-19) infection. Nonetheless, it is often underestimated for its impact on human's health. We conducted this first study to investigate the global prevalence of COVID-related dysphonia as well as related clinical factors during acute COVID-19 infection, and after a mid- to long-term follow-up following the recovery. METHODS: Five electronic databases including PubMed, Embase, ScienceDirect, the Cochrane Library, and Web of Science were systematically searched for relevant articles until Dec, 2022, and the reference of the enrolled studies were also reviewed. Dysphonia prevalence during and after COVID-19 infection, and voice-related clinical factors were analyzed; the random-effects model was adopted for meta-analysis. The one-study-removal method was used for sensitivity analysis. Publication bias was determined with funnel plots and Egger's tests. RESULTS: Twenty-one articles comprising 13,948 patients were identified. The weighted prevalence of COVID-related dysphonia during infection was 25.1 % (95 % CI: 14.9 to 39.0 %), and male was significantly associated with lower dysphonia prevalence (coefficients: -0.116, 95 % CI: -0.196 to -0.036; P = .004) during this period. Besides, after recovery, the weighted prevalence of COVID-related dysphonia declined to 17.1 % (95 % CI: 11.0 to 25.8 %). 20.1 % (95 % CI: 8.6 to 40.2 %) of the total patients experienced long-COVID dysphonia. CONCLUSIONS: A quarter of the COVID-19 patients, especially female, suffered from voice impairment during infection, and approximately 70 % of these dysphonic patients kept experiencing long-lasting voice sequelae, which should be noticed by global physicians.

Swine acute diarrhoea syndrome coronavirus (SADS-CoV) Nsp5 antagonizes type I interferon signaling by cleaving DCP1A.

Swine acute diarrhoea syndrome coronavirus (SADS-CoV), which is a recently discovered enteric coronavirus, is the major aetiological agent that causes severe clinical diarrhoea and intestinal pathological damage in pigs, and it has caused significant economic losses to the swine industry. Nonstructural protein 5, also called 3C-like protease, cleaves viral polypeptides and host immune-related molecules to facilitate viral replication and immune evasion. Here, we demonstrated that SADS-CoV nsp5 significantly inhibits the Sendai virus (SEV)-induced production of IFN-ß and inflammatory cytokines. SADS-CoV nsp5 targets and cleaves mRNA-decapping enzyme 1a (DCP1A) via its protease activity to inhibit the IRF3 and NF-κB signaling pathways in order to decrease IFN-ß and inflammatory cytokine production. We found that the histidine 41 and cystine 144 residues of SADS-CoV nsp5 are critical for its cleavage activity. Additionally, a form of DCP1A with a mutation in the glutamine 343 residue is resistant to nsp5-mediated cleavage and has a stronger ability to inhibit SADS-CoV infection than wild-type DCP1A. In conclusion, our findings reveal that SADS-CoV nsp5 is an important interferon antagonist and enhance the understanding of immune evasion by alpha coronaviruses.

The Protective Nature of Gold During Times of Oil Price Volatility: An Analysis of the COVID-19 Pandemic.

This research explores gold's safe-haven properties amid oil price instability, focusing on the COVID-19 pandemic. The study examines how gold hedges against oil price swings in the context of the pandemic's exceptional market circumstances. A VAR (Vector Autoregressive) model analyzes gold and oil prices from 2006 through 2021. The VAR model reflects the dynamic interactions and interdependencies between these two essential commodities in the context of oil price volatility and the COVID-19 pandemic. This analysis shows that gold protects against oil price volatility and the COVID-19 pandemic-gold buffers against oil price swings due to its strong inverse association with oil prices. Gold offers investors security and asset preservation during significant oil price volatility. In light of oil price volatility and the COVID-19 pandemic, the study helps explain gold's importance as a diversification tool and haven asset. Investors, policymakers, and market players should consider gold as a hedge against oil price volatility and economic instability.

Mitochondria-Targeted Fluorescent Nanoparticles with Large Stokes Shift for Long-Term BioImaging.

Mitochondria (MITO) play a significant role in various physiological processes and are a key organelle associated with different human diseases including cancer, diabetes mellitus, atherosclerosis, Alzheimer's disease, etc. Thus, detecting the activity of MITO in real time is becoming more and more important. Herein, a novel class of amphiphilic aggregation-induced emission (AIE) active probe fluorescence (AC-QC nanoparticles) based on a quinoxalinone scaffold was developed for imaging MITO. AC-QC nanoparticles possess an excellent ability to monitor MITO in real-time. This probe demonstrated the following advantages: (1) lower cytotoxicity; (2) superior photostability; and (3) good performance in long-term imaging in vitro. Each result of these indicates that self-assembled AC-QC nanoparticles can be used as effective and promising MITO-targeted fluorescent probes.

Potent NTD-Targeting Neutralizing Antibodies against SARS-CoV-2 Selected from a Synthetic Immune System.

The majority of neutralizing antibodies (NAbs) against SARS-CoV-2 recognize the receptor-binding domain (RBD) of the spike (S) protein. As an escaping strategy, the RBD of the virus is highly variable, evolving mutations to thwart a natural immune response or vaccination. Targeting non-RBD regions of the S protein thus provides a viable alternative to generating potential, robust NAbs. Using a pre-pandemic combinatorial antibody library of 1011, through an alternate negative and positive screening strategy, 11 non-RBD-targeting antibodies are identified. Amongst one NAb that binds specifically to the N-terminal domain of the S protein, SA3, shows mutually non-exclusive binding of the angiotensin-converting enzyme 2 receptor with the S protein. SA3 appears to be insensitive to the conformational change and to interact with both the "open" and "closed" configurations of the trimeric S protein. SA3 shows compatible neutralization as S-E6, an RBD-targeting NAb, against the wild type and variant of concern (VOC) B.1.351 (Beta) of the SARS-CoV-2 pseudo virus. More importantly, the combination of SA3 with S-E6 is synergistic and recovers from the 10-fold loss in neutralization efficacy against the VOC B.1.351 pseudo virus.

Safety and immunogenicity of a modified COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults: an open-labeled, two-centered and multi-arm randomised, phase 1 trial.

BACKGROUND: We assessed the safety and immunogenicity of a core-shell structured lipopolyplex (LPP) based COVID-19 mRNA vaccine, SW-BIC-213, as a heterologous booster in healthy adults. METHODS: We conducted an open-labeled, two-centered, and three-arm randomised phase 1 trial. Healthy adults, who had completed a two-dose of inactivated COVID-19 vaccine for more than six months, were enrolled and randomized to receive a booster dose of COVILO (inactivated vaccine) (n = 20) or SW-BIC-213-25µg (n = 20), or SW-BIC-213-45µg (n = 20). The primary study endpoint was adverse events within 30 days post-boosting. The secondary endpoint was the titers of binding antibodies and neutralizing antibodies against the wild-type (WT) of SARS-CoV-2 as well as variants of concern in serum. The exploratory endpoint was the cellular immune responses. This trial was registered with http://www.chictr.org.cn (ChiCTR2200060355). FINDINGS: Between Jun 6 and Jun 22, 2022, 60 participants were enrolled and randomized to receive a booster dose of SW-BIC-213 (25 µg, n = 20, or 45 µg, n = 20) or COVILO (n = 20). The baseline demographic characteristics of the participants at enrollment were similar among the treatment groups. For the primary outcome, injection site pain and fever were more common in the SW-BIC-213 groups (25 µg and 45 µg). Grade 3 fever was reported in 25% (5/20) of participants in the SW-BIC-213-45µg group but was resolved within 48 h after onset. No fatal events or adverse events leading to study discontinuation were observed. For secondary and exploratory outcomes, SW-BIC-213 elicited higher and longer humoral and cellular immune responses than that in the COVILO group. INTERPRETATION: SW-BIC-213, a core-shell structured lipopolyplex (LPP) based mRNA vaccine, was safe, tolerable, and immunogenic as a heterologous booster in healthy Chinese adults. FUNDING: Shanghai Municipal Government, the Science and Technology and Economic Commission of Shanghai Pudong New Area, and mRNA Innovation and Translation Center of Shanghai.

A Two-Stage Voting-Boosting Technique for Ensemble Learning in Social Network Sentiment Classification.

In recent years, social network sentiment classification has been extensively researched and applied in various fields, such as opinion monitoring, market analysis, and commodity feedback. The ensemble approach has achieved remarkable results in sentiment classification tasks due to its superior performance. The primary reason behind the success of ensemble methods is the enhanced diversity of the base classifiers. The boosting method employs a sequential ensemble structure to construct diverse data while also utilizing erroneous data by assigning higher weights to misclassified samples in the next training round. However, this method tends to use a sequential ensemble structure, resulting in a long computation time. Conversely, the voting method employs a concurrent ensemble structure to reduce computation time but neglects the utilization of erroneous data. To address this issue, this study combines the advantages of voting and boosting methods and proposes a new two-stage voting boosting (2SVB) concurrent ensemble learning method for social network sentiment classification. This novel method not only establishes a concurrent ensemble framework to decrease computation time but also optimizes the utilization of erroneous data and enhances ensemble performance. To optimize the utilization of erroneous data, a two-stage training approach is implemented. Stage-1 training is performed on the datasets by employing a 3-fold cross-segmentation approach. Stage-2 training is carried out on datasets that have been augmented with the erroneous data predicted by stage 1. To augment the diversity of base classifiers, the training stage employs five pre-trained deep learning (PDL) models with heterogeneous pre-training frameworks as base classifiers. To reduce the computation time, a two-stage concurrent ensemble framework was established. The experimental results demonstrate that the proposed method achieves an F1 score of 0.8942 on the coronavirus tweet sentiment dataset, surpassing other comparable ensemble methods.

Masked Face Recognition System Based on Attention Mechanism

With the continuous development of deep learning, the face recognition field has also developed rapidly. However, with the massive popularity of COVID-19, face recognition with masks is a problem that is now about to be tackled in practice. In recognizing a face wearing a mask, the mask obscures most of the facial features of the face, resulting in the general face recognition model only capturing part of the facial information. Therefore, existing face recognition models are usually ineffective in recognizing faces wearing masks. This article addresses this problem in the existing face recognition model and proposes an improvement of Facenet. We use ConvNeXt-T as the backbone of the network model and add the ECA (Efficient Channel Attention) mechanism. This enhances the feature extraction of the unobscured part of the face to obtain more useful information, while avoiding dimensionality reduction and not increasing the model complexity. We design new face recognition models by investigating the effects of different attention mechanisms on face mask recognition models and the effects of different data set ratios on experimental results. In addition, we construct a large set of faces wearing masks so that we can efficiently and quickly train the model. Through experiments, our model proved to be 99.76% accurate for real faces wearing masks. A combined accuracy of 99.48% for extreme environments such as too high or lousy contrast and brightness.

Ionizable drug delivery systems for efficient and selective gene therapy.

Gene therapy has shown great potential to treat various diseases by repairing the abnormal gene function. However, a great challenge in bringing the nucleic acid formulations to the market is the safe and effective delivery to the specific tissues and cells. To be excited, the development of ionizable drug delivery systems (IDDSs) has promoted a great breakthrough as evidenced by the approval of the BNT162b2 vaccine for prevention of coronavirus disease 2019 (COVID-19) in 2021. Compared with conventional cationic gene vectors, IDDSs can decrease the toxicity of carriers to cell membranes, and increase cellular uptake and endosomal escape of nucleic acids by their unique pH-responsive structures. Despite the progress, there remain necessary requirements for designing more efficient IDDSs for precise gene therapy. Herein, we systematically classify the IDDSs and summarize the characteristics and advantages of IDDSs in order to explore the underlying design mechanisms. The delivery mechanisms and therapeutic applications of IDDSs are comprehensively reviewed for the delivery of pDNA and four kinds of RNA. In particular, organ selecting considerations and high-throughput screening are highlighted to explore efficiently multifunctional ionizable nanomaterials with superior gene delivery capacity. We anticipate providing references for researchers to rationally design more efficient and accurate targeted gene delivery systems in the future, and indicate ideas for developing next generation gene vectors.

Efficacy of blood urea nitrogen-to-albumin ratio for predicting prognostic outcomes of inpatients with COVID-19: A meta-analysis.

BACKGROUND: The associations between blood urea nitrogen (BUN)/albumin ratio and poor prognosis in patients with diagnosis of coronavirus disease 2019 (COVID-19) remain to be clarified. METHODS: A search based on 4 electronic databases (i.e., EMBASE, Google scholar, MEDLINE, and Cochrane Library) was performed on June 23, 2022. The association of BUN/Albumin ratio with poor prognostic outcomes, defined as patients with mortality/severe illnesses, were analyzed. RESULTS: Results from analysis of 7 cohort studies (3600 individuals with COVID-19) published between 2020 and 2022 showed a higher BUN/Albumin ratio in the poor-prognosis group (Mean difference:  = 2.838, 95% confidence interval: 2.015-3.66, P < .001, I2 = 92.5%) than the good-prognosis group. Additional investigation into the connection between BUN/Albumin ratio as a binary variable (i.e., high or low) and the risk of poor outcome also supported an association between a higher BUN/Albumin ratio and a poor prognostic risk (odd ratio = 3.009, 95% confidence interval: 1.565-5.783, P = .001, I2 = 93.7%, 5 studies). Merged analysis of poor prognosis produced a sensitivity of 0.76, specificity of 0.72, and area under curve of 0.81. CONCLUSION: This meta-analysis demonstrated a positive correlation between BUN/albumin ratio and poor outcome in patients with COVID-19. Additional large-scale prospective studies are needed to verify our findings.

The Impact of a Lockdown for the COVID-19 Pandemic on Seasonal HbA1c Variation in Patients with Type 2 Diabetes.

Glycemic control in patients with type 2 diabetes may be disrupted due to restricted medical service access and lifestyle changes during COVID-19 lockdown period. This retrospective cohort study examined changes of HbA1c levels in adults with type 2 diabetes 12 weeks before and after May 19 in 2021, the date that COVID-19 lockdown began in Taiwan. The mean levels of HbA1c-after were significantly lower than HbA1c-before in 2019 (7.27 ± 1.27% vs 7.43 ± 1.38%, p < 0.001), 2020 (7.27 ± 1.28% vs 7.37 ± 1.34%, p < 0.001), and 2021 (7.03 ± 1.22% vs 7.17 ± 1.29%, p < 0.001). Considering the seasonal variation of HbA1c, ΔHbA1c values (HbA1c-after minus HbA1c-before) in 2020 (with sporadic COVID-19 cases and no lockdown) were not significantly different from 2021 (regression coefficient [95% CI] = 0.01% [-0.02%, 0.03%]), while seasonal HbA1c variation in 2019 (no COVID-19) was significantly more obvious than in 2021 (-0.05% [-0.07, -0.02%]). In conclusion, HbA1c level did not deteriorate after a lockdown measure during the COVID-19 pandemic in Taiwan. However, the absolute seasonal reduction in HbA1c was slightly less during the COVID-19 pandemic compared with the year without COVID-19.

On summary ROC curve for dichotomous diagnostic studies: an application to meta-analysis of COVID-19.

In a systematic review of a diagnostic performance, summarizing performance metrics is crucial. There are various summary models in the literature, and hence model selection becomes inevitable. However, most existing large-sample-based model selection approaches may not fit in a meta-analysis of diagnostic studies, typically having a rather small sample size. Researchers need to effectively determine the final model for further inference, which motivates this article to investigate existing methods and to suggest a more robust method for this need. We considered models covering several widely-used methods for bivariate summary of sensitivity and specificity. Simulation studies were conducted based on different number of studies and different population sensitivity and specificity. Then final models were selected using several existing criteria, and we compared the summary receiver operating characteristic (sROC) curves to the theoretical ROC curve given the generating model. Even though parametric likelihood-based criteria are often applied in practice for their asymptotic property, they fail to consistently choose appropriate models under the limited number of studies. When the number of studies is as small as 10 or 5, our suggestion is best in different scenarios. An example for summary ROC curves for chemiluminescence immunoassay (CLIA) used in COVID-19 diagnosis is also illustrated.

Systemic lupus erythematosus in a 36-year old Filipino male after SARS-COV- 2 vaccination

Background: Systemic lupus erythematosus (SLE), a multisystem autoimmune disease more common in females, is associated with autoantibodies against different autoantigens forming immune complexes. Inadequate removal of these complexes from the host triggers inflammatory response which causes tissue damage. Some antiviral vaccines have been associated with the onset of SLE. Few cases of SLE occurring after SARS-CoV- 2 vaccines have been reported. Herein, we describe a case of new-onset SLE associated with COVID-19 vaccine. Case Summary: A previously well 36-year- old male with unremarkable family history of autoimmune disease started to develop muscle and joint pains, hair thinning, and ecchymoses 2 months after receiving second dose of inactivated SARS-CoV- 2 vaccine. He was subsequently admitted after consultation due to thrombocytopenia (platelet count of 58). He was given high dose steroid with tapering dose during the entire 14 days admission with significant increase of platelet count after 72 hours of repeat complete blood count. He went consult at rheumatology clinic a month after due to persistent joint and muscle pains, and progression of hair fall with associated facial rash, oral ulcers, easy fatigability and weight loss. Physical exam disclosed an ambulatory well-built male with normal vital signs, alopecia, malar rash, oral ulcers, joint tenderness and no objective muscle weakness. Complete blood counts and Anti-smith were within normal. Urinalysis, Antinuclear antibody (ANA), Anti-SSA, Anti-SSB, complement factor 3 (C3), and Anti-dsDNA were positive. He was managed with tapering prednisone and hydroxychloroquine with significant improvement at time of this report. Conclusion(s): Development of autoimmune reaction following COVID-19 vaccine has been described extensively;however, evidence of autoimmunity following vaccination seems to be lacking at present. Pathomechanisms include defective elimination and/or control of self-reactive lymphocytes resulting in over-stimulation of the immune system leading to clinical manifestations strikingly similar to the infection itself. Management approach to these autoimmune reactions address the immune hyper-stimulation with immunosuppressive or immuno-modulating agents including steroids and hydroxychloroquine.