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+ + + ++Wastewater monitoring can provide insights into respiratory disease occurrence in communities that contribute to the wastewater system. Using daily measurements of RNA of influenza A (IAV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV), as well as SARS-CoV-2 in wastewater solids from eight publicly owned treatment works in the Greater San Francisco Bay Area of California between July 2022 until early May 2023, we identify a “tripledemic” when concentrations of IAV, RSV, and SARS-CoV-2 peaked at approximately the same time. HMPV was also widely circulating. We designed novel hydrolysis probe RT-PCR assays for different IAV subtype makers to discern that the dominant circulating IAV subtype was H3N2. We show that wastewater data can be used to identify onset and offset of wastewater disease occurrence events that can provide insight into disease epidemiology and timely, localized information to inform hospital staffing and clinical decision making to respond to circulating viruses. Whereas RSV and IAV wastewater events were mostly regionally coherent, HMPV events displayed localized occurrence patterns. +
++Introduction. Coronavirus disease 2019 (COVID-19) survivors can develop residual lung abnormalities consistent with lung fibrosis. A shared genetic component between COVID-19 and idiopathic pulmonary fibrosis (IPF) has been shown. However, genetic overlap studies of IPF and COVID-19 have primarily concentrated on the IPF genome-wide significant risk variants that have been previously identified, rather than combined into a genome-wide polygenic risk. Here we used IPF genome-wide association study (GWAS) results to calculate polygenic risk scores (PRSs) and study their association with COVID-19 severity. Methods. We used results from the largest meta-GWAS of clinically defined IPF risk (base dataset; n=24,589) and individual-level imputed data from the SCOURGE study of patients with COVID-19 (target dataset; n=15,024). We calculated IPF PRSs using PRSice-2 and assessed their association with COVID-19 hospitalisation, severe illness, and critical illness. We also evaluated the effect of age and sex stratification. Results were validated using an independent PRS method. Enrichment analyses and pathway-specific PRSs were performed to study biological pathways associated with COVID-19 severity. Results. IPF PRSs were significantly associated with COVID-19 hospitalisation and severe illness. The strongest association was found in patients aged <60 years, especially among younger males (OR=1.16; 95%CI=1.08-1.25; p=6.39x10-5). A pathway enrichment analysis of the variants included in the best model fit and subsequent pathway-specific PRSs analyses supported the link of Cadherin and Integrin signalling pathways to COVID-19 severity when stratified by age and sex. Conclusion. Our results suggest that there is genome-wide genetic overlap between IPF and severe COVID-19 that is dependent on age and sex and adds further support that the pathogenesis of both IPF and severe COVID-19 share underlying biological mechanisms. This could imply that individuals with a high IPF genetic risk are at an overall increased risk of developing lung sequelae resulting from severe COVID-19. +
++Background Vaccines for COVID-19 represent a major breakthrough. However, worries about adverse effects led to vaccine hesitancy in some people. On the other hand, as COVID-19 may be associated with various sequelae, vaccination may protect against such sequelae via the prevention of infections and severe disease. Methods We leveraged the UK-Biobank (UKBB) and studied associations of at least one dose of COVID-19 vaccination (BioNTech-BNT162b2 or Oxford-AstraZeneca-ChAdOx1) with short-term hospitalizations from cardiovascular and other selected diseases(N=393,544; median follow-up=54 days among vaccinated). Multivariable Cox and Poisson regression analyses were performed. We also performed adjustments using prescription-time distribution matching (PTDM) and prior-event rate ratio (PERR). PERR minimizes unmeasured confounding by comparing event hazards before introduction of vaccination. Results We observed that COVID-19 vaccination(at least one dose), when compared to no vaccination, was associated with reduced short-term risks of hospitalizations from stroke(hazard ratio[HR]=0.178, 95% CI: 0.127-0.250, P=1.50e-23), venous thromboembolism (VTE) (HR=0.426, CI: 0.270-0.673, P=2.51e-4), dementia(HR=0.114, CI: 0.060-0.216; P=2.24e-11), non-COVID-19 pneumonia(NCP) (HR=0.108, CI: 0.080-0.145; P=2.20e-49), coronary artery disease (CAD) (HR=0.563, CI: 0.416-0.762; P=2.05e-4), chronic obstructive pulmonary disease (COPD) (HR=0.212, CI: 0.126-0.357; P=4.92e-9), type-2 diabetes (T2DM) (HR=0.216, CI: 0.096-0.486, P=2.12e-4), heart failure (HR=0.174, CI: 0.118-0.256, P=1.34e-18) and renal failure (HR=0.415, CI: 0.255- 0.677, P=4.19e-4), based on Cox regression models. Among the above results, reduced hospitalizations for stroke, heart failure, NCP and dementia were consistently observed across all analyses, including regression/PTDM/PERR. Conclusions Taken together, this study provides further support to the safety and benefits of COVID-19 vaccination, and such benefits may extend beyond reduction of infection risk or severity per se. However, causal relationship cannot be concluded and further studies are required to verify the findings. +
++Infodemiology and infoveillance approaches have been extensively used in recent years to support traditional epidemiology and disease surveillance. Hence, the present study aimed to explore the association between Google Trends (GTs) search of clinical symptoms and cases reported during the first wave of COVID-19. The GT data from January 30, 2020, to September 30, 2020, and daily COVID-19 cases in India and a few selected states were collected from the Ministry of Health and Family Welfare, Government of India. Correlation analysis was performed between the GT index values and the number of confirmed cases. Followed by, the COVID-19 cases were predicted using Bayesian regression and classical linear regression models. A strong association was observed between the search index of clinical symptoms and reported COVID-19 cases (cold: R=0.41, headache: R=0.46, fever: R=0.66, loss of taste: R=0.78, loss of smell R=0.86) across India. Similarly, lagged correlations were also observed (loss of smell, loss of taste, loss of taste and loss of smell, fever and headache show 3, 9, 1, 9, and 13 days lag periods respectively). Besides this, the Bayesian regression model was outperformed (MAE: 0.331164, RMSE: 0.411087) for predicting the COVID-19 cases in India and regionally than the frequentist linear regression (MAE: 0.33134, RMSE: 0.411316). The study helps health authorities better prepare and planning of health care facility timely to avoid adverse impacts. +
++Neurodivergent (ND) individuals (e.g., Autistic people) are more likely to experience health problems that are characterised by central sensitisation9. Recent research suggests that a so-called Long-COVID syndrome might also be explained by a heightened response to internal physiological stimuli, much like in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Using a standardised assessment tool, we examined whether traits associated with Autism would predict long-term COVID-19 symptoms in 267 Healthcare Workers (HCW).. Higher autistic traits predicted COVID-19 symptoms that lasting more than 12 weeks regardless of formal autism diagnosis. A personality measure also showed that negative affect was associated with experiencing COVID-19 symptoms for 4-12 weeks, though the direction of causality in this case is uncertain. Limitations of the present study are 1) the retrospective nature of COVID-19 symptom reporting; 2) likely self-selection bias given the high number of HCWs who reported long-term COVID-19 symptoms; and 3) the gender-bias towards females in our sample. +
++Background: Myocardial injury (MI) is frequent in critically ill patients with COVID-19, but its pathogenesis remains unclear. We hypothesized that MI is not solely due to viral infection by SARS-CoV-2, but rather due to the common pathophysiological mechanisms associated with severe pulmonary infections and respiratory failure. Methods: Contemporary and comparative cohort study designed to compare the incidence of MI in patients with acute respiratory failure caused by COVID-19 to that of patients with other pulmonary infections. In addition, we aim to investigate whether MI is a distinct risk factor for in-hospital mortality in patients with COVID-19-related respiratory failure compared to those with non-COVID-19 infections. Results: The study included 1444 patients with COVID-19 [55.5% men; age 58 (46;68) years] and 182 patients with other pulmonary infections [46.9% men; age 62 (44;73) years]. The incidence of MI at ICU admission was lower in COVID-19 patients (36.4%) compared to non-COVID-19 patients (56%), and this difference persisted after adjusting for age, sex, coronary artery disease, heart failure, SOFA score, lactate, and C-reactive protein [RR 0.84 (95% CI, 0.71-0.99)]. MI at ICU admission was associated with a 59% increase in mortality [RR 1.59 (1.36-1.86); P<0.001], and there was no significant difference in the mortality between patients with COVID-19 and those with other pulmonary infections (P=0.271). Conclusion: Myocardial injury is less frequent in patients with critical COVID-19 pneumonia and respiratory failure compared to those with other types of pneumonia. The occurrence of MI is a significant risk factor for in-hospital mortality, regardless of the etiology of the pulmonary infection. +
++One in ten SARS-CoV-2 infections result in prolonged symptoms termed “long COVID”, yet disease phenotypes and mechanisms are poorly understood. We studied the blood proteome of 719 adults, grouped by long COVID symptoms. Elevated markers of monocytic inflammation and complement activation were associated with increased likelihood of all symptoms. Elevated IL1R2, MATN2 and COLEC12 associated with cardiorespiratory symptoms, fatigue, and anxiety/depression, while elevated MATN2 and DPP10 associated with gastrointestinal (GI) symptoms, and elevated C1QA was associated with cognitive impairment (the proteome of those with cognitive impairment and GI symptoms being most distinct). Markers of neuroinflammation distinguished cognitive impairment whilst elevated SCG3, indicative of brain-gut axis disturbance, distinguished those with GI symptoms. Women had a higher incidence of long COVID and higher inflammatory markers. Symptoms did not associate with respiratory inflammation or persistent virus in sputum. Thus, persistent inflammation is evident in long COVID, distinct profiles being associated with specific symptoms. +
++Background Antimicrobial Resistance (AMR), a major global public health threat causing 1.2 million deaths, calls for immediate action. Antimicrobial stewardship (AMS) promotes judicious antibiotic use, but the COVID-19 pandemic increased AMR by 15%. Our study evaluated AMS implementation and inappropriate antibiotic prescribing before-the-pandemic (PD) and during-the-pandemic (DP). Methods This retrospective study examined medical records of adult patients (age 25 and above) admitted to an NHS Foundation Trust in England for respiratory tract infections (RTIs) or pneumonia in 2019 and 2020. Our objective was to evaluate antibiotic prescribing practices BP and DP in 2019 and 2020. Primary outcomes included evaluating the prevalence of inappropriate antibiotic prescribing and assessing the implementation of AMS using Public Health England9s 9Start Smart, Then Focus9 (SSTF) toolkit. Reliable data extraction was ensured by two independent reviewers using a validated data extraction tool. Results A total of 640 patient records (320 from 2019 and 320 from 2020) were analysed. The mean age of enrolled adults was 74.3 years in 2019 and 76.2 years in 2020. COVID pneumonia showed a significantly higher odds ratio (OR) of 20.24 (95% CI 5.82 to 128.19, p-value<0.001). Inappropriate antibiotic prescribing, as per local guidelines, increased from 36% in 2019 to 64% in 2020 for the second course of antibiotics DP. Differences were observed in AMS interventions, with an OR of 3.36 (95% CI 1.30-9.25, p=0.015) for 9Continue Antibiotics9 and an OR of 2.77 (95% CI 1.37-5.70, p=0.005) for 9De-escalation9. Conclusion The COVID-19 pandemic significantly impacted antibiotic prescribing, increasing inappropriate use and posing risks of antimicrobial resistance. Factors influencing prescribing practices must be considered, and proactive measures, including updating the SSTF toolkit and developing an AMS roadmap, are needed to address the challenges of AMR in the context of evolving infectious diseases. +
++Post-Acute Sequelae of SARS-CoV-2 (PASC), also known as Long COVID, is globally estimated to have affected up to 40-50% of individuals who were infected with SARS-CoV-2. The causes of PASC are being investigated, and there are no established therapies. One of the leading hypotheses for the cause of PASC is the persistent activation of innate immune cells with increased systemic inflammation. Naltrexone is a medication with anti-inflammatory and immunomodulatory properties that has been used in other conditions that overlap with PASC. In this study we performed retrospective review of a clinical cohort of 59 patients at a single academic center who received low-dose naltrexone (LDN) off-label as a potential therapeutic intervention for PASC. The use of LDN was associated with improved clinical symptoms (fatigue, brain fog, post exertional malaise/PEM, unrefreshing sleep, sleep pattern, and headache), fewer number of symptoms, and better functional status. This observational finding warrants further testing in rigorous, randomized, placebo-controlled clinical trials. +
++Background: Varied seasonal patterns of respiratory syncytial virus (RSV) have been reported worldwide. We aimed to review the patterns of RSV activity globally before the COVID-19 pandemic and to explore factors potentially associated with RSV seasonality. Methods: We conducted a systematic review on articles identified in PubMed reporting RSV seasonality based on data collected before 1 January 2020. Information on the timing of the start, peak, and end of an RSV season, study location, study period, and details in study methods were extracted. RSV seasonal patterns were examined by geographic location, calendar month, analytic method and meteorological factors including temperature and absolute humidity. Correlation and regression analyses were conducted to explore the relationship between RSV seasonality and study methods and characteristics of study locations. Results: RSV seasons were reported in 209 articles published in 1973-2023 for 317 locations in 77 countries. Variations were identified in types of data, data collection and analytical methods across the studies. Regular RSV seasons were similarly reported in countries in temperate regions, with highly variable seasons identified in subtropical and tropical countries. Durations of RSV seasons were relatively longer in subtropical and tropical regions than from temperate regions. Longer durations of RSV seasons were associated with a higher daily average mean temperature and daily average mean absolute humidity. Conclusions: The global seasonal patterns of RSV provided important information for optimizing interventions against RSV infection. Heterogeneity in study methods highlighted the importance of developing and applying standardized approaches in RSV surveillance and data reporting. +
+Extracorporeal Photopheresis as a Possible Therapeutic Approach to Adults With Severe and Critical COVID-19 - Condition: COVID-19
Intervention: Procedure: Extracorporeal photopheresis
Sponsor: Del-Pest Central Hospital - National Institute of Hematology and Infectious Diseases
Recruiting
A Clinical Trial on Booster Immunization of Two COVID-19 Vaccines Constructed From Different Technical Routes - Condition: COVID-19
Interventions: Biological: Prototype and Omicron BA.4/5 Bivalent Recombinant COVID-19 Vaccine(Adenovirus Type 5 Vector) For Inhalation; Biological: Bivalent COVID-19 mRNA Vaccine; Biological: Recombinant COVID-19 Vaccine (Adenovirus Type 5 Vector) For Inhalation
Sponsors: Zhongnan Hospital; Institute of Biotechnology, Academy of Military Medical Sciences, PLA of China
Recruiting
Community-engaged Optimization of COVID-19 Rapid Evaluation And TEsting Experiences - Conditions: COVID-19; COVID-19 Pandemic
Interventions: Behavioral: COVID-19 walk-up, on-site testing strategy; Behavioral: Community Health Worker (CHW) leading testing navigation and general preventive care reminders; Behavioral: No-cost self-testing kit vending machines
Sponsors: University of California, San Diego; San Ysidro Health Center
Not yet recruiting
Safety Study of COVID19 Vaccine on the Market - Condition: COVID-19
Intervention: Biological: Recombinant new coronavirus vaccine (CHO cell)
Sponsors: Anhui Zhifei Longcom Biologic Pharmacy Co., Ltd.; Hunan Provincial Center for Disease Control and Prevention; Guizhou Center for Disease Control and Prevention; Hainan Center for Disease Control & Prevention
Recruiting
ACTIV-6: COVID-19 Study of Repurposed Medications - Arm F (Montelukast) - Condition: Covid19
Interventions: Other: Placebo; Drug: Montelukast
Sponsors: Susanna Naggie, MD; National Center for Advancing Translational Sciences (NCATS); Vanderbilt University Medical Center
Recruiting
ACTIV-6: COVID-19 Study of Repurposed Medications - Arm B (Fluvoxamine) - Condition: Covid19
Interventions: Drug: Fluvoxamine; Other: Placebo
Sponsors: Susanna Naggie, MD; National Center for Advancing Translational Sciences (NCATS); Vanderbilt University Medical Center
Completed
ACTIV-6: COVID-19 Study of Repurposed Medications - Arm D (Ivermectin 600) - Condition: Covid19
Interventions: Drug: Ivermectin; Other: Placebo
Sponsors: Susanna Naggie, MD; National Center for Advancing Translational Sciences (NCATS); Vanderbilt University Medical Center
Completed
ACTIV-6: COVID-19 Study of Repurposed Medications - Arm E (Fluvoxamine 100) - Condition: Covid19
Interventions: Drug: Fluvoxamine; Other: Placebo
Sponsors: Susanna Naggie, MD; National Center for Advancing Translational Sciences (NCATS); Vanderbilt University Medical Center
Completed
Evaluation of Home Use COVID-19 Frequent Antigen Testing and Data Reporting - Condition: COVID-19 Respiratory Infection
Intervention: Diagnostic Test: SARS CoV-2 antigen tests
Sponsors: IDX20 Inc; National Institute on Minority Health and Health Disparities (NIMHD)
Recruiting
Mitoquinone/Mitoquinol Mesylate as Oral and Safe Postexposure Prophylaxis for Covid-19 - Conditions: SARS-CoV Infection; COVID-19
Interventions: Drug: Mitoquinone/mitoquinol mesylate; Other: Placebo
Sponsor: University of Texas Southwestern Medical Center
Not yet recruiting
Pycnogenol® in Post-COVID-19 Condition - Conditions: Post COVID-19 Condition; Long COVID
Interventions: Drug: Pycnogenol®; Drug: Placebo
Sponsor: University of Zurich
Recruiting
Efficacy of Bailing Capsule on Pulmonary Fibrosis After COVID-19 - Conditions: Pulmonary Fibrosis; COVID-19 Pneumonia
Intervention: Drug: Bailing capsule
Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University
Not yet recruiting
Evaluating Emetine for Viral Outbreaks (EVOLVE) - Condition: COVID-19
Interventions: Drug: Emetine Hydrochloride; Drug: Placebo
Sponsors: Johns Hopkins University; Nepal Health Research Council; Bharatpur Hospital Chitwan; Stony Brook University; Rutgers University
Not yet recruiting
Cupping Therapy on Immune System in Post Covid -19 - Condition: Covid-19 Patients
Interventions: Combination Product: Cupping therapy with convential medical treatment; Drug: Convential medical treatment
Sponsor: Cairo University
Completed
To Evaluate the Immunogenicity and Safety of Sequential Booster Immunization of Recombinant Novel Coronavirus Vaccine (CHO Cells) for SARS-CoV-2 - Condition: COVID-19
Intervention: Biological: Recombinant Novel Coronavirus vaccine (CHO Cells)
Sponsor: Anhui Zhifei Longcom Biologic Pharmacy Co., Ltd.
Completed
Synthesis, Characterization, and Antibacterial Activity of New Isatin Derivatives - 1H-indol-2,3-dione (isatin) class of biologically active compounds have analgesic, anti-microbial, anti-inflammatory, anti-tubercular, anti-proliferative properties, and is also useful for the treatment of SARS-CoV. Schiff bases containing isatin moiety are known to have broad spectrum of biological activities like anti-viral, anti-tubercular, anti-fungal, and anti-bacterial. In this work, several Schiff base derivatives have been synthesized using two methods (synthetic and microwave) by…
Mercapto-pyrimidines are reversible covalent inhibitors of the papain-like protease (PLpro) and inhibit SARS-CoV-2 (SCoV-2) replication - The papain-like protease (PLpro) plays a critical role in SARS-CoV-2 (SCoV-2) pathogenesis and is essential for viral replication and for allowing the virus to evade the host immune response. Inhibitors of PLpro have great therapeutic potential, however, developing them has been challenging due to PLpro’s restricted substrate binding pocket. In this report, we screened a 115 000-compound library for PLpro inhibitors and identified a new pharmacophore, based on a mercapto-pyrimidine fragment that…
Sulfated Glycomimetic α-Helical Polypeptides for Antiviral Activity - In this work, we developed a library of sulfated glycomimetic polypeptides with a high sulfated degree (up to 99%) via a click reaction and sulfation modification, enabling control over the helicity, molecular weight, rigidity, and side-chain structure. Their potentials as the inhibitors of SARS-CoV-2 and common enterovirus were investigated, and the structure-activity relationship was explored in detail. The in vitro results revealed the crucial role of α-helical conformation and sulfated sugar…
Stakeholder perspectives and experiences of the implementation of remote mental health consultations during the COVID-19 pandemic: a qualitative study - CONCLUSIONS: Remote mental health consultations were welcomed as a means to continue care during the COVID-19 pandemic. Their swift and necessary adoption placed pressure on providers and organisations to adapt quickly, navigating challenges and adjusting to a new way of working. This implementation created changes to workflows and dynamics that disrupted the traditional method of mental health care delivery. Further consideration of the importance of the therapeutic relationship and fostering…
AEROSOLIZED SULFATED HYALURONAN DERIVATIVES PROLONG THE SURVIVAL OF K18 ACE2 MICE INFECTED WITH A LETHAL DOSE OF SARS-COV-2 - Despite several vaccines that are currently approved for human use to control the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), there is an urgent medical need for therapeutic and prophylactic options. SARS-CoV-2 binding and entry in human cells involves interactions of its spike (S) protein with several host cell surface factors, including heparan sulfate proteoglycans (HSPGs), transmembrane protease serine 2 (TMPRSS2), and angiotensin-converting enzyme 2…
β-Cyclodextrins as affordable antivirals to treat coronavirus infection - The SARS-CoV-2 pandemic made evident that there are only a few drugs against coronavirus. Here we aimed to identify a cost-effective antiviral with broad spectrum activity and high safety profile. Starting from a list of 116 drug candidates, we used molecular modelling tools to rank the 44 most promising inhibitors. Next, we tested their efficacy as antivirals against α and β coronaviruses, such as the HCoV-229E and SARS-CoV-2 variants. Four drugs, OSW-1, U18666A, hydroxypropyl-β-cyclodextrin…
Novel SARS-CoV-2 entry inhibitors, 2-anilinoquinazolin-4(3H)-one derivatives, show potency as SARS-CoV-2 antivirals in a human ACE2 transgenic mouse model - The ongoing COVID-19 has not only caused millions of deaths worldwide, but it has also led to economic recession and the collapse of public health systems. The vaccines and antivirals developed in response to the pandemic have improved the situation markedly; however, the pandemic is still not under control with recurring surges. Thus, it is still necessary to develop therapeutic agents. In our previous studies, we designed and synthesized a series of novel 2-anilinoquinazolin-4(3H)-one…
Antibody responses to mRNA versus non-mRNA COVID vaccines among the Mongolian population - CONCLUSIONS: The BNT162b2 vaccine showed the highest level of antibody against SARS-CoV-2, followed by the BBIBP-CorV, Gam-COVID-Vac, and ChAdOx1 n-CoV-19 vaccines. The level of antibodies was increased in people infected with SARS-CoV-2 after vaccination, as compared to uninfected but vaccinated individuals.
Inhibiting C5 in patients with severe COVID-19-the incorrect target? - Authors’ reply - No abstract
Inhibiting C5 in patients with severe COVID-19-the incorrect target? - No abstract
Pharmacological properties and derivatives of saikosaponins-a review of recent studies - CONCLUSIONS: An increasing amount of data have indicated diverse SS pharmacological properties, indicating crucial clues for future studies and the production of novel saikosaponin-based anti-inflammatory, efficacious anticancer, and anti-novel-coronavirus agents with improved efficacy and reduced toxicity.
Applications of advances in mRNA-based platforms as therapeutics and diagnostics in reproductive technologies - The recent COVID-19 pandemic led to many drastic changes in not only society, law, economics, but also in science and medicine, marking for the first time when drug regulatory authorities cleared for use mRNA-based vaccines in the fight against this outbreak. However, while indeed representing a novel application of such technology in the context of vaccination medicine, introducing RNA into cells to produce resultant molecules (proteins, antibodies, etc.) is not a novel principle. It has been…
Biotransformation and brain distribution of the anti-COVID-19 drug molnupiravir and herb-drug pharmacokinetic interactions between the herbal extract Scutellaria formula-NRICM101 - The aim of this study was to explore the effects of herbal drug pharmacokinetic interactions on the biotransformation of molnupiravir and its metabolite β-D-N4-hydroxycytidine (NHC) in the blood and brain. To investigate the biotransformation mechanism, a carboxylesterase inhibitor, bis(4-nitrophenyl)phosphate (BNPP), was administered. Not only molnupiravir but also the herbal medicine Scutellaria formula-NRICM101 is potentially affected by coadministration with molnupiravir. However, the…
Dicoumarol is an effective post-exposure prophylactic for SARS-CoV-2 Omicron infection in human airway epithelium - Repurposing existing drugs to inhibit SARS-CoV-2 infection in airway epithelial cells (AECs) is a quick way to find novel treatments for COVID-19. Computational screening has found dicoumarol (DCM), a natural anticoagulant, to be a potential SARS-CoV-2 inhibitor, but its inhibitory effects and possible working mechanisms remain unknown. Using air-liquid interface culture of primary human AECs, we demonstrated that DCM has potent antiviral activity against the infection of multiple Omicron…
Binding properties of selective inhibitors of P323L mutated RdRp of SARS-CoV-2: a combined molecular screening, docking and dynamics simulation study - Since 2019 the SARS-CoV-2 and its variants caused COVID-19, such incidents brought the world in pandemic situation. This happened due to furious mutations in SARS-CoV-2, in which some variants had high transmissibility and infective, this led the virus emerged as virulent and worsened the COVID-19 situation. Among the variants, P323L is one of the important mutants of RdRp in SARS-CoV-2. To inhibit the erroneous function of this mutated RdRp, we have screened 943 molecules against the P323L…
The Case Against Trump Is Strong, but There Are Problems Ahead - It gives Trump a compelling reason to persevere in his campaign, and to sow doubt about the criminal process. - link
How Elon Musk Could Affect the 2024 Election - The personal politics of Twitter’s owner wouldn’t matter so much if he hadn’t also demonstrated an extraordinary capacity for pettiness. - link
What Was Nate Silver’s Data Revolution? - Silver, a former professional poker player, was in the business of measuring probabilities. Many readers mistook him for an oracle. - link
The Trial of the Malibu Shooter - Anthony Rauda, who was accused of terrorizing residents of Malibu, one of California’s wealthiest and safest communities, has been convicted of killing a man sleeping in a tent with his two young daughters. - link
Is Donald Trump Scared? - At the former President’s indictment in Miami on Tuesday, it was impossible to say whether his fate was more likely to be a return to the White House—or prison. - link
+Why some cities are restricting landlords’ reviews of criminal history. +
++Every year, more than 600,000 people leave US state and federal prisons. Then they need to find a place to live. +
++Researchers have found that formerly incarcerated individuals are far more likely to be homeless than the general public. Many landlords simply reject renting to applicants who’ve been to jail or prison — and given that one in three US adults has a criminal record, this creates a significant housing crisis. +
++But those released with stable housing are more likely to reintegrate into their communities and less likely to end up back in prison than their formerly incarcerated peers in more precarious housing situations. +
++Enter “fair chance” laws: legislation that limits how landlords can use criminal records when screening prospective tenants. While the ordinances vary from place to place — some cover all rental housing while others just apply to subsidized housing — the goal is to limit how criminal histories can be used and ensure due process for prospective tenants when applying. +
++Think of it as a “ban-the-box” policy, which prohibits employers from asking about criminal records, but for landlords. The movement has picked up steam in liberal localities over the last decade, first in cities like Oakland, Berkeley, Seattle, and Portland. In Richmond, California, landlords who accept Section 8 vouchers are barred from rejecting applicants based on criminal history alone. Minneapolis restricts the use of background checks, eviction history, and credit history in rental applications, and New Jersey restricts how far back in time a specific crime can be considered. +
++Early research suggests fair chance ordinances may have some unintended consequences: One study found landlords in Minneapolis became more likely to discriminate by race after the policy took effect. But by and large, there hasn’t been much research into how fair chance laws are working, as proponents have been focused on raising awareness about the new protections and implementing them. +
++“It’s been just two years since New Jersey’s passage, and in full transparency, a bill like this does take time,” said James Williams, the director of racial justice policy at the New Jersey-based Fair Share Housing Center. “There’s a tremendous amount of education required and the education piece is still something that’s being actively done.” +
++For now, most advocates have their eye on a pending legal battle in Seattle, which in 2017 passed the most progressive fair chance ordinance in the country, prohibiting landlords from asking about “any arrest record, conviction record or criminal history” or refusing to rent to them because of that history. Landlords sued in 2018, arguing the statute violated their free speech and due process rights, and this past March a panel of the Ninth Circuit Court of Appeals decided the part of the law banning landlords from asking about criminal histories was unconstitutional. The Court upheld other aspects of the law, though, and both sides have filed for an appeal. +
++“I think the results from that case will have far-reaching implications,” said Marie Claire Tran-Leung, a senior attorney at the National Housing Law Project, which has promoted fair chance ordinances around the country. +
++For now, the only rigorous study on fair chance housing ordinances comes from the Minneapolis Federal Reserve, where two economists looked at the effects of a law the Minneapolis city council passed in 2019. +
++The local law caps security deposits at one month’s rent, bans the use of credit scores in rental applications, and restricts landlords’ ability to reject people based on evictions that occurred more than three years prior. For criminal records, landlords can no longer reject applicants due to misdemeanors older than three years, felonies older than seven years, and certain more serious convictions older than 10 years. +
++The economists submitted fake email inquiries to publicly listed rental ads using names chosen to sound like Black, white, and Somali people. (Minnesota has the largest Somali population in the US.) +
++The researchers found that after Minneapolis’s fair chance ordinance took effect, discrimination against Black and Somali applicants increased by over 10 percentage points for both groups, relative to those in neighboring St. Paul, which did not have such a law. Differences were largest for emails sent from Black and Somali male-sounding names, for apartments that were at least two bedrooms, and for units in historically Black neighborhoods. (The researchers couldn’t identify individual companies that discriminated, but could observe discrimination based on overall contact rates to randomized emails sent to large groups of properties.) +
++Marina Mileo Gorzig, one of the economists, told Vox that their study helps show causal impact of the fair chance ordinance, though it’s impossible to tell which aspect of the law — be it limiting eviction history, credit history, or criminal records — might be causing the effect. +
++Similar unintended consequences have been found for ban-the-box policies in the employment context. Research published in 2016 found employers were actually more likely to discriminate based on race following the passage of ban-the-box, thus increasing racial disparities in job interviews. More recent studies suggest the policies seem to have done little to increase employment for ex-offenders in the private sector. +
++Deborah Rho, the other economist to study Minneapolis’s fair chance ordinance, suggested outcomes might have been different if Minneapolis had a greater supply of housing, or if the city removed certain barriers to new housing development. “Economic theory would tell us landlords would have less room to discriminate if they were competing with more landlords,” she said. +
++Jeremiah Ellison, the Minneapolis council member who led the push for the city’s law, largely dismissed the conclusion that a tight housing market might be a factor. “That’s a free market solution, like saying the free market will solve racism,” he said. +
++Ellison told Vox he was reviewing the study and planned to meet with the researchers to ask questions, but felt their findings didn’t detract from the policy’s necessity. “From my vantage point, I don’t think they analyzed how the policy works at all,” he said. “And it’s a relatively young policy … it could take many, many years until tenants learn their rights.” +
++Meanwhile, in Seattle, city officials have been arguing that researchers find no empirical basis for the claim that a criminal record might indicate a future problematic tenancy or threat. Landlords, for their part, tend to argue such relationships exist and that they need to screen tenants’ criminal backgrounds. +
++Seattle points to two large-scale, rigorous studies that evaluated the efficacy of supportive housing programs that helped people at risk of homelessness, including tenants with criminal histories. One study found no significant difference between those formerly incarcerated and those never incarcerated in terms of supportive housing program outcomes. Another found a criminal record was not statistically predictive of failure in supportive housing. The researcher looked at detailed data like a program participant’s specific criminal history, time elapsed since their last conviction, number of prior offenses, and the seriousness of their past offenses, and found none were statistically predictive. +
++Coupled with the research showing how crucial stable housing is for successful re-entry, advocates have argued these studies “raise important questions about the validity of standards of risk estimation, screening practices and admissions policies related to criminal records in the general rental housing context.” +
++But lawyers representing landlords say the fact that Seattle can only point to relevant studies in the supportive housing context matters. “This is at the heart of our appeal,” Brian Hodges, an attorney with the Pacific Legal Foundation, said. “Seattle is not relying on studies that look at the private rental market, they’re looking at public supportive housing, which are either government-run or NGO housing that provides not just affordable housing but also drug and occupational counseling.” +
++Some Seattle landlords argue their experience dramatically changed following the passage of the fair chance law, and that denying them the ability to screen applicants makes it impossible to protect other residents and the property itself. +
++In one amicus brief, owners of a federally assisted building said following the law taking effect, conditions rapidly declined. The number of 911 calls more than doubled, more fights broke out in the lobby, used needles, trash, and feces were left in stairways, and fire alarms were repeatedly set off at night. They cited increased negative reviews online and average occupancy declines. +
++When one tenant stabbed his guest in the chest during an argument in November 2019, it was only after they were arrested that managers learned they had several outstanding arrest warrants. +
++In 2021, New Jersey passed a statewide fair chance housing law with bipartisan support, and with backing from landlord groups. It doesn’t go as far as Seattle’s ordinance in restricting how criminal histories can ultimately be used, but it comes with a strong enforcement mechanism. +
++The New Jersey Apartment Association, an industry group that represents landlords and housing managers, originally opposed the bill, but eventually endorsed it following a series of amendments. The original version, for example, proposed fines up to $25,000 for a first offense, and the final version landed on $10,000. +
++David Brogan, the group’s executive director, told Vox that since the law was passed, the real estate industry has had to train staff, reprogram systems, and update old paperwork, materials, and online data. “It’s a process,” he said, “but I have been impressed by how quickly the industry has moved to comply.” +
++With the exception of convictions related to producing methamphetamine and being listed on a sex offender registry, landlords can never ask about an applicant’s criminal history in the first round of applications, and they can only evaluate a criminal record after a conditional housing offer has been made. If a landlord finds a serious crime committed relatively recently, they can withdraw the offer, explaining to the applicant in detail why, and the applicant has the right to appeal it or file a complaint with the state. A housing provider can never rely on arrests that didn’t result in convictions to reject an applicant. +
++Brogan said his members think the bill is “reasonable” and “balanced” because people should not be punished for the rest of their lives for something they did years ago, but at the same time, landlords have an obligation to provide safe housing. The balance, he said, was struck by providing liability protection, creating reasonable penalties, and “banning the box” from an initial renter application but allowing it in later inquiries. +
++“Some fair chance in housing acts in other areas of the country don’t acknowledge the severity of the crime [and] simply ban background checks altogether,” Brogan said. “We felt that was unfair and unsafe.” +
++Williams, of the Fair Share Housing Center, said they’re most proud of the fact that the law puts responsibility for enforcing the rules within the state attorney general’s office, bringing more serious investigative powers than other states and cities had thus far embraced. He thinks his state’s law would be less likely to face the kind of constitutional challenge Seattle is dealing with because they don’t abolish the practice of landlords reviewing criminal records entirely, they just move those reviews to the back end of the process. +
++“There’s no bulletproof piece of legislation, but if it gets challenged, we’re ready,” he said. +
++Hodges, from the Pacific Legal Foundation, said the Seattle landlords he represents are willing to rent to people with criminal records, so long as they’re not violent, cooking meth, or past sex offenders. He suggested the government should provide housing for them, and excluding those kinds of applicants is not discrimination but a “business and property” decision. +
++“Being a criminal is not an inherent characteristic, this is not like race and religion or gender, it’s not a protected class,” he argued, and pointed to past court decisions that established landlords’ duty to other tenants to screen for violent crimes. Yet without more ample public supportive options, people with those kinds of backgrounds have nowhere to live. +
++As for potential unintended consequences, national advocates think that the existence of a housing shortage is not a reason to avoid pursuing more fair chance laws around the country and that the broader fight against racism will need to continue. +
++“Taking away what many landlords are using as a proxy for race helps reveal the underlying race discrimination,” said Tran-Leung, of the National Housing Law Project. “But I don’t think there’s any notion that taking away problematic screening criteria is going to cure it.” +
+Interrogating the true toll of pervasive racism. +
++For this month’s issue of The Highlight, Vox teamed up with Black-led nonprofit newsroom Capital B to explore the insidious effects of discrimination on Black Americans. +
++The collaboration — part of an ongoing partnership with Capital B — was prompted in part by the work of researchers at the University of Chicago, who compiled nearly 50 years’ worth of studies examining bias against Black people in nearly every aspect of modern life, which they shared exclusively with Vox and Capital B. +
++The researchers, led by Sendhil Mullainathan — one of the scholars behind the seminal resumé discrimination study “Are Emily and Greg More Employable than Lakisha and Jamal?” — reviewed decades of studies. They found that discrimination impacts consequential endeavors and mundane tasks alike, from buying a home and applying to jobs to looking for a new church and using rideshare apps. Simply put, discrimination is everywhere. +
++That isn’t news to the tens of millions of Black Americans who experience it daily. But as many white Americans continue to question whether systemic racism exists, these myriad studies offer affirmation, borne out with data in no uncertain terms, of its existence and pervasiveness. This, in turn, has provided us with opportunities to ask: What happens to Black lives when you endure racist acts day in and day out? What solutions exist? And what care can we provide? +
++Vox analyzed dozens of studies and found that racism adds up in insidious ways. +
++By Sean Collins and Izzie Ramirez +
++From chronic stress to cancer, racial discrimination weathers Black Americans’ lives over time. +
++By Margo Snipe +
++Cars can be a source of freedom. They also drive discrimination. +
++By Marin Cogan +
++How school reinforces inequalities between Black children and their peers. +
++By Jonquilyn Hill +
++The next generation of AI comes with a familiar bias problem. +
++By Abby Ohlheiser +
++Is it chemicals? Diet? Stress? +
++By Akilah Wise +
++There’s no cure for the effects of pervasive discrimination, but there are steps you can take to help heal. +
++By Kenya Hunter +
++CREDITS +
++Editors: Vox: Adam Estes, Libby Nelson, Lavanya Ramanathan, Julia Rubin. Capital B: Gavin Godfrey, Dalila Johari-Paul, Simone Sebastian +
++Copy editors/fact-checkers: Vox: Elizabeth Crane, Kim Eggleston, Tanya Pai, Caitlin PenzeyMoog. Capital B: Neil Cornish +
++Additional fact-checking: Anouck Dussaud, Kelsey Lannin +
++Art direction: Dion Lee, Paige Vickers +
++Audience: Gabriela Fernandez, Shira Tarlo, Agnes Mazur. Capital B: Charity Scott, Alexandra Watts +
++Production/project editors: Lauren Katz, Nathan Hall +
++The next generation of AI comes with a familiar bias problem. +
++Part of the discrimination issue of The Highlight. This story was produced in partnership with Capital B. +
++Say a computer and a human were pitted against each other in a battle for neutrality. Who do you think would win? Plenty of people would bet on the machine. But this is the wrong question. +
++Humans created computers, and they design and train the systems that make modern technology work. As these systems are created, the biases of their human creators are reflected in them. When people refer to artificial intelligence bias, this is, in essence, what they are talking about. Like human bias, AI bias, when translated into decisions or actions, becomes discrimination. Like many forms of discrimination, AI bias disproportionately impacts communities that historically or presently face oppression. +
++Facial recognition software has a long history of failing to recognize Black faces. Researchers and users have identified anti-Black biases in AI applications ranging from hiring to robots to loans. AI systems can determine whether you find public housing or whether a landlord rents to you. Generative AI technology is being pitched as a cure for the paperwork onslaught that contributes to medical professional burnout. +
++As the capabilities of generative AI tools like ChatGPT and Google Bard enter the mainstream, the unfair preferences or prejudices that have long plagued AI have remained in place. The effect is all around us, in apps and software you encounter daily, from the automatic sorting of your social media feeds to the chatbots you use for customer service. AI bias also can creep into some of the biggest decisions companies might make about you: whether to hire you for a job, to lend you money for a home, or to cover the cost of your health care. +
++The terminology of this technology — AI, algorithms, large language models — can make the examinations of its effects feel highly technical. In some ways, AI bias is a technical issue, one with no easy solution. Yet the questions at the heart of fighting AI bias require little specialized knowledge to understand: Why does bias creep into these systems? Who is harmed by AI bias? Who is responsible for addressing it and the harms it generates in practice? Can we trust AI to handle important tasks that have an impact on human lives? +
++Here’s a guide to help you sort through these concerns, and figure out where we go from here. +
++A lot of definitions of artificial intelligence rely on a comparison to human reasoning: AI, these definitions go, is advanced technology designed to replicate human intelligence, and able to perform tasks that have previously required human intervention. But really, AI is software that can learn, make decisions, complete tasks, and problem-solve. +
++AI learns how to do this from a data set, often referred to as its training data. An AI system trained to recognize faces would learn to do that on a data set composed of a bunch of photos. One that creates text would learn how to write from existing writing fed into the system. Most of the AI you’ve heard about in 2023 is generative AI, which is AI that can, from large data sets, learn how to make new content, like photos, audio clips, and text. Think the image generator DALL-E or the chatbot ChatGPT. +
++In order to work, AI needs algorithms, which are basically mathematical recipes, instructions for a piece of software to follow in order to complete tasks. In AI, they provide the basis for how a program will learn, and what it will do. +
++AI bias is like any other bias: It’s an unfair prejudice or practice present in or executed by the system. It disproportionately impacts some communities over others, and is creeping into more and more corners of daily life. People might encounter bias from a social media filter that doesn’t work properly on darker skin, or in test proctoring software that doesn’t account for the behavior of neurodivergent students. Biased AI systems might determine the care someone receives at the doctor or how they’re treated by the criminal justice system. +
++Bias finds its way into AI in a lot of ways. Broadly speaking, however, to understand what’s happening when an AI system is biased, you just need to know that AI is fundamentally trained to recognize patterns and complete tasks based on those patterns, according to Sasha Luccioni, a researcher on the Machine Learning Ethics and Society team at the open source AI startup Hugging Face. Because of this, she said, AI systems “will home in on the dominant patterns, whatever they are.” +
++Those dominant patterns might show up in the training data an AI system learns from, in the tasks it is asked to complete, and in the algorithms that power its learning process. Let’s start with the first of these. +
++AI-powered systems are trained on sets of existing data, like photos, videos, audio recordings, or text. This data can be skewed in an endless number of ways. For instance, facial recognition software needs photos to learn how to spot faces, but if the data set it’s trained on contains photographs that depict mostly white people, the system might not work as well on nonwhite faces. An AI-powered captioning program might not be able to accurately transcribe somebody speaking English with a slight foreign accent if that accent isn’t represented in the audio clips in its training database. AI can only learn from what it’s been given. +
++The data set’s bias might itself merely be a reflection of larger systemic biases. As Karen Hao has explained in MIT Technology Review, unrepresentative training data prompts AI systems to identify unrepresentative patterns. A system designed to automate a decision-making process trained on historical data may simply learn how to perpetuate the prejudices already represented in that history. +
++Perhaps an AI system’s creator is trying to remove bias introduced by a data set. Some methods of trying to reduce bias can also introduce their own problems. Making an algorithm “blind” to an attribute like race or gender doesn’t mean that the AI won’t find other ways to introduce biases into its decision-making process — and perhaps to identify the same attributes it was supposed to ignore, as the Brookings Institution explained in a 2019 report. For example, a system that is designed to assess applications for a job might be rendered “blind” to an applicant’s gender but learn to distinguish male-sounding and female-sounding names, or look for other indicators in their CV, like a degree from an all-women’s college, if the data set it’s trained on favors male applicants. +
++Probably, yes. +
++For many Americans, AI-powered algorithms are already part of their daily routines, from recommendation algorithms driving their online shopping to the posts they see on social media. Vincent Conitzer, a professor of computer science at Carnegie Mellon University, notes that the rise of chatbots like ChatGPT provides more opportunities for these algorithms to produce bias. Meanwhile, companies like Google and Microsoft are looking to generative AI to power the search engines of the future, where users will be able to ask conversational questions and get clear, simple answers. +
++“One use of chat might be, ‘Okay, well, I’m going to visit this city. What are some of the sites that I should see? What is a good neighborhood to stay in?’ That could have real business implications for real people,” Conitzer said. +
++Although generative AI is just beginning to show up in quotidian technologies, conversational search is already a part of many people’s lives. Voice-activated assistants have already shifted our relationship to searching for information and staying organized, making routine tasks — compiling a grocery list, setting a timer, or managing a schedule — as simple as talking. The assistant will do the rest of the work. But there’s an established bias in tools like Siri, Alexa, and Google Assistant. +
++Speech recognition technologies have an established history of failing in certain scenarios. They might not recognize requests from people who do not speak English as a first language, or they may fail to properly understand Black speakers. While some people may choose to avoid these problems by not using these technologies, these failures can be particularly devastating for those with disabilities who may rely on voice-activated technologies. +
++This form of bias is creeping into generative AI, too. One recent study of tools meant to detect the use of ChatGPT in any given writing sample found that these detectors might falsely and unfairly flag writing done by non-native English speakers as AI-generated. Right now, ChatGPT feels like a novelty to many of its users. But as companies rush to incorporate generative AI into their products, Conitzer said, “these techniques will increasingly be integrated into products in various ways that have real consequences on people.” +
++For a stark glimpse of how AI bias impacts human lives, we can look at the criminal justice system. Courts have used algorithms with biases against Black people to create risk scores meant to predict how likely an individual is to commit another crime. These scores influence sentences and prisoners’ ability to get parole. Police departments have even incorporated facial recognition, along with the technology’s well-documented biases, into its daily policing. +
++An algorithm designed to do a risk assessment on whether an arrestee should be detained would use data derived from the US criminal justice system. That data would contain false convictions, and fail to capture data on people who commit crimes and are not caught, according to Conitzer. +
++“Some communities are policed far more heavily than other communities. It’s going to look like the other community isn’t committing a whole lot of crimes, but that might just be a consequence of the fact that they’re not policed as heavily,” Conitzer explained. An algorithm trained on this data would pick up on these biases within the criminal justice system, recognize it as a pattern, and produce biased decisions based on that data. +
++Obvious AI bias is hardly limited to one institution. At the start of the Covid-19 pandemic, schools relied on anti-cheating software used for virtual test takers. That type of software often uses video analysis and facial recognition to watch for specific behaviors it’s been trained to see as potential signs of cheating. Students soon found that virtual proctoring software, intended to enforce academic fairness, didn’t work equally well for all students. Some popular proctoring programs were failing to detect Black faces and penalizing students who were unable to find a stable internet connection and quiet, private space in their home for test-taking. Proctoring software was particularly biased against students with a wide range of disabilities, or spiking the anxiety of test takers with some mental health conditions. +
++As the Center for Democracy and Technology has noted, proctoring software could incorrectly flag students requiring a screen reader, those with visual impairment or other disabilities that might cause irregular eye movements, and neurodivergent students who might pace or fidget while taking a test. Some proctoring services do not allow for bathroom breaks. +
++The good news is that AI bias is a problem that lots of people talk about and think about how to reduce. However, not everyone agrees on how to fix this increasingly pressing issue. +
++Sam Altman, the founder of OpenAI, recently told Rest of World that he believes these systems will eventually be able to fix themselves: “I’m optimistic that we will get to a world where these models can be a force to reduce bias in society, not reinforce it,” he said. “Even though the early systems before people figured out these techniques certainly reinforced bias, I think we can now explain that we want a model to be unbiased, and it’s pretty good at that.” +
++Altman’s solution essentially asks the world to trust the technology to fix itself, in a process driven by the people who created it. For a lot of AI and ethics experts, that’s not enough. +
++Luccioni, the Hugging Face ethics researcher, used the example of generative AI tools that are supposed to speed up medical paperwork, arguing that we should be questioning whether AI belongs in this space at all. “Say that ChatGPT writes down the wrong prescription, and someone dies,” she says. While note-taking is not a task that takes a decade of education to master, assuming that you can simply swap out a medical doctor for an AI bot to speed up the paperwork process removes vital oversight from the equation. +
++An even deeper problem, Luccioni notes, is that there are no mechanisms for accountability when an AI tool integrating itself into vital care makes mistakes. Companies promising to replace or work in tandem with highly specialized professionals do not need to seek any sort of certification before, for instance, launching a bot that’s supposed to serve as a virtual therapist. +
++Timnit Gebru, a computer scientist with deep expertise in AI bias and the founder of the Distributed AI Research Institute, argued recently that the companies behind the push to incorporate AI into more and more aspects of our lives have already proven that they do not deserve this trust. “Unless there is external pressure to do something different, companies are not just going to self-regulate. We need regulation and we need something better than just a profit motive,” she told the Guardian. +
++Conitzer says the problem of AI bias requires auditing and transparency in AI systems, particularly those tasked with important decisions. Presently, many of these systems are proprietary or otherwise unavailable for scrutiny from the public. As the novelty of generative AI tools like ChatGPT fuels a rush to incorporate new systems into more and more of our lives, understanding how to identify AI bias is the first step toward systemic change. +
++Abby Ohlheiser is a freelance reporter and editor who writes about technology, religion, and culture. +
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Reddit is killing third-party applications (and itself). Read more in the comments. - submitted by /u/JokeSentinel
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Reddit is killing third-party applications (and itself). Read more in the comments. - submitted by /u/JokeSentinel
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When you go to church in the morning you say, “Amen.” -
++When you go to church in the afternoon you say, “Pmen.” +
+ submitted by /u/vedicsun
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Did you hear about Apple’s new VR headset? -
++They’re called the iGlasses +
+ submitted by /u/sheeeeeez
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If women want a guy who is taller than them… -
++why do they care if he has hair on top of his head? +
+ submitted by /u/2Agile2Furious
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