We found that p53-loss appears to preferentially affect K8+ epithelial cells, leading to the development of uterine and ovarian malignancies, whereas PTEN-loss may preferentially affect mesothelial cells, leading to the development of ovarian endometrioid malignancies or adenoma on the fallopian tube surface. Collectively, our data suggest that oncogenic driver mutations may dominantly determine the locations and types of gynecological malignancies developed from K8+ mesothelial and epithelial cells in the female reproductive system.Ovarian and uterine cancers are the most common gynecological malignancies in women. The early detection, prevention, and treatment of these gynecological cancers can benefit from a better understanding of how tumor-initiating cells in them are formed from their corresponding target cell populations in the female reproductive system. To study this, we utilized a genetic approach in mice to introduce driver mutations commonly found in these cancers to Keratin 8 positive (K8Krt8 promoter (Ad-K8-Cre) to mice carrying combinations of various conditional alleles for cancer genes. We found that Ad-K8-Cre specifically targeted mesothelial cells, including ovarian surface epithelial (OSE) cells (mainly the LGR5+ subset of OSE cells) and mesothelial cells lining the fallopian tube (FT) serosa; the injected Ad-K8-Cre also targeted Müllerian-derived epithelial cells, including FT epithelial cells and uterine endometrial epithelial cells. The loss of p53 may preferentially affect Müllerian-derived epithelial cells, leading to the development of uterine and ovarian malignancies, whereas PTEN-loss may preferentially affect mesothelial cells, leading to the development of ovarian endometrioid malignancies (upon KRAS-activation or APC-loss) or adenoma on the FT surface (upon DICER-loss). Overall, our data suggest that different Krt8+ mesothelial and epithelial cell types in the female reproductive system may have different sensitivities toward oncogenic mutations and, as a result, oncogenic events may dominantly determine the locations and types of the gynecological malignancies developed from them.Ovarian and uterine cancers are the most prevalent types of gynecological malignancies originating from mesothelial and/or Müllerian-derived epithelial cells. Recent genomic studies have identified common mutations in them that affect signaling pathways such as p53, PTEN/PI3K, RAS, and WNT pathways. However, how these mutations and their corresponding deregulated pathways affect gynecological cancer development from their cells-of-origin remains largely elusive. To address this, we performed the intrabursal injection of Cre-expressing adenovirus under the control of  TP53 mutations, whereas most endometrioid tumors have frequent mutations in the PTEN/PI3K, WNT, RAS, and SWI/SNF pathways . To. ToLgr5, FT, and uterus , loxP/loxP;Brca1loxP/loxPTrp53 (p53/Brca1), Kras*G12D/+Rosa26-LSL-(G12D/+Kras)loxP/loxP;Pten (Pten/Kras), loxP/loxP;PtenloxP/loxPApc (Pten/Apc), Pik3ca*H1047R/+Rosa26-LSL- (H1047R/+Pik3ca)loxP/loxP;Pten (Pten/Pik3ca), and loxP/loxP;PtenloxP/loxPDicer (Pten/Dicer). We monitored the injected females for up to 18 months; some mice were euthanized earlier for analysis due to various health issues, including tumor development. Upon termination, we collected their ovaries, FTs, and uteri for histological analyses. In most injected females, we found at least one malignancy in either their uteri or ovaries and, to a lesser degree, in their FTs  coupled with the loss of either Rb1 or Brca1, the other was based on the Cre-mediated loss of Pten  coupled with several other oncogenic events  , in particular the serous adenocarcinoma [Rb1 knockout model from that used in a previous study (which developed serous ovarian cancer) [Ad-K8-Cre would mainly target mesothelial cells (including OSE cells and FT serosa lining cells), followed by FTE cells in the fimbria , and then FTE cells in the tubal region, as well as endometrial cells in the uterus (Our mouse models can be divided into two cohorts: one cohort was based on the Cre-induced loss of utation) . In the utation) , upper. utation) A, endomeutation) B, and leutation) C. A smalutation) D, and seutation) E. Immunoutation) . In thisarcinoma ,17,18,19 cancer) . Due to e uterus C, yet thAd-CMV-Cre) and FTE cells (based on the tamoxifen-induced activation of Ovgp1-iCreER) could serve as the cells-of-origin of endometrioid ovarian cancer [Ad-K8-Cre mainly targeted OSE cells —in particular, LGR5+ OSE stem cells  in the ovarian malignancies in the injected Pten/Kras mice ; the expAd-K8-Cre-injected mice, by recapitulating mutational events commonly found in human uterine and ovarian cancers. Our study is unique, as the genetic approach we used specifically targets the K8+ epithelial and mesothelial cells in the ovary, FT, and uterus. Our lineage-tracing experiments showed that the intrabursally injected Ad-K8-Cre not only targeted LGR5+ OSE stem cells but might also target long-lived stem cells in the FT epithelial and endometrial epithelial lineages, which are potential targets of transformation for their corresponding cancer types. The malignant phenotypes observed in various models possibly represent the unique interplay of different oncogenic events and various K8+ cell types in the ovary, FT, and uterus.In this study, we performed a comparative study of gynecological malignancies developed in the ovaries, FTs, and uteri of the + OSE cells) or FTE cells. Regardless of the cellular origin, the predominant cancer phenotype seems to be the endometrioid-like malignancy found in the ovary, suggesting that the activating KRAS mutant protein may dominantly dictate the malignant phenotype. Although we observed almost no malignancies in the uteri of these mice, we cannot rule out the possibility that such mice may also develop uterine malignancies, but after a longer latency . In almost all injected Pten/Pik3ca females, we observed aggressive angiosarcomas in their uteri after a very short latency; we also detected some angiosarcomas in the ovaries of the injected mice, possibly as a result of the metastatic spreading of angiosarcoma cells from the uterus to the ovary. This is the only exception in the Pten cohort in which the predominant malignancy was observed in the uterus , which may largely affect K8+ endometrial cells. Although we did not observe genetically marked endothelial cells in the uterus upon the intrabursal injection of Ad-K8-Cre, we cannot entirely rule out the possibility that the observed angiosarcoma may be derived from very rare endothelial cells targeted by Ad-K8-Cre.Collectively, we can draw several conclusions. First, oncogenic events—in particular, dominant acting oncoproteins —often dictate the malignant phenotypes in the ovary/reproductive tract. The cancer latencies driven by oncoproteins are much shorter than those from models induced by the inactivation of only tumor suppressors . In moste uterus . Since oKRAS, PTEN, and CTNNB1 [Ad-K8-Cre would mainly target OSE cells—in particular, LGR5+ OSE cells . The loss of p53 in K8+ endometrial cells leads to the development of various endometrial malignancies, possibly including poorly differentiated adenocarcinoma and sarcoma, whereas the loss of p53 in K8+ FTE cells may lead to the development of serous adenocarcinoma and endometrioid adenocarcinoma in the ovary. In contrast, Pten-loss may affect mesothelial cells  more than Müllerian-derived epithelial cells. Recently, by culturing FTE and OSE cells as organoids and by introducing the same sets of mutations , it was found that both cell types could serve as the cells-of-origin of high-grade serous ovarian carcinomas (HGSOCs); however, mutated FTE cells exhibited a shorter latency and higher penetrance of developing HGSOCs than similarly mutated OSE cells [Lastly, it appears that Müllerian-derived K8SE cells ,42. SincTP53 mutations can be either loss-of-function or gain-of-function, and individual TP53 hotspot mutations have different impacts on HGSOC patient outcomes [TP53 gain-of-function mutations would affect Müllerian-derived epithelial cells versus mesothelial cells in a similar or different way (when compared to the p53-loss from this work).The preferential development of gynecological malignancies in a particular organ in response to specific oncogenic mutations may be caused by both cell-intrinsic  and extrinsic  mechanisms. For instance, the loss of both p53 and BRCA1 can lead to DNA damage and replication stress ,44; Mülloutcomes . Thus, fOverall, our study provides comprehensive insights into how common oncogenic events determine both the types and locations of gynecological malignancies via their unique interactions with cellular origins and supports a model that oncogenic events largely dictate the types and locations of gynecological malignancies.


The effect of HIV infection on COVID-19 outcomes is unclear. Studies in South Africa  active TB, including patients taking anti-TB medication; or 4) underweight (body mass index [BMI] <18.5 kg/m2). HIV-positive patients who did not meet any of the conditions were considered to have controlled HIV infection.Severe COVID-19 was defined as having an oxygen saturation <90%, respiratory rate >30 breaths/minute, or a need for oxygen therapy.The three primary outcomes assessed in the study were 1) severe COVID-19 at admission; 2) severe COVID-19 during hospitalization; and 3) death. Mixed-effects logistic regression models were used to assess associations between exposure variables  and the two severe COVID-19 outcomes . Mixed-effects Cox proportional hazards regression models were used to examine time to COVID-19–associated death in relation to exposure variables. All models included a random-effects term for treatment center, and other covariates were sex, age, and number of underlying health conditions. Cox models were also adjusted for COVID-19 severity at admission. Similar mixed-effects logistic regression and mixed-effects Cox proportional hazards models were used to assess COVID-19 outcomes among HIV-positive persons stratified by HIV infection control status; covariates in these models included sex, age, and treatment center (random effects term). Data were analyzed using R . An alpha level of 0.05 was used to assess statistical significance. The study protocol was approved by the University of Zambia Biomedical Research Ethics Committee, reviewed by CDC, and conducted consistent with applicable federal law and CDC policy.Among 612 hospitalized patients who were eligible for the study, 443 (72%) had HIV status recorded. Among those patients, 122 (28%) were HIV-positive, and among the 102 HIV-positive persons who provided information on ART status, 91 (89%) were receiving ART . AlthougAge ≥60 years and having two or more underlying medical conditions were associated with severe COVID-19; however, HIV status alone was not associated with severe COVID-19 at admission or during hospitalization . SimilarHIV infection was not independently associated with worse outcomes among patients hospitalized for COVID-19 in Zambia. This finding is consistent with results from smaller studies among hospitalized patients in North America (The relationship between severe HIV disease and poor COVID-19 outcomes underscores the importance of Zambia’s progress toward ending the HIV epidemic and of efforts to maintain HIV services during the COVID-19 pandemic. As of June 2020, approximately 90% of an estimated 1.2 million HIV-positive Zambians were receiving ART, and nearly 90% of those patients were virally suppressed (The findings in this report are subject to at least three limitations. First, the small sample size might have contributed to the absence of a significant association between HIV status and COVID-19 outcomes. Whereas cohort studies with larger populations in South Africa (The findings from this study indicate that HIV-positive persons with severe HIV disease appear to be more likely to develop severe COVID-19 and die of COVID-19 than those with controlled HIV infections. In Zambia and other sub-Saharan African countries with high HIV prevalence and limited capacity to treat severe COVID-19, continued efforts to ensure that HIV-positive persons maintain control of their HIV infections through retention in care and adherence to ART and by addressing and managing their underlying medical conditions, could help limit COVID-19–associated morbidity and mortality and HIV-associated morbidity. Larger studies that include more robust data on CD4 counts and viral loads might provide a more nuanced picture of the potential impact of HIV disease status on COVID-19–associated morbidity and mortality.The effect of HIV infection on COVID-19 outcomes is unclear.HIV infection was not associated with poor outcomes among patients hospitalized for COVID-19 in Zambia. However, HIV-positive patients with severe HIV disease were more likely to develop severe COVID-19 or die of COVID-19.Ensuring that persons maintain HIV disease control, including by maintaining ART treatment continuity and adherence, achieving viral suppression, and addressing underlying medical conditions, could help reduce COVID-19–associated morbidity and mortality in sub-Saharan Africa.


Hyperactivation of immune responses resulting in excessive release of pro-inflammatory mediators in alveoli/lung structures is the principal pathological feature of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The cytokine hyperactivation in COVID-19 appears to be similar to those seen in rheumatoid arthritis (RA), an autoimmune disease. Emerging evidence conferred the severity and risk of COVID-19 to RA patients. Amid the evidence of musculoskeletal manifestations involving immune-inflammation-dependent mechanisms and cases of arthralgia and/or myalgia in COVID-19, crosstalk between COVID-19 and RA is often debated. The present article sheds light on the pathological crosstalk between COVID-19 and RA, the risk of RA patients in acquiring SARS-CoV-2 infection, and the aspects of SARS-CoV-2 infection in RA development. We also conferred whether RA can exacerbate COVID-19 outcomes based on available clinical readouts. The mechanistic overlapping in immune-inflammatory features in both COVID-19 and RA was discussed. We showed the emerging links of angiotensin-converting enzyme (ACE)-dependent and macrophage-mediated pathways in both diseases. Moreover, a detailed review of immediate challenges and key recommendations for anti-rheumatic drugs in the COVID-19 setting was presented for better clinical monitoring and management of RA patients. Taken together, the present article summarizes available knowledge on the emerging COVID-19 and RA crosstalk and their mechanistic overlaps, challenges, and therapeutic options. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection that caused coronavirus disease 2019 (COVID-19) usually produces a mild to moderate respiratory disease . EmerginIn general, there is a close association between viral infection and arthritis with a wide spectrum of symptoms ranging from arthralgia to arthritis. Earlier reports revealed that individuals infected with hepatitis C and several alphaviruses frequently develop prolonged arthritis; however, Parvovirus B19, Hepatitis B, and Rubella viruses frequently cause self-limited arthritis. In contrast, respiratory viruses, such as corona and influenza viruses more frequently can cause arthralgia and/or myalgia. Approximately 15 and 44% of COVID-19 patients present arthralgia and/or myalgia, respectively, during the infective stage ,4,5. HowEmerging evidence revealed that respiratory viral infections can increase the risk of autoimmune inflammatory arthritis, such as RA . In addiIn general, viruses can produce arthritis either through direct colonization at the joints or through aberrant immune-inflammation reactions produced during the host response to the infection. Earlier reports mentioned that respiratory viruses can be associated with RA development . MoreoveEmerging evidence revealed that patients with immune-mediated inflammatory diseases are more vulnerable to represent severe SARS-CoV-2 infections than that of the general population, which may arise due to their immune dysfunction and as a consequence of immunosuppressant therapy . AccumulOpenSAFELY, a health analytics platform holding healthcare records of 40% of patients in England revealed that the presence of rheumatic diseases slightly increases the risk of COVID-19 mortality as compared to the patients without these diseases . In a reUpon SARS-CoV-2 infection, infected host cells rapidly execute both innate and adaptive immune responses, which serve as the initial line of defense against COVID-19  Figure A. CD8+ cImmunologically, RA is characterized by dysfunctional innate immunity, adaptive immunity against “self”-antigens, and dysregulation in cytokine set-ups. CD4+ T cells contribute to the chronic autoimmune response of RA via antigenic activation of naive CD8+ T cells, which, in turn, triggers inflammation via massive production of pro-inflammatory mediators  Figure . TNF-α, Immune-inflammatory disorders can be associated with ACE/ACE2 imbalance . ACE propositive) alveolar macrophages is substantially reduced, and thus gas exchange is compromised . In. Inposity joints  [53]. Boectively . Taken tPatients with RA generally represent a compromised immune system, which makes them susceptible to SARS-CoV-2 infection . TreatmeDespite this, no direct association has been established between specific RA medication and the COVID-19 development or outcomes, and some reports claimed that RA patients exhibit an increased risk of serious infections . AccumulSome reports claimed that the use of NSAIDs does not produce any serious adverse manifestation in COVID-19 patients  Table 1Table 1. Hydroxychloroquine and chloroquine are commonly used as csDMARDs directed for the treatment of RA. Both these antimalarial drugs justify the theoretical requirements to be effective against COVID-19 . Thus, tConsidering the mechanistic similarity between RA and COVID-19 disease pathogenesis, it has been postulated that bDMARDs would be effective in the COVID-19 setting. However, the effect of bDMARDs in the COVID-19 setting remains highly controversial . AccordiIn the ongoing COVID-19 pandemic, the monitoring of RA patients is a significant challenge for rheumatologists. Patients with RA are known to be more susceptible to a multitude of infections, which advises against physically visiting the physicians on a routine basis during the COVID-19 setting. The COVID-19 lockdown also aids in this issue. Thus, in the absence of routine clinical assessment, it is really a challenging task for the rheumatologists to follow effective disease control protocol to alleviate disease activity. So, the situation forced rheumatologists to develop effective strategies to provide optimum patient care. Recent reports showed that telemedicine is gaining popularity in this situation . It alloTelephonic consultations supported by supplemental information, such as laboratory tests and photos of suspected manifestation areas, have also been found to be fruitful to avoid physical visits ,98. In tThe clinical features of immune-inflammatory activities in SARS-CoV-2-infected alveolar structures share a pathological resemblance with the immunoreactive activities in the joints of RA patients. The establishment of localized acute inflammation mediated through excessive release of pro-inflammatory mediators is the hallmark of disease pathogenesis in both cases. Mechanistically, dysfunctional immune response endorses a hyperinflammatory state in alveolar tissue following SARS-CoV-2 infection referred to as a “cytokine storm.” In the cytokine-enriched environment, SARS-CoV-2 induces pyroptosis of lymphocytes, which results in the decline in memory Th cells and regulatory T lymphocytes. In addition, SARS-CoV-2 recruits APCs to trigger pathogenic Th17 cell activation, which induces neutrophilic inflammation and suppresses adaptive immune responses by activating neutrophils. In a “cytokine storm microenvironment,” CD4+ T cells recruit pathogenic Th1 cells, which aid in COVID-19 pathogenesis via macrophage activation. Immunologically, immune dysfunction against self”-antigens, as well as cytokine dysregulation, are hallmarks of RA. APC endorses Th2 and Th17 cell activation in the lymph node. CD4+ T cells in association with naive CD8+ T cells induce chronic autoimmune response and elicit inflammation via endorsing Th1/Th17 activation in synovial tissue. The activated Th1/IL-17 axis elicits the production of pro-inflammatory mediators, activates immune cells, and endorses B lymphocyte differentiation to produce autoantibodies in synovial tissue. In synovial fibroblasts, Th17 triggers the production of IL-17, which further promotes osteoclast development by recruiting pro-inflammatory cytokines, VEGF, RANKL, GM-CSF, and MMPs. Thus, the aberrant immune-inflammatory response resulting in hyperactivation of the cytokine–chemokine axis plays a crucial role in the pathogenesis of both COVID-19 and RA. With the emerging evidence that both RA and COVID-19 share similar pathological mechanisms in the affected tissues, it has been aimed to decipher the mechanistic overlapping between COVID-19 and RA immune-inflammatory features. Both COVID-19 and RA share common mechanistic pathways of pathogenesis mediated through aberrant ACE/ACE2 activities, as well as being driven by the activities of analogous macrophage clusters. The viral entry to the host cells depends on ACE2 binding of the spike protein of SARS-CoV-2 resulting in a suppression of ACE2 protein expression. Suppression of ACE2 and activation of ACE in alveolar tissues and joints share an identical mechanistic pathway of disease pathogenesis in both COVID-19 and RA, respectively. In addition, the alveolar macrophages in COVID-19 patients are homologous to that of the macrophages in joints of RA patients as seen with the macrophages in healthy alveolar tissue and joints, which strongly suggests that both COVID-19 and RA share similar mechanistic pathways of macrophage-mediated disease pathogenesis.Towards effective therapeutic management, the use of anti-rheumatic drugs, such as glucocorticoids, NSAIDs, csDMARDs, bDMARDs, and tsDMARDs was critically reviewed along with their usefulness and contraindications in the COVID-19 setting. Although several anti-rheumatic drugs exhibited promise in certain clinical settings, careful investigation is obligatory to achieve their precise therapeutic utility in SARS-CoV-2-infected RA patients. Recognition of the immune-inflammatory mechanism of disease pathogenesis in both the diseases and the need for anti-rheumatic and anti-inflammatory drugs was largely underlined. Given the fact that several anti-rheumatic drugs do not influence COVID-19 severity/risk, RA patients may continue taking anti-rheumatic drugs during the pandemic. However, advice to RA patients on whether to stop or continue anti-rheumatic drugs requires careful testing of all disease-related parameters including severity, age, and comorbidities. In this line, we identified the immediate challenges and forwarded key recommendations by different professional rheumatology associations regarding the use of anti-rheumatic drugs in the COVID-19 setting for better clinical management of RA patients. Finally, routine monitoring of RA patients in the COVID-19 pandemic and the emerging prospects of telemedicine and virtual consultation were discussed.Conclusively, COVID-19 and RA share similar immune-inflammatory features of disease pathogenesis executed by analogous mechanistic pathways. However, the treatment of RA patients in the COVID-19 setting itself stands as a challenging task. Implementation of individualized clinical surveillance of RA patients considering the disease severity and appropriate risk-benefit study referring to the recommendations of using anti-rheumatic drugs in the COVID-19 setting by different professional rheumatology associations would stand as the optimal therapeutic strategy for effective disease control during the COVID-19 pandemic. Finally, it is advisable to use virtual consultation by the patients with stable RA activity during this pandemic era, while the patients with RA flares are recommended to take all precautionary measures during visiting the clinics to prevent acquiring/spreading SARS-CoV-2 infection.


Microscopic electric fields govern the majority of elementary excitations in condensed matter and drive electronics at frequencies approaching the Terahertz (THz) regime. However, only few imaging schemes are able to resolve sub-wavelength fields in the THz range, such as scanning-probe techniques, electro-optic sampling, and ultrafast electron microscopy. Still, intrinsic constraints on sample geometry, acquisition speed and field strength limit their applicability. Here, we harness the quantum-confined Stark-effect to encode ultrafast electric near-fields into colloidal quantum dot luminescence. Our approach, termed Quantum-probe Field Microscopy (QFIM), combines far-field imaging of visible photons with phase-resolved sampling of electric waveforms. By capturing ultrafast movies, we spatio-temporally resolve a Terahertz resonance inside a bowtie antenna and unveil the propagation of a Terahertz waveguide excitation deeply in the sub-wavelength regime. The demonstrated QFIM approach is compatible with strong-field excitation and sub-micrometer resolution—introducing a direct route towards ultrafast field imaging of complex nanodevices in-operando. Novel Quantum-probe Field Microscopy (QFIM) captures ultrafast movies of Terahertz electric waveforms inside microstructures using fluorescent quantum dots. Today, electric waveforms can coherently be sampled with ultrashort laser pulses4 to directly access the temporal signatures of charge motion and quasi-particle excitations in condensed matter systems up to the visible spectrum5. Yet, relevant field distributions are often confined to microscopic scales significantly below the diffraction limit—arising from inhomogeneity of materials, microstructures or intrinsic confinement of light-matter excitations8. Only a few approaches spatially resolve local electric near-field waveforms up to multi-Terahertz frequencies, including raster-scanned photoconductive switches and electro-optic microscopy13. Enhanced resolution is provided by scattering near-field optical microscopy17, THz-driven scanning tunneling microscopy19 and recently emerging ultrafast electron microscopy22. THz-induced visible luminescence has been employed for imaging spatial field distributions via temporally cumulated effects of strong local fields26. Sampling THz electric waveforms in the time-domain using visible fluorescence appears highly desirable as it bears numerous prospects including the access to nanoscopic scales, 3D geometries, high-speed acquisition, and compatibility with strong local fields inside active and nonlinear-driven devices30.The detection of radiation—including human vision—is typically sensitive to the energy carried by an electromagnetic wave rather than its fields. Heinrich Hertz succeeded to prove the existence of electromagnetic fields by conversion into incoherent visible fluorescence33, encoding electric near-fields into far-field luminescence modulations via variations of photo-absorption, illustrated in Fig. 35. Harnessing this mechanism, we perform spatially resolved time-domain spectroscopy, and demonstrate the imaging capabilities by resolving the ultrafast electric waveforms of (a) the localized THz resonance of a bowtie antenna and (b) the propagating THz gap excitation inside a micro-slit waveguide. Akin to plasmonics in the visible and near-infrared spectrum, these highly localized excitations arise from collective oscillations of the electron plasma constrained by sub-wavelength geometries.Here, we demonstrate ultrafast far-field imaging of THz electric near-fields using fluorescence microscopy. We capture visible photons from local quantum dot probes and acquire stroboscopic movies of electric near-field evolutions. The scheme employs the quantum-confined Stark effect (QCSE)37, are deposited as a homogeneous layer of quantum-probes via drop-casting. Luminescence is excited via wide-field illumination in the image plane of a fluorescence microscope with ~150 fs pulses at wavelengths around 500 nm. We acquire differential images of the emission yield with a CCD camera in the presence and absence of THz excitation. The difference signal, which we refer to as the QFIM signal SQFIM in the following, represents the crucial observable for instant local fields.Our experiments are based on two-color excitation using single-cycle Terahertz pulses to drive phase-stable near-fields and visible fs-pulses to excite the quantum dot probes, see Fig. τ = 30 fs —, we simulate the local near-field and the resulting QFIM signal using a finite-element time-domain simulation of the structure and find close agreement with the experimental QFIM trace, see Fig. Analyzing the QFIM signal inside the gap, we demonstrate the extraction of local electric waveforms and characterize the temporal response of the bowtie antenna. As a prerequisite, we study the relation between the maximum field strength 32, i.e., the QCSE in semiconductor nanocrystals33. The altered electron and hole wavefunctions induce a quasi-instantaneous change of the optical transition dipole moment. As a result, the photoabsorption may be reduced or enhanced depending on the visible excitation frequency and the accessed electronic states, as previously resolved via transient absorption spectroscopy35. We spatially map these changes via luminescence emission microscopy. Specifically, we note that irrespective of much longer luminescence lifetimes (~10 ns), the temporal sampling resolution is exclusively governed by the ultrafast absorption process. This quasi-instantaneous absorption can alternatively be accessed via transient absorption imaging of the antenna, as shown, e.g., for Δτ = 0 fs in Fig. The underlying mechanism enabling the QFIM scheme relies on THz-driven modulations of the electronic band structure in low-dimensional quantum systemsx, Δτ) in Fig. cprop below c0 emerging from the left edge of the structure. Such propagating plasmonic excitations are confined inside a subwavelength slit and provide the basis for ultrafast circuits—enabling the routing, nanofocusing, and enhancement of infrared radiation42. We corroborate our finding with a time-domain electromagnetic simulation of the ultrafast interaction , yielding the launching of a THz wavepacket from the edge with a propagation velocity cprop  in Fig. cprop ~ c0/2. Moreover, we also reproduce the experimentally observed interference of the direct and the propagating pulses. We attribute the different propagation lengths of experiment and simulation to the idealized homogeneous microstructure assumed in the model43. Furthermore, the simulation yields a second gap excitation at the opposite side of the THz waveguide. We experimentally resolve this feature in a QFIM measurement acquired at the right side of the waveguide in Fig. Now, we demonstrate the field-resolved tracking of propagating ultrafast THz excitations using the QFIM scheme. Specifically, we spatio-temporally resolve a THz wavepacket traveling along the subwavelength slit of a gold waveguide, as depicted in Fig. 28. Moreover, we observe THz propagation inside a gap deeply in the sub-wavelength regime and, thus, introduce the ultrafast sampling of propagating electric fields inside confined structures in the time domain. These results motivate the application of QFIM for imaging electric waveforms of surface excitations, including THz phonon and plasmon polaritons on bulk surfaces and 2D heterostructures45. In contrast to near-field scattering microscopy based on nanotips, our scheme is compatible with strong driving fields and we envision unprecedented insights to THz-driven nonlinear dynamics, such as interactions between polaritonic wavepackets29. Finally, we highlight the prospect of QFIM for imaging THz fields at the nanoscale using optical super-resolution microscopy46, paving a promising way towards ultrafast nanoscopy of strong electric fields inside nonlinearly driven nanosystems.We introduce Quantum-probe Field Microscopy to image ultrafast electric near-field waveforms in the time-domain. Our approach utilizes the encoding of momentary THz-fields onto the visible emission of nanocrystals and far-field fluorescence imaging. The underlying THz field-driven and quasi-instantaneous QCSE provides a direct link between the luminescence observable and the local electric fields. On this basis, we demonstrate the time-resolved microscopy of near-field waveforms inside a single bowtie antenna—a building block of ultrahigh-frequency devices, metamaterials, and strong-field light-matter interaction experiments47 in a MgO:LiNbO3 crystal using pulses from an amplified 10 kHz Yb-laser system , see Fig. Sτ between THz pump pulses and visible excitation pulses via a mechanical delay stage.We generate high-field single-cycle THz pulses by the tilted pulse front method49. For the propagating THz waveguide excitation, we employ a model consisting of two conducting metal bars  on a soda lime glass substrate. We excite the structures using a plane wave single-cycle THz pulse .We employ a finite element solver (COMSOL Multiphysics) to calculate the electric near-fields of the structures. The model for the bowtie resonator consists of the gold antenna on a soda lime glass substrate.Details on the fabrication of gold microstructures, the synthesis of CdSe-CdS quantum dots and the polarization dependence of the bowtie antenna are presented in the Supplementary InformationSupplementary InformationQFIM Movie of the THz bowtie antenna


Spleen Tyrosine Kinase (SYK) is a cytosolic, non-receptor tyrosine kinase with an imperative role in immune and non-immune processes. Recently, we identified six gain-of-function SYK variants in patients that presented multi-organ inflammation and immune dysregulation. The SYK variants displayed constitutive SYK phosphorylation in human embryonic kidney (HEK) 293T, colonic epithelial cells (SW480), and in knock-in heterozygous SYK mice. These observations mark SYK as a therapeutic target for autoimmune diseases.Phenotype drug discovery accelerates this process and can be done successfully with an appropriate phenotype. A possible phenotype displayed by SYK variants is SYK phosphorylation, as high-throughput screening can identify hit compounds that reduce the constitutive activation of phosphorylated SYK (p-SYK).SYK S550Y variant in HEK293T cells.Aim 1: Determine the screening phenotype with wildtype (WT) and  Recently, we observed increased phosphorylation in gain-of-function SYK variants We hypothesize that we can use phosphorylated-SYK (p-SYK) levels to identify hit compounds that can decrease the kinase activity in these variants. With stable transfected SYK WT and SYK S550Y HEK293T cell-line, protein analyses will be completed to characterize the appropriate screening phenotype.Establish an assay for high-throughput drug screening. We will utilize homogenous time-resolved fluorescence (HTRF) assay. The signal measured from HTRF is positively proportional to the level of p-SYK; therefore, we expect that S550Y cells will have a higher signal than the WT.Validate hit compounds in HEK293T and zebrafish. We will create a dose-response curve with the hit compounds in in vitro and in vivo models.We will use stable transfection to established overexpressing SYK WT and S550Y HEK293T cells. We will apply homogenous time-resolved fluorescence (HTRF) to quantify p-SYK levels during the drug screening.Protein analyses have verified high expression of p-SYK in stable transfected HEK293T cells. No stimulation was required, as the cells showed an increased phosphorylation level at baseline. Downstream signaling partners such as p-ERK and p-JNK of the MAPK pathway displayed an upregulation. This suggests that the sustained activation of p-SYK may consequently affect cellular processes and contribute to the clinical manifestations observed in patients.This research study will identify hit compounds that can produce a safe and effective biological response in pediatric patients with gain-of-function SYK variants. Personalizing medicine throughout high-throughput drug screening can accelerate drug repurposing for pediatric patients with multiple systemic diseases and immune dysregulation.None


Surveillance of nosocomial infections, like catheter-associated urinary tract infection (CAUTI), central line-associated bloodstream infection, possible ventilator-associated pneumonia and secondary bloodstream infections were observed to study the impact of COVID-19 outbreak in ICUs from Tan Tock Seng Hospital and National Centre for Infectious Diseases, Singapore between February and June 2020. Higher nosocomial infection rates were observed in COVID-19 patients, although it was not statistically significant. Moreover, COVID-19 patients seem to be more predisposed to CAUTI despite a higher proportion of non-COVID-19 patients having urinary catheters. Thus, continued vigilance to ensure adherence to IPC measures is needed.The online version contains supplementary material available at 10.1186/s13756-021-00988-7. With the COVID-19 pandemic continuing globally, the prevention of nosocomial infections is more crucial than ever as secondary nosocomial infections may increase the morbidity and mortality of COVID-19 patients and have been recommended as part of the clinical outcomes to measure for COVID-19 . While lHence, there is a need to obtain robust data based on established surveillance methods to compare the incidence of nosocomial infections between COVID-19 and non-COVID-19 patients. As part of the outbreak response, we conducted a prospective surveillance for device-associated infections (DAI) and secondary nosocomial bacteraemia in intensive care unit (ICU) using National Healthcare Safety Network (NHSN) criteria. We report the findings from the surveillance in this report.We conducted prospective surveillance at the National Centre for Infectious Diseases (NCID), a 330-bedded purpose-built outbreak response facility with 38 ICU beds, and at Tan Tock Seng Hospital (TTSH), a 1700-bedded acute hospital with 72 ICU beds. Outbreak ICUs (n = 2) and medical ICUs wards (n = 2) were included in this surveillance. The surveillance was conducted from 1st February to 30th June 2020 during COVID-19 epidemic in Singapore. Data were extracted from electronic medical records using Research Electronic Data Capture (REDCap) software hosted at National Healthcare Group, Singapore  and 7.04 per 1000 ICU-days (95% CI 4.09–12.12)  potentially due to longer duration of indwelling urinary catheter-days despite a higher proportion of non-COVID-19 patients having urinary catheters. Moreover, our study also reflected a relatively low ICU nosocomial infection (8.5%) compared to other studies , 10, 11,Additionally, on top of having invasive devices, critically ill COVID-19 patients may have increased susceptibility to nosocomial infections due to lymphopenia and reduced immune functions . StudiesFurthermore, the relatively stable nosocomial infection rate in non-COVID-19 patients during the study could also be attributed to heightened infection prevention and control practices during the COVID-19 outbreak. Enhanced precautions, such as improved hand hygiene practices decreases the transmission of nosocomial infections between patients in the ICU. However, changes in care practices such as minimizing contact with suspected or confirmed COVID-19 patients and rostering of available manpower could possibly affect nosocomial infection rates, such as CAUTI in COVID-19 patients as opposed to non-COVID-19 patients. All ICUs in TTSH and NCID are also protocolled to nurse patients in the semirecumbent position unless contraindicated, which reduces the risks of PVAP infection in both patients’ group. Additionally, COVID-19 patients were placed in prone position when medically required. Thus, longer length of stay, use of invasive devices, and reduced immune functions could be potential reasons which resulted in a higher nosocomial infection rate in COVID-19 patients compared to non-COVID-19 patients , 14.Our study has several limitations. First, the small number of nosocomial infections makes it difficult to analyse the risk factors for nosocomial infections and include device-days into our model. Second, we did not audit the adherence to process measures that were in place to prevent nosocomial infections. Hence, we were unable to identify the reasons for CAUTI being the main device-associated infection in COVID-19 patients.In conclusion, although the incidence of nosocomial infection was not significantly affected by COVID-19 in our centre, continued vigilance to ensure adherence to IPC measures is needed.Additional file 1. Additional figures on recruitment flowchart and monthly nosocomial infection rates; Data collection form.


Early detection of SARS-CoV-2 infection is critical to reduce asymptomatic and pre-symptomatic transmission, curb the spread of variants by travelers, and maximize treatment efficacy. Low-sensitivity nasal-swab testing (antigen and some nucleic-acid-amplification tests) is commonly used for surveillance and symptomatic testing, but the ability of low-sensitivity nasal-swab tests to detect the earliest stages of infection has not been established. In this case-ascertained study, initially-SARS-CoV-2-negative household contacts of individuals diagnosed with COVID-19 prospectively self-collected paired anterior-nares nasal-swab and saliva samples twice daily for viral-load quantification by high-sensitivity RT-qPCR and digital-RT-PCR assays. We captured viral-load profiles from the incidence of infection for seven individuals and compared diagnostic sensitivities between respiratory sites. Among unvaccinated persons, high-sensitivity saliva testing detected infection up to 4.5 days before viral loads in nasal swabs reached the limit of detection of low-sensitivity nasal-swab tests. For most participants, nasal swabs reached higher peak viral loads than saliva, but were undetectable or at lower loads during the first few days of infection. High-sensitivity saliva testing was most reliable for earliest detection. Our study illustrates the value of acquiring early (within hours after a negative high-sensitivity test) viral-load profiles to guide the appropriate analytical sensitivity and respiratory site for detecting earliest infections. Such data are challenging to acquire but critical to design optimal testing strategies in the current pandemic and will be required for responding to future viral pandemics. As new variants and viruses emerge, up-to-date data on viral kinetics are necessary to adjust testing strategies for reliable early detection of infections. Early detection enables individuals to self-isolate sooner, reducing transmission within households and local communities, and to vulnerable populations, including individuals hospitalized for non-COVID-19 illnesses and individuals at high risk for severe disease due to multiple medical comorbidities . Low-sensitivity nasal-swab tests are commonly used for SARS-CoV-2 detection and symptomatic testing.2 As new variants-of-concern emerge, e.g. the Delta variant with increased transmissibility,5 high viral loads,6 and outbreaks with large numbers of breakthrough infections,7 it is clear that testing strategies  need to be adjusted to diagnose infections earlier.Early detection of SARS-CoV-2 infection is needed to reduce asymptomatic and pre-symptomatic transmission, including the introduction and spread of new viral variants from travelers. More than half of transmission eventsAlthough national vaccination efforts are reducing severe COVID-19 outcomes in the U.S., a sizable portion of the world’s population is likely to remain unvaccinated due to limited vaccine availability, medical ineligibility , or personal preference. Thus, testing remains an important tool for preventing outbreaks among children in schools and daycare facilities (where children under age 2 cannot wear masks), which may spread to the community and increase rates of infection among high-risk and unvaccinated individuals. Tests that detect early infections are also important to prevent viral transmission in congregate settings with high-risk or unvaccinated populations, such as hospitals, college dormitories, homeless shelters, correctional facilities, summer camps for children, elementary schools, and long-term care facilities.8 Results of the ACTT-1 trial demonstrated a survival benefit in patients for whom Remdesivir was initiated in the early stages of treatment , but that benefit was lost once disease progressed, and advanced respiratory support was needed.10 Convalescent plasma failed to show efficacy in a study where the median time to entry in the study was 8 days after symptom onset11 but demonstrated protection against progression to respiratory failure when given to individuals of advanced age earlier in the course of the illness.12 Similarly, the use of anti-SARS-CoV-2 monoclonal antibody therapy (bamlanivimab or casirivimab plus imdevimab) did not show benefit over placebo in a cohort of hospitalized patients.13 However, when given to outpatients with mild or moderate COVID-19, who may have otherwise progressed to hospitalization later in the course of illness, reductions in emergency room or medical visit rates and more rapid declines in viral load16 have been observed. Further, a greater effect was observed among the subgroup of patients who had not yet developed a detectable endogenous antibody response.15Beyond outbreak prevention and control, early detection of COVID-19 may also be useful for individual patient care, as high-risk patients who are identified early can be monitored and treatment initiated swiftly if it becomes appropriate. Several treatments show exclusive or increased efficacy only when given early in the infection. The advantage of earlier treatment initiation is likely due to reduction of viral replication either directly or by promotion of an early effective immune response, which prevents a later exaggerated inflammatory response.However, it is currently unclear which testing strategy can detect SARS-CoV-2 infection at the earliest stages. Does one need a high-sensitivity test, or would a low-sensitivity test suffice? Which sample type should one use?17 High-sensitivity tests have LOD values equivalent to ~102 to 103 copies/mL of sample, whereas low-sensitivity tests have LOD values equivalent to ~105 to 107 copies/mL. Therefore, to choose the appropriate test for reliable early detection, one needs to measure viral loads present in samples collected early in the course of infection,18 and then choose a test with an LOD below that viral load. Initial data by us19 and others21 show that, at least in some humans, SARS-CoV-2 viral load can be low  early in infection, therefore only high-sensitivity tests would reliably detect infection.Tests with high analytical sensitivity can detect low levels of molecular components of the virus (e.g. RNA or proteins), in a sample. Analytical sensitivity is described by the limit of detection (LOD) of a test . The lower the LOD, the higher the analytical sensitivity of the assay. LOD of SARS-CoV-2 diagnostic tests are described in various units; the most directly comparable among tests are units that report the number of viruses  or viral RNA copies per milliliter of sample. Viral RNA copies/mL are roughly equivalent to genome copy equivalents/mL (GCE/mL) or nucleic acid detectable units/mL (NDU/mL). These LOD values are tabulated by the U.S. Food & Drug Administration (FDA).22 which have occasionally been linked to viral tropism. For example, the cellular receptor for entry of MERS-CoV is expressed nearly exclusively in the lower respiratory tract, prompting recommendations for diagnostic testing of specific sample types .23 A previous study on SARS-CoV found high levels of viral RNA in saliva and throat wash early in the infection course (before the development of lung lesions), to suggest saliva as a promising sample type for early detection.24 Although nasopharyngeal (NP) swab is often considered the gold standard for SARS-CoV-2 detection, it requires collection by a healthcare worker and is not well tolerated. Furthermore, the performance of NP swabs for early detection of current SARS-CoV-2 variants is not known. Other sample types, such as nasal (anterior-nares or mid-turbinate) swabs28 and saliva32 are more practical, especially for repeated sampling in serial surveillance testing .Sampling site or specimen type may also be critical to early detection. Other respiratory viruses have been shown to have detection rates that vary by sampling site,36 and had higher viral loads,34 whereas others concluded that testing performance in different locations of the respiratory tract is similar.43 Some studies have observed detection of SARS-CoV-2 in saliva before nasal swabs, or in saliva but not in nasal swabs;45 one study of an emerging variant (B.1.616) showed poor detectability of SARS-CoV-2 in NP swabs.46 It is not known whether NP is the best respiratory site for currently circulating variants and emerging variants.Studies comparing paired samples (collected from different locations in the respiratory tract) from the same individual are inconsistent in their findings of which sample type had the better sensitivity. Some studies concluded that nasal swabs outperform saliva/oral fluid49 most have collected dry-swabs or saliva in sterile collection vessels;57 without an RNA-stabilizing buffer, introducing risk of viral degradation during transport and handling, which will affect detection and quantification. Most studies that compared multiple respiratory sites for SARS-CoV-2 detection selected individuals already known to be positive for SARS-CoV-2, thus missing the very earliest detectable loads and also not having context for how far along the course of infection that individual might have been. An excellent study comparing nasal swabs and saliva sampling early in the infection among adults at a university58 suggested that high-sensitivity testing is needed for early detection; by leveraging university saliva surveillance testing and enrolling close contacts, the researchers reported longitudinal viral kinetics data from 60 participants, 3 of whom (based on our interpretation of the study) were negative in both sample types upon enrollment, allowing for definitive quantification of the earliest day(s) of infection. The thorough work done here shows both how important it is to obtain early samples, but also how difficult it is to capture samples from which to assess the earliest days of infection.There are several possible explanations for these inconsistencies in respiratory sampling site. Most studies comparing clinical sensitivity of different respiratory sites for SARS-CoV-2 detection focused only on viral detection, not viral-load quantification, which is needed to infer whether detection would have been achieved by assays with different LODs. Although a few studies collected samples in RNA-stabilizing buffers,64 laboratory diagnosis ,65 or peak viral load,58 but these measures can be highly variable among people. Misalignment of illness stage may confound comparisons of sample type sensitivity or viral loads throughout the course of infection. Despite the urgency of defining optimal diagnostic strategies to contain further outbreaks (and spread of variants-of-concern), there is a lack of quantitative data on longitudinal SARS-CoV-2 viral load in paired sample types with sample collection starting prior to earliest detectable viral loads.Negative samples preceding the first positive result are needed confirm with high resolution the true starting point of longitudinal measurements on viral load. In order to compare diagnostic performance at different stages of the infection, studies with longitudinal data often align the comparisons to an infection time point—typically days relative to symptom onset,19 we enrolled individuals from Los Angeles County, California, ages 6 and older who had recently tested positive (household index case), and their exposed household contacts at risk of infection. All participants self-collected saliva and anterior-nares nasal swabs twice daily, in the morning upon waking and before bed. Importantly, all samples were immediately placed in a guanidinium-based inactivating solution (see N1 and N2 gene positivity using a high-sensitivity assay and if a transmission event was observed (a previously SARS-CoV-2 negative participant tested positive in at least one sample type), we quantified viral loads in all samples  prospectively collected from that participant for at least two weeks from their first positive. Quantification was performed via quantitative reverse-transcription PCR (RT-qPCR), with a subset of measurements validated by reverse-transcription droplet digital PCR (RT-ddPCR), capturing the early and full course of acute SARS-CoV-2 infection with high sensitivity.To understand the required test sensitivity and the optimal sample type for earliest SARS-CoV-2 detection, we designed a case-ascertained study of household transmission with high-frequency sampling of both saliva and anterior-nares nasal swabs. Building on our earlier work,tion see  that pre66 and a RT-ddPCR assay developed by Bio-Rad.67 Both of these assays received an emergency use authorization (EUA) for qualitative, but not quantitative, detection of SARS-CoV-2. In initial testing, when combined with standard KingFisher MagMax sample preparation protocols, these assays performed well to quantify heat-inactivated SARS-CoV-2 viral particles spiked into commercially available SARS-CoV-2 negative saliva and nasal fluid from pooled donors. However, they did not provide reliable quantification when we analyzed individual saliva samples freshly collected from positive participants in this study. Carryover of materials from some of the mucus-rich samples was inhibitory, as determined by RT-ddPCR analysis of dilutions of eluted RNA (data not shown). We optimized the extraction and each quantitative assay protocol ocol see  to obtaiocol see , Fig. S1We cross-validated our quantification methods in two steps. First, we used commercial, heat-inactivated SARS-CoV-2 viral particles to establish calibration curves for both saliva and swab samples to convert RT-qPCR quantification cycle values  to viral load. Input particle concentrations for each point on the curve were calculated based on the stock quantification reported on the certificate of analysis for each lot of particles. We could not extend the calibration curve to very high viral loads because of the limited concentration of viral particle stock; so, to confirm performance at high viral loads, we quantified 42 swab and 63 saliva samples from SARS-CoV-2-positive participants with both RT-qPCR and RT-ddPCR methods. We observed excellent concordance between the calibration curve Data in , RT-qPCRNext, to quantify viral load at the earliest stage of infection, we analyzed the viral loads in the saliva and nasal swabs of participants who were negative in both sample types upon enrollment and became positive during their participation in the study . We exteRNase P Cq values remained consistent throughout the collection period for both saliva and nasal swabs for most of the participants , while the nasal swab remained negative, and days before the participant reported any symptoms. As measured, viral load in nasal-swab samples reached the level of LOD of low-sensitivity tests 1.5 days after the first saliva positive samples (pink triangle). This same pattern of earlier detection in high-sensitivity saliva was observed in five of the other six participants: high-sensitivity saliva was 2.5 days earlier (3–104) of SARS-CoV-2 RNA in saliva for 4 days while nasal swabs remained negative by high-sensitivity measurements. The nasal viral load spiked above 1010 copies/mL. Even after spiking to high viral load in nasal swab, her only symptoms were mild congestion/runny nose. Even with high-sensitivity nasal swab testing, only one participant tested positive in nasal swab before saliva . In the first participant, , detecti earlier , 3.5 day earlier , 6 days  earlier , 4.5 day earlier , and 2.5 earlier . Even co earlier  and from earlier . The max earlier . This pae saliva . In thise saliva , Fig. S4RNase P Cq values (indicating low concentration of the human control target); and variability of RNase P Cq values across the nasal-swab samples suggests that inconsistent swab-sampling quality could have impacted these participants’ viral load data, and should be taken into account when interpreting those data. These two participants  detected the infection 6 days before viral loads reached the lower range of the LODs of low-sensitivity tests (pink triangle) for this participant. Recent data from individuals infected by the Delta variant suggest viral loads in breakthrough infections are not impacted by vaccination status.72The fifth participant  had rece8 viral copies/mL (N1 gene target) while SARS-CoV-2 RNA remained undetectable in nasal swab, even by the high-sensitivity assay used here. This contrast between high and likely infectious viral load in saliva73 at the same time point as a negative nasal swab emphasizes the need for careful choice of sampling site and test sensitivity in the early stages of SARS-CoV-2 infection to minimize transmission.The final participant  with medCompiled data from all seven participants highlights the non-trivial interplay of anatomical sampling site, infection stage (early vs late), and diagnostic test sensitivity . Partici36Next, we plotted viral loads in each respiratory site starting from the first positive test . Paired 74 We considered the positivity rate of high- or low- sensitivity testing methods with each sample type during the first ten days of test-positive infection, separating into categories of no symptoms or symptomatic if the participant reported at least one COVID-19-like symptom  is not authorized (at the time of this writing) for the sample collection of nasal swabs. Third, we have paired data for saliva and anterior nares nasal swabs but do not compare nasopharyngeal (NP) swabs, sputum, or other lower-respiratory specimens. We do not know whether other sampling sites, such as nasopharyngeal swabs or oropharyngeal swabs, would have provided earlier or later detection than saliva. As mentioned above, parallel sampling of multiple respiratory sites should be done as new variants emerge. Fourth, we do not have data for low-sensitivity tests or any antigen tests, and are inferring ability to pick up infections based on the quantified viral load in the participant samples and the LODs reported by the FDA for the diagnostic platforms. Fifth, our investigation of SARS-CoV-2 RNA stability in each sample type  in the inactivating buffer at 4 °C during storage suggests some degradation may have occurred in some samples, and revealed subtle differences between degradation in saliva and nasal swabs . See SupBy rapidly enrolling household members at high risk for contracting COVID-19 and having them self-sample and report symptoms twice daily in paired respiratory sites, we were able to observe patterns in SARS-CoV-2 viral load in the earliest days of infection. All seven participants tested negative by both sample types  upon enrollment, ensuring we captured the earliest detectable SARS-CoV-2 viral load (within 12 hours) in both sample types. Our dataset helps inform diagnostic testing strategies by showing differences in viral loads in paired nasal swabs and saliva samples at high temporal resolution (twice daily) during the early days and pre-symptomatic phases of infection.First, choosing the correct respiratory sampling site is critical for earliest detection of SARS-CoV-2 infection. In our study, alignment of longitudinal data to the first day of positivity clearly shows the superiority of high-sensitivity saliva testing for detection in the first 5.5 days of infection , Fig. S536 and others showing saliva  has equivalent or better detection to nasal-swabs.45 Through longitudinal rather than cross-sectional sampling, we show the relative viral loads in each respiratory site is a factor of infection stage  viral load in saliva samples while the paired nasal swab was either negative (3 copies/mL) viral load  to substantially less sensitive . FDA’s NDU/mL is approximately equivalent to the copy/mL scale used in this paper. The low-sensitivity end of this RT-qPCR sensitivity range  overlaps with the range of low-sensitivity rapid isothermal nucleic-acid tests  and approaches the analytical sensitivity range of antigen tests. Therefore, to achieve early detection, tests with high sensitivity rather than tests of a particular type should be chosen. With many strategies for asymptomatic screening/surveillance testing in use, it is critically important to consider whether the LODs of the tests would be able to detect early infection, and to prompt actions that minimizes transmission.Fourth, using a diagnostic test with high analytical sensitivity , rather Fifth, our data show the utility of combining knowledge of the appropriate respiratory site and the appropriate test analytical sensitivity for achieving earliest detection. Among our unvaccinated participants, when a high-sensitivity test was combined with saliva as a sample type, SARS-CoV-2 infection was detected up to 4.5 days before viral loads in nasal swabs reached the LODs of low-sensitivity tests . AlthougWe made five conclusions from our study:Our work suggests three steps to improve effectiveness of diagnostic tests in early detection and preventing transmission of SARS-CoV-2 as new variants emerge and as infections spread to additional segments of the global population: (1) Additional longitudinal studies are needed that include high-frequency collection from multiple respiratory sites using quantitative assays with high analytical sensitivity. (2) Policy makers need to use such quantitative data to revise and optimize testing, surveillance, and screening guidelines to ensure early detection of SARS-CoV-2 infections and reduction of transmission. (3) Innovation is needed to produce rapid point-of-care tests with high analytical sensitivity for a range of sample types  at a price point to enable global distribution.75 and recent evidence suggests that vaccinated individuals may transmit infections from the new variants, including Delta.7 Another reason for continued monitoring of early viral kinetics is that viral evolution, including of host tropism, can markedly diminish the effectiveness of a diagnostic strategy. In one study, decreased clinical sensitivity of NP swabs was observed in SARS-CoV-2 variant B.1.616,46 which may indicate a tropism shift of the virus into lower-respiratory compartments. Finally, quantitative data must be acquired in parallel with viral-culture data to understand the viral loads and phases of infection that are most relevant to transmission.As new SARS-CoV-2 variants emerge, quantitative studies of the kinetics of early-stage viral loads must be continually updated. Importantly, such studies should be undertaken in people of a wide range of ethnicities, races, health conditions, and ages. For example, children under 12 years of age remain ineligible for vaccination even as schools around the country reopen for in-person studies. Given the potential differences in viral kinetics between children and adults, it is critical to collect quantitative viral-load data from children to understand the most effective testing strategies for this population. Quantitative studies of viral-load dynamics must also include vaccinated persons. Breakthrough cases are often asymptomaticearliest detection. Moreover, lacking such data-based guidance, diagnostic tests have been used incorrectly  in several scenarios, resulting in outbreaks that could have been prevented with an appropriate testing strategy.82 Once armed with data on early viral-load kinetics of new and emerging variants, policy makers will be able to develop targeted testing strategies  for key populations undergoing regular repeated testing, such as hospital staff and nursing-home staff. Such data would also inform optimal testing guidelines for early detection in situations where a single test is typically administered to admit a person into an environment  where the impact of false negatives is particularly high.Early detection of infection clearly reduces community transmission, however for most of the COVID-19 pandemic, policy makers have had to develop testing strategies in the absence of quantitative data on viral kinetics from the earliest stage of infection. Testing strategies have been guided by the available viral-load data, which has come mostly from hospitalized patients, symptomatic people, and people who have tested positive with the commonly available tests; but these data cannot inform on the best strategies for One barrier to implementing such more advanced testing strategies is availability of appropriate tests. Because the optimal sample type for early detection might be different for different populations, or might change as new variants emerge, tests with robust high analytical sensitivity across multiple sample types are needed. Developing such tests is challenging because it requires incorporating robust sample-preparation technology to purify and concentrate pathogen nucleic acids from diverse human matrices, from upper respiratory  to lower respiratory samples . It is even more challenging to incorporate such sample-preparation technology into tests that can be broadly deployed—at very low cost—at the point of care in limited-resource settings . Development of such highly sensitive, rapid, and inexpensive tests with broad sample-type compatibility is urgently needed.73 and future quantitative studies of early viral-load kinetics will lead to improved testing strategies to combat the current COVID-19 pandemic. The methodology for performing such studies efficiently and quickly will likely be extendable to defining strategies for early detection of causative pathogens in subsequent pandemics.We hope our data, important work by others in this area,Refer to the 19 Both studies were reviewed and approved by the Institutional Review Board of the California Institute of Technology, protocol #20–1026. All participants provided either written informed consent or (for minors ages 6–17) assent accompanied by parental permission, prior to enrollment. Participants were eligible if they had recently (within 7 days) been diagnosed with COVID-19 by a CLIA laboratory test, or lived with someone meeting who had. Demographic and medical information for the seven participants described here can be found in This study is an extension of our previous study examining viral load in saliva.19 Symptoms (including those listed by the CDC83) were reported by participants twice daily in parallel with sample collection. Participants recorded any COVID-19-like symptoms (as defined by the CDC83) on a symptom-tracking card or on a custom app run on REDCap.Acquisition of participant data was performed as described in our previous study.Participants self-collected nasal-swab (1 swab) and saliva (~1.5mL) samples in the Spectrum SDNA-1000 Saliva Collection Kit , which contains 1.5mL of liquid buffer, at home twice per day (after waking up and before going to bed), per manufacturer’s guidelines. Of note, at the time of this writing, Spectrum devices are not approved for the collection of nasal-swab samples. Participants were instructed not to eat, drink, smoke, brush their teeth, use mouthwash, or chew gum for at least 30 min prior to donating. Prior to nasal-swab donation, participants were asked to gently blow their noses to remove debris. Participants were provided with one of the following types of sterile flocked swabs: Nest Oropharyngeal Specimen Collection Swabs  Puritan HydraFlock Swab  or Copan USA FLOQSwab . Participants were instructed to swab each nostril for four complete rotations using the same swab while applying gentle pressure, then to break the tip of the swab into the Spectrum tube and securely screw on the cap. A parent or legal guardian assisted all minors with swab collection and they were instructed to wear a face covering during supervision.Samples were stored at 4 °C and were equilibrated to room temperature before being processed with extraction protocols.Participant saliva and anterior-nares swab samples were extracted using the KingFisher Flex 96 instrument (ThermoFisher Scientific) with the MagMax Viral Pathogen I Nucleic Acid Isolation kit  guided by ThermoFisher technical notes for SARS-CoV-2 modification and saliva.19 using the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel,66 with duplicate reactions. To establish the limit of detection (LOD) for each sample type , 20 contrived samples with the equivalent of 1,000 copies/mL were prepared, individually extracted as described above, and subjected to RT-qPCR, with a positive result for detection (as defined in the EUA for the CDC RT-qPCR assay) in ≥ 19 of 20 (≥95%) of replicates establishing the LOD  on elutions from both the calibration curve samples , Fig. S2N1 gene Cq of below 26 were sent to Chan Zuckerberg Biohub for SARS-CoV-2 viral genome sequencing, a modification of Deng et al. (2020)84 as described in Gorzynski et al. (2020).85 Sequences were assigned pangolin lineages described by Rambaut et al. (2020)86 using Phylogenetic Assignment of Named Global outbreak LINeages software v2.3.2 (github.com/cov-lineages/pangolin). Chan Zuckerberg Biohub submitted consequence genomes to GISAID.Saliva and nasal-swab samples with an 1


Non-invasive characterization of adrenal lesions requires a rigorous approach. Although CT is the cornerstone of adrenal lesion characterization, a multimodality multiparametric imaging approach helps improve confidence in adrenal lesion characterization. 18F-FDG PET/CT helps differentiate between atypical benign and malignant adrenal lesions, with the adrenal-to-liver maximum standardized uptake value ratio being the most discriminative variable. Recent studies evaluating the capabilities of radiomics and artificial intelligence have shown encouraging results.Detection and characterization of adrenal lesions have evolved during the past two decades. Although the role of imaging in adrenal lesions associated with hormonal secretion is usually straightforward, characterization of non-functioning adrenal lesions may be challenging to confidently identify those that need to be resected. Although many adrenal lesions can be readily diagnosed when they display typical imaging features, the diagnosis may be challenging for atypical lesions. Computed tomography (CT) remains the cornerstone of adrenal imaging, but other morphological or functional modalities can be used in combination to reach a diagnosis and avoid useless biopsy or surgery. Early- and delayed-phase contrast-enhanced CT images are essential for diagnosing lipid-poor adenoma. Ongoing studies are evaluating the capabilities of dual-energy CT to provide valid virtual non-contrast attenuation and iodine density measurements from contrast-enhanced examinations. Adrenal lesions with attenuation values between 10 and 30 Hounsfield units (HU) on unenhanced CT can be characterized by MRI when iodinated contrast material injection cannot be performed.  Adrenal lesions are present on 4–6% of routine abdominal imaging examinations, mostly as incidental adrenal lesions consisting of asymptomatic adrenal lesions discovered when performing an abdominal imaging examination for any other indication, with the exclusion of adrenal lesions discovered during the screening of patients with hereditary syndromes or extra-adrenal tumors . AdrenalThe objective of this review article was to provide an overview of the essentials of adrenal gland imaging, including the latest advancements and newest imaging techniques.Inherited genetic disorders represent major risk factors for adrenal lesions. Pheochromocytomas are present in several genetic syndromes ,5, which18F-fluorodesoxyglucose (FDG) positron emission tomography (PET)/CT . Ad. Ad71]. 123-iodine for single photon emission computed tomography (SPECT) or with 11C for PET imaging. 11C-metomidate PET/CT has 86% sensitivity and 96% specificity for the diagnosis of adrenocortical vs. non-adrenocortical lesions . In sucpatients . 68Ga-DOion rate . Recent ckground  75]. 68. 6818F-F18F-DOPA, 18F-fluoro-labeled fluorodopamine; 123I-MIBG, 123-iodine-labeled meta-iodobenzylguanidine; 68GA-DOTA-SSA, 68-gallium labeled DOTA somatostatin analogs; SDHx, succinate dehydrogenase Type x; NF1, neurofibromatosis type 1; RET, RET proto-oncogene; VHL, von Hippel–Lindau; MAX, Myc-associated factor X.68Gallium prostate membrane-specific antigen (68GaPMSA) uptake by the solid portion of adrenal schwannoma may be important but remains poorly studied . So. So38]. AVS consists of femoral venous access to the adrenal veins to sample blood as close as possible from its point of secretion. The ratio of hormones between both glands allows the lateralization of the secretion at a level of >4 for aldosterone . PharmacHistopathological confirmation using percutaneous biopsy may be required to avoid surgery only in specific situations, such as undetermined, non-secreting adrenal lesions confirmed using non-invasive tools, suspected metastasis in a patient with a cancer for which the presence of an adrenal metastasis would alter management, searching for specific mutations for further targeted therapies and a suspicion of rare tumors such as adrenal sarcoma, primary lymphoma or granulomatosis ,85. UndeArtificial intelligence (AI) may provide added value to computed image analysis. It requires different steps from image acquisition for the analysis. The first step mostly consists of lesion segmentation. Segmentation aims to extract the volume of interest from the entire data. The segmentation may be manual or automated using different algorithms such as multi-organ atlas-based, landmark-based, shape model-based and neural network-based algorithms . DespiteAfter segmentation, the analysis may be performed using several algorithms and strategies, including machine learning (ML) and deep learning (DL). ML refers to providing more data to continuously update the computer/software performance for a given task. This implies that the computer/software learns from the data and improves its performance through experience . DL refeMidway between AI and morphological imaging, texture and radiomics analyses are quantitative methods that provide measurements of heterogeneity using parameters based on local variations in image voxel brightness that are often beyond the reach of the human eye . ExtractTo date, clinical applications of AI remain limited in daily practice and most studies have a low level of evidence. However, radiomic features may provide new tools for the diagnosis of atypical adrenal lesions and research applications. To date, AI tools mostly aim to differentiate benign from malignant adrenal lesions. Specific characterization remains in the field of research.With first-order features, a >10% cut-off of negative voxels in a histogram derived from unenhanced CT data had 92.3% sensitivity and 100% specificity for the diagnosis of lipid-poor AA . The hisp = 0.39) . One ma18F-FDG-PET/CT data did not prove superior to SUVmax alone for discriminating between AA and adrenal metastasis, as SUVmax alone has 86% sensitivity and 80% specificity in that task [In functional imaging, texture analysis extracted from hat task .18F-FDG PET/CT data, such as the non-uniformity calculated on the grey- level run length matrix, can be used as a predictor of overall survival in patients with primary adrenal lymphoma [Some texture parameters derived from lymphoma .As previously described, most of the existing AI tools suffer from a lack of level of evidence and applicability for use in daily practice. The next steps consist of selection of the tools and validation in large prospective cohorts. Researchers may also consider using AI-extracted imaging features in association with clinico-biological features as previously performed with conventional imaging to improve the capacity for adrenal lesion characterization . In conclusion, adrenal lesions have currently a prevalence of 4–6%, but it can be assumed that these figures may increase with the rise in the use of abdominal imaging examinations, along with improvements in imaging technology. Although AA remains the most frequent adrenal lesion, many histological subtypes exist, with possible heterogeneous presentations within conventional imaging, resulting in limited specificity and accuracy. Radiologists must be aware of typical features to avoid overdiagnosis of benign or indolent lesions. Atypical features require a multidisciplinary approach with a comprehensive evaluation. Recent studies evaluating the capabilities of radiomics and artificial intelligence have shown encouraging results. but further research remains to be carried out to proceed further in the non-invasive characterization of adrenal gland lesions.