FAM111 protease activity undermines cellular fitness and is amplified by gain-of-function mutations in human disease

Dominant missense mutations in the human serine protease FAM111A underlie perinatally lethal gracile bone dysplasia and Kenny-Caffey syndrome, yet how FAM111A mutations lead to disease is not known. We show that FAM111A proteolytic activity suppresses DNA replication and transcription by displacing key effectors of these processes from chromatin, triggering rapid programmed cell death by Caspase-dependent apoptosis to potently undermine cell viability. Patient-associated point mutations in FAM111A exacerbate these phenotypes by hyperactivating its intrinsic protease activity. Moreover, FAM111A forms a complex with the uncharacterized homologous serine protease FAM111B, point mutations in which cause a hereditary fibrosing poikiloderma syndrome, and we demonstrate that disease-associated FAM111B mutants display amplified proteolytic activity and phenocopy the cellular impact of deregulated FAM111A catalytic activity. Thus, patient-associated FAM111A and FAM111B mutations may drive multisystem disorders via a common gain-of-function mechanism that relieves inhibitory constraints on their protease activities to powerfully undermine cellular fitness

Influence of upper ocean on Indian summer monsoon rainfall: studies by observation and NCEP climate forecast system(CFSv2)

This study explores the role played by ocean processes in influencing Indian summer monsoon rainfall (ISMR) and compares the observed findings with National Centers for Environmental Prediction (NCEP)-coupled model Climate Forecast System, version 2 (CFSv2). The excess and deficit ISMR clearly brings out the distinct signatures in sea surface height (SSH) anomaly, thermocline and mixed layer depth over north Indian Ocean. CFSv2 is successful in simulating SSH anomalies, especially over Arabian Sea and Bay of Bengal region. CFSv2 captures observed findings of SSH anomalies during flood and drought (e.g., Rossby wave propagation which reaches western Bay of Bengal (BoB) during flood years, Rossby wave propagation which did not reach western BoB during drought). It highlights the ability of CFSv2 to simulate the basic ocean processes which governs the SSH variability. These differences are basically generated by upwelling and downwelling caused by the equatorial and coastal Kelvin and Rossby waves, thereby causing difference in SSH anomaly and thermocline, and subsequently modifying the convection centers, which dictates precipitation over the Indian subcontinent region. Since the observed SSH anomaly and thermal structure show distinct characteristic features with respect to strong and weak ISMR variability, the assimilation of real ocean data in terms of satellite products (like SSHA from AVISO/SARAL) bestow great promise for the future improvement

An observing system simulation experiment for Indian Ocean surface pCO2 measurements

An observing system simulation experiment (OSSE) is conducted to identify potential locations for making surface ocean pCO2 measurements in the Indian Ocean using the Bayesian Inversion method. As of the SOCATv3 release, the pCO2 data is limited in the Indian Ocean. To improve our modeling of this region, we need to identify where and what observation systems would produce the most good or benefit for their cost. The potential benefits of installing pCO2 sensors in the existing RAMA and OMNI moorings of the Indian Ocean, the potential of Bio-Argo floats (with pH measurements), and the implementation of the ship of opportunity program (SOOP) for underway sampling of pCO2 are evaluated. A cost function of dissolved inorganic carbon as a model state vector and CO2 flux mismatch as the source of error is minimized, and the basin-wide CO2 flux uncertainty reduction is estimated for different seasons. The maximum flux uncertainty reduction achievable by installing pCO2 sensors in the existing RAMA and OMNI moorings is limited to 30% during different seasons. One may consider that around 20 Bio-Argos are still the right choice over installing mooring based pCO2 sensors and achieve uncertainty reduction up to 50% with additional benefit of profiling the sub-surface upto 1000 & ndash;2000 m. However, a single track SOOP has the potential to reduce the uncertainty by approximately 62%. This study identifies vital RAMA and OMNI moorings and SOOP tracks for observing Indian Ocean pCO2. Plain Language Summary. Surface ocean partial pressure of CO2 (pCO2) information is vital for estimating sea-to-air CO2 exchanges. This parameter is least available from the Indian Ocean as compared to other global tropical and southern oceans. There has been no effort made so far to measure surface ocean pCO2 in the Indian Ocean with routine monitoring such as by mounting instruments to moorings or by underway sampling via any ship of opportunity program. Therefore there is a considerable demand to start pCO2 observations in the Indian Ocean. However, one key question that emerges is where to deploy pCO2 instruments in the Indian Ocean to learn the most with limited resources. This study addresses this question with inverse modeling techniques. The study finds that the existing moorings of the Indian Ocean are capable of hosting pCO2 sensors, and data from those are useful to reduce the uncertainty in the surface sea-to-air CO2 flux estimation by a quarter magnitude. In contrast, the Bio-Argo floats with pH sensors, and the ship of opportunity underway sampling of pCO2 may benefit from reducing the same up to 50% and 62%, respectively

Biological production in the Indian Ocean upwelling zones – Part 1: refined estimation via the use of a variable compensation depth in ocean carbon models

Biological modelling approach adopted by the Ocean Carbon-Cycle Model Intercomparison Project (OCMIP-II) provided amazingly simple but surprisingly accurate rendition of the annual mean carbon cycle for the global ocean. Nonetheless, OCMIP models are known to have seasonal biases which are typically attributed to their bulk parameterisation of compensation depth. Utilising the criteria of surface Chl a-based attenuation of solar radiation and the minimum solar radiation required for production, we have proposed a new parameterisation for a spatially and temporally varying compensation depth which captures the seasonality in the production zone reasonably well. This new parameterisation is shown to improve the seasonality of CO2 fluxes, surface ocean pCO2, biological export and new production in the major upwelling zones of the Indian Ocean. The seasonally varying compensation depth enriches the nutrient concentration in the upper ocean yielding more faithful biological exports which in turn leads to accurate seasonality in the carbon cycle. The export production strengthens by  ∼ 70 % over the western Arabian Sea during the monsoon period and achieves a good balance between export and new production in the model. This underscores the importance of having a seasonal balance in the model export and new productions for a better representation of the seasonality of the carbon cycle over upwelling regions. The study also implies that both the biological and solubility pumps play an important role in the Indian Ocean upwelling zones

Matched Cohort Study of Convalescent COVID-19 Plasma Treatment in Severely or Life Threateningly Ill COVID-19 Patients.

BACKGROUND: The utility of convalescent coronavirus disease 2019 (COVID-19) plasma (CCP) in the current pandemic is not well defined. We sought to evaluate the safety and efficacy of CCP in severely or life threateningly ill COVID-19 patients when matched with a contemporaneous cohort. METHODS: Patients with severe or life-threatening COVID-19 were treated with CCP according to Food and Drug Administration criteria, prioritization by an interdisciplinary team, and based on CCP availability. Individual-level matched controls (1:1) were identified from patients admitted during the prior month when no CCP was available. The safety outcome was freedom from adverse transfusion reaction, and the efficacy outcome was a composite of death or worsening O RESULTS: Study patients (n = 94, 47 matched pairs) were 62% male with a mean age of 58, and 98% (90/94) were minorities (53% Hispanic, 45% Black, non-Hispanic) in our inner-city population. Seven-day composite and mortality outcomes suggested a nonsignificant benefit in CCP-treated patients (adjusted hazard ratio [aHR], 0.70; 95% CI, 0.23-2.12; CONCLUSIONS: In this short-term matched cohort study, transfusion with CCP was safe and showed a nonsignificant association with study outcomes. Randomized and larger trials to identify appropriate timing and dosing of CCP in COVID-19 are warranted. TRIAL REGISTRATION:  ClinicalTrials.gov Identifier: NCT04420988

SCAI promotes error-free repair of DNA interstrand crosslinks via the Fanconi anemia pathway

DNA interstrand crosslinks (ICLs) are cytotoxic lesions that threaten genome integrity. The Fanconi anemia (FA) pathway orchestrates ICL repair during DNA replication, with ubiquitylated FANCI-FANCD2 (ID2) marking the activation step that triggers incisions on DNA to unhook the ICL. Restoration of intact DNA requires the coordinated actions of polymerase zeta (Pol zeta)-mediated translesion synthesis (TLS) and homologous recombination (HR). While the proteins mediating FA pathway activation have been well characterized, the effectors regulating repair pathway choice to promote error-free ICL resolution remain poorly defined. Here, we uncover an indispensable role of SCAI in ensuring error-free ICL repair upon activation of the FA pathway. We show that SCAI forms a complex with Pol zeta and localizes to ICLs during DNA replication. SCAI-deficient cells are exquisitely sensitive to ICL-inducing drugs and display major hallmarks of FA gene inactivation. In the absence of SCAI, HR-mediated ICL repair is defective, and breaks are instead re-ligated by polymerase theta-dependent microhomology-mediated end-joining, generating deletions spanning the ICL site and radial chromosomes. Our work establishes SCAI as an integral FA pathway component, acting at the interface between TLS and HR to promote error-free ICL repair.Genome Instability and Cance

Screening COVID-19 by Swaasa AI platform using cough sounds: a cross-sectional study

Abstract The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than six million lives to date and therefore, needs a robust screening technique to control the disease spread. In the present study we created and validated the Swaasa AI platform, which uses the signature cough sound and symptoms presented by patients to screen and prioritize COVID-19 patients. We collected cough data from 234 COVID-19 suspects to validate our Convolutional Neural Network (CNN) architecture and Feedforward Artificial Neural Network (FFANN) (tabular features) based algorithm. The final output from both models was combined to predict the likelihood of having the disease. During the clinical validation phase, our model showed a 75.54% accuracy rate in detecting the likely presence of COVID-19, with 95.45% sensitivity and 73.46% specificity. We conducted pilot testing on 183 presumptive COVID subjects, of which 58 were truly COVID-19 positive, resulting in a Positive Predictive Value of 70.73%. Due to the high cost and technical expertise required for currently available rapid screening methods, there is a need for a cost-effective and remote monitoring tool that can serve as a preliminary screening method for potential COVID-19 subjects. Therefore, Swaasa would be highly beneficial in detecting the disease and could have a significant impact in reducing its spread