Co-Expression of Niemann-Pick Type C1-Like1 (NPC1L1) with ACE2 Receptor Synergistically Enhances SARS-CoV-2 Entry and Fusion.

The entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into human embryonic kidney (HEK293T) cells has been shown to be a cholesterol-rich, lipid raft-dependent process. In this study, we investigated if the presence of a cholesterol uptake receptor Niemann-pick type c1-like1 (NPC1L1) impacts SARS-CoV-2 cell entry. Initially, we utilized reporter-based pseudovirus cell entry assays and a spike (S) glycoprotein-mediated cell-to-cell fusion assay. Using Chinese hamster ovary (CHO-K1) cells, which lack endogenous receptors for SARS-CoV-2 entry, our data showed that the co-expression of NPC1L1 together with the ACE2 receptor synergistically increased SARS-CoV-2 pseudovirus entry even more than the cells expressing ACE-2 receptor alone. Similar results were also found with the HEK293T cells endogenously expressing the ACE2 receptor. Co-cultures of effector cells expressing S glycoprotein together with target cells co-expressing ACE-2 receptor with NPC1L1 significantly promoted quantitative cell-to-cell fusion, including syncytia formation. Finally, we substantiated that an elevated expression of NPC1L1 enhanced entry, whereas the depletion of NPC1L1 resulted in a diminished SARS-CoV-2 entry in HEK293T-ACE2 cells using authentic SARS-CoV-2 virus in contrast to their respective control cells. Collectively, these findings underscore the pivotal role of NPC1L1 in facilitating the cellular entry of SARS-CoV-2. Importance: Niemann-Pick type C1-like1 (NPC1L1) is an endosomal membrane protein that regulates intracellular cholesterol trafficking. This protein has been demonstrated to play a crucial role in the life cycle of several clinically important viruses. Although SARS-CoV-2 exploits cholesterol-rich lipid rafts as part of its viral entry process, the role of NPC1L1 in SARS-CoV-2 entry remains unclear. Our research represents the first-ever demonstration of NPC1L1's involvement in facilitating SARS-CoV-2 entry. The observed role of NPC1L1 in human kidney cells is not only highly intriguing but also quite relevant. This relevance stems from the fact that NPC1L1 exhibits high expression levels in several organs, including the kidneys, and the fact that kidney damages are reported during severe cases of SARS-CoV-2. These findings may help us understand the new functions and mechanisms of NPC1L1 and could contribute to the identification of new antiviral targets.

SARS-CoV-2 superinfection in CD14+ monocytes with latent human cytomegalovirus (HCMV) promotes inflammatory cascade.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), has posed significant challenges to global health. While much attention has been directed towards understanding the primary mechanisms of SARS-CoV-2 infection, emerging evidence suggests co-infections or superinfections with other viruses may contribute to increased morbidity and mortality, particularly in severe cases of COVID-19. Among viruses that have been reported in patients with SARS-CoV-2, seropositivity for Human cytomegalovirus (HCMV) is associated with increased COVID-19 risk and hospitalization. HCMV is a ubiquitous beta-herpesvirus with a seroprevalence of 60-90 % worldwide and one of the leading causes of mortality in immunocompromised individuals. The primary sites of latency for HCMV include CD14+ monocytes and CD34+ hematopoietic cells. In this study, we sought to investigate SARS-CoV-2 infection of CD14+ monocytes latently infected with HCMV. We demonstrate that CD14+ cells are susceptible and permissive to SARS-CoV-2 infection and detect subgenomic transcripts indicative of replication. To further investigate the molecular changes triggered by SARS-CoV-2 infection in HCMV-latent CD14+ monocytes, we conducted RNA sequencing coupled with bioinformatic differential gene analysis. The results revealed significant differences in cytokine-cytokine receptor interactions and inflammatory pathways in cells superinfected with replication-competent SARS-CoV-2 compared to the heat-inactivated and mock controls. Notably, there was a significant upregulation in transcripts associated with pro-inflammatory response factors and a decrease in anti-inflammatory factors. Taken together, these findings provide a basis for the heightened inflammatory response, offering potential avenues for targeted therapeutic interventions among HCMV-infected severe cases of COVID-19. SUMMARY: COVID-19 patients infected with secondary viruses have been associated with a higher prevalence of severe symptoms. Individuals seropositive for human cytomegalovirus (HCMV) infection are at an increased risk for severe COVID-19 disease and hospitalization. HCMV reactivation has been reported in severe COVID-19 cases with respiratory failure and could be the result of co-infection with SARS-CoV-2 and HCMV. In a cell culture model of superinfection, HCMV has previously been shown to increase infection of SARS-CoV-2 of epithelial cells by upregulating the human angiotensin-converting enzyme-2 (ACE2) receptor. In this study, we utilize CD14+ monocytes, a major cell type that harbors latent HCMV, to investigate co-infection of SARS-CoV-2 and HCMV. This study is a first step toward understanding the mechanism that may facilitate increased COVID-19 disease severity in patients infected with SARS-CoV-2 and HCMV.

Significance of wastewater surveillance in detecting the prevalence of SARS-CoV-2 variants and other respiratory viruses in the community - A multi-site evaluation.

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome in wastewater has proven to be useful for tracking the trends of virus prevalence within the community. The surveillance also provides precise and early detection of any new and circulating variants, which aids in response to viral outbreaks. Site-specific monitoring of SARS-CoV-2 variants provides valuable information on the prevalence of new or emerging variants in the community. We sequenced the genomic RNA of viruses present in the wastewater samples and analyzed for the prevalence of SARS-CoV-2 variants as well as other respiratory viruses for a period of one year to account for seasonal variations. The samples were collected from the Reno-Sparks metropolitan area on a weekly basis between November 2021 to November 2022. Samples were analyzed to detect the levels of SARS-CoV-2 genomic copies and variants identification. This study confirmed that wastewater monitoring of SARS-CoV-2 variants can be used for community surveillance and early detection of circulating variants and supports wastewater-based epidemiology (WBE) as a complement to clinical respiratory virus testing as a healthcare response effort. Our study showed the persistence of the SARS-CoV-2 virus throughout the year compared to a seasonal presence of other respiratory viruses, implicating SARS-CoV-2's broad genetic diversity and strength to persist and infect susceptible hosts. Through secondary analysis, we further identified antimicrobial resistance (AMR) genes in the same wastewater samples and found WBE to be a feasible tool for community AMR detection and monitoring.

Inactivation of SARS-CoV-2 and Other Human Coronaviruses Aided by Photocatalytic One-Dimensional Titania Nanotube Films as a Self-Disinfecting Surface.

SARS-CoV-2 and its variants that continue to emerge have necessitated the implementation of effective disinfection strategies. Developing self-disinfecting surfaces can be a potential route for reducing fomite transmissions of infectious viruses. We show the effectiveness of TiO2 nanotubes (T_NTs) on photocatalytic inactivation of human coronavirus, HCoV-OC43, as well as SARS-CoV-2. T_NTs were synthesized by the anodization process, and their impact on photocatalytic inactivation was evaluated by the detection of residual viral genome copies (quantitative real-time quantitative reverse transcription polymerase chain reaction) and infectious viruses (infectivity assays). T_NTs with different structural morphologies, wall thicknesses, diameters, and lengths were prepared by varying the time and applied potential during anodization. The virucidal efficacy was tested under different UV-C exposure times to understand the photocatalytic reaction's kinetics. We showed that the T_NT presence boosts the inactivation process and demonstrated complete inactivation of SARS-CoV-2 as well as HCoV-OC43 within 30 s of UV-C illumination. The remarkable cyclic stability of these T_NTs was revealed through a reusability experiment. The spectroscopic and electrochemical analyses have been reported to correlate and quantify the effects of the physical features of T_NT with photoactivity. We anticipate that the proposed one-dimensional T_NT will be applicable for studying the surface inactivation of other coronaviruses including SARS-CoV-2 variants due to similarities in their genomic structure.

Aluminum Phosphide Poisoning, an Institutional Experience: Case Series.

BACKGROUND: The growing concern over pesticide use has been linked to self-harm and suicide especially in agricultural countries like Nepal.  Pesticides like organophosphorus and aluminum phosphide cause the majority of deaths. Although organophosphorus poisoning is common means for suicide, Aluminum phosphide poisoning is also encountered occasionally. Our case series aims to look after the intent of poisoning and the outcome of the patients following Aluminum phosphide poisoning. METHODS: This hospital record-based study includes Aluminum phosphide poisoning patients presenting to the emergency department of Scheer Memorial Adventist Hospital from first January 2017 to 31st December 2020. Data were analyzed using SPSS version-22. RESULTS:   Out of 25 total poisoning cases, most of them were female (60%) and married (56%).  The case fatality rate was 84% among which 20% cases were brought dead while 64% died in the hospital. All poisoning cases were suicidal in intent. CONCLUSIONS: Herein we report a case series on 25 Aluminum phosphide poisoning cases with high case fatality rate and all cases being suicidal in intent.

Psychological and clinical-epidemiological profile of poisoning in Nepal: an institutional experience.

Background  Poisoning has become a major public health problem, with the intent in most cases being self-harm and commit suicide. This study highlights the psychological and clinical-epidemiological profile of patients visiting Scheer Memorial Adventist Hospital after poisoning.  Methods  This retrospective record-based study was done among poisoning patients of a hospital in Nepal from 1st January 2018 to 31st December 2020. Data were analyzed using STATA version-15.  Results  Out of 134 total poisoning cases, 71 had consumed organophosphate compounds. The majority of the cases were female (59.2% in organophosphate groups, 69.8% in non-organophosphate groups). The circumstances of poisoning were mostly suicidal (95.8% in organophosphate groups, 90.5% in non-organophosphate groups) and the reasons for this being mostly family disputes. Organophosphate groups had 8.41 times higher odds of having complications when compared to non-organophosphorus compounds.   Conclusions  The majority of the poisoning cases were suicidal in nature and family disputes being the major reason for the intake of a poisonous substance. This demands that more attention be given to psychological and family counseling to resolve any disputes, as well as psychological management of poisoning cases after medical management. Also, a strong regulatory mechanism should be imposed to control the easy access to poisonous substances.

W-GUN: Whale Optimization for Energy and Delay-Centric Green Underwater Networks.

Underwater sensor networks (UWSNs) have witnessed significant R&D attention in both academia and industry due to their growing application domains, such as border security, freight via sea or river, natural petroleum production and the fishing industry. Considering the deep underwater-oriented access constraints, energy-centric communication for the lifetime maximization of tiny sensor nodes in UWSNs is one of the key research themes in this domain. Existing literature on green UWSNs are majorly adapted from the existing techniques in traditional wireless sensor network relying on geolocation and the quality of service-centric underwater relay node selection, without paying much attention to the dynamic underwater network environments. To this end, this paper presents an adapted whale and wolf optimization-based energy and delay-centric green underwater networking framework (W-GUN). It focuses on exploiting dynamic underwater network characteristics by effectively utilizing underwater whale-centric optimization in relay node selection. Firstly, an underwater relay node optimization model is mathematically derived, focusing on underwater whale dynamics for incorporating realistic underwater characteristics in networking. Secondly, the optimization model is used to develop an adapted whale and grey wolf optimization algorithm for selecting optimal and stable relay nodes for centric underwater communication paths. Thirdly, a complete workflow of the W-GUN framework is presented with an optimization flowchart. The comparative performance evaluation attests to the benefits of the proposed framework and is compared to state-of-the-art techniques considering various metrics related to underwater network environments.

Real-time physiological tremor estimation using recursive singular spectrum analysis.

Physiological hand tremor causes undesirable vibration of hand-held surgical instruments which results in imprecisions and poor surgical outcomes. Existing tremor cancellation algorithms are based on detection of the tremulous component from the whole motion; then adding an anti-phase tremor signal to the whole motion to cancel it out. These techniques are based on adaptive filtering algorithms which need a reference signal that is highly correlated with the actual tremor signal. Hence, such adaptive approaches use a non-linear phase filter to pre-filter the tremor signal either offline or in real-time. However, pre-filtering causes unnecessary delays and non-linear phase distortions as the filter has frequency selective delays. Consequently, the anti-phase tremor signal cannot be generated accurately which results in poor tremor cancellation. In this paper, we present a new technique based on singular spectrum analysis (SSA) and its recursive version, that is, recursive singular spectrum analysis (RSSA). These algorithms decompose the whole motion into dominant voluntary components corresponding to larger eigenvalues and oscillatory tremor components having smaller eigenvalues. By selecting a group of specific decomposed signals based on their eigenvalues and spectral range, both voluntary and tremor signals can be reconstructed accurately. We test the SSA and RSSA algorithms using recorded tremor data from five novice subjects. This new approach shows the tremor signal can be estimated from the whole motion with an accuracy of up to 85% offline. In real-time, tolerating a delay of ≈ 72ms, the tremor signal can be estimated with at least 70% accuracy. This delay is found to be one-tenth of the delay caused by a conventional linear-phase bandpass filter to achieve similar performance in real-time.

A Quaternion Weighted Fourier Linear Combiner for Modeling Physiological Tremor.

GOAL: This paper offers a new approach to model physiological tremor aiming at attenuating undesired vibrations of the tip of microsurgical instruments. METHOD: Several tremor modeling algorithms, such as the weighted Fourier linear combiner (wFLC), have proved effective. They, however, treat the three-dimensional (3-D) tremor signal as three independent 1-D signals in the x-, y-, and z-axes. In addition, the force f by which a surgeon holds the instrument has never been taken into account in modeling. Hence, conventional algorithms are inherently blind to any potential multidimensional couplings. RESULTS: We first show that there exists statistically significant subject- and task-dependent coherence between data in the x-, y-, z -, and f-axes. We hypothesize that a filter that models the tremor in 4-D ( x , y, z, and f ) yields a more accurate model of tremor. We, therefore, developed a quaternion version of the wFLC algorithm and termed it QwFLC. We tested the proposed QwFLC algorithm with real physiological tremor data that were recorded from five novice subjects and four experienced microsurgeons. Although compared to wFLC, QwFLC requires six times larger computational resources, we showed that QwFLC can improve the modeling by up to 67% and that the improvement is proportional to the total coherence between the tremor in xyz and the force signal. CONCLUSION: By taking into account interactions of the 3-D tremor and the force data, the tremor modeling performance enhances significantly.