Integral evaluation of effective conversion of sewage sludge from WWTP into highly porous activated carbon

Urban sewage sludge (SL) is a major concern due to the number of environmental problems it causes. Its application for different purposes is strictly regulated, limiting the possibilities of recycling and reusing this material. Thus, in this work, a complete study of a simple method to convert SL into activated carbon (AC) was carried out. The comprehensive study involves an evaluation of the main process parameters, such as the activating agent (AA) content (25 %, 33 %, 50 %), using the lowest amount of AA as novelty, different pyrolysis temperatures (600 and 800 °C), and purification conditions (6 M HCl:AC ratio, v:w). Under controlled and optimised conditions and through a single combined activation and pyrolysis step followed by acid purification, ACs with well-developed porosity can be obtained. Surface area values of around 870 m2/g and over 60 % carbon content were achieved, demonstrating that the prepared ACs could have applications in a wide variety of fields as high-value products. As an innovative aspect in this research, the gases streams and liquid effluents generated during the global process were analysed, achieving elimination of over 63 % of the concentration of the chemical elements contained in the SL during the chemical purification stage. Finally, mass, energy, and economic balances were carried out to estimate the production cost of AC derived from SL (<€ 8/kg AC).

Estimation of the contemporary effective population size from SNP data while accounting for mating structure

A new method is developed to estimate the contemporary effective population size (Ne ) from linkage disequilibrium (LD) between SNPs without information on their location, which is the usual scenario in non-model species. The general theory of linkage disequilibrium is extended to include the contribution of full-sibs to the measure of LD, leading naturally to the estimation of Ne in monogamous and polygamous mating systems, as well as in multiparous species, and with non-random distributions of full-sib family size due to selection or other causes. Prediction of confidence intervals for Ne estimates was solved using a small artificial neural network trained on a dataset of over 105 simulation results. The method, implemented in a user-friendly and fast software (currentNe), is able to estimate Ne even in problematic scenarios with large population sizes or small sample sizes and provides confidence intervals that are more consistent than resampling methods.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BACKGROUND

Effective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.

RESULTS

Our results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.

CONCLUSIONS

Different kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.

Cobalt Stabilization through Mesopore Confinement on TiO2 Support for Fischer-Tropsch Reaction

Cobalt supported on mesostructured TiO2 catalysts has been prepared by a wet-impregnation method. The Co/TiO2 catalytic system showed better catalytic performance after support calcination at 380 °C. Co nanoparticles appeared well distributed along the mesopore channels of TiO2. After reduction pretreatment and reaction, a drastic structural change leads to mesopore structure collapse and the dispersion of the Co nanoparticles on the external surface. Along this complex process, Co species first form discrete nanoparticles inside the pore and then diffuse out as the pore collapses. Through this confinement, a strong metal-support interaction effect is hindered, and highly stable metal active sites lead to better performance for Fischer-Tropsch synthesis reaction toward C5+ products.

An empirical evaluation of the estimation of inbreeding depression from molecular markers under suboptimal conditions

Inbreeding depression (ID), the reduction in fitness due to inbreeding, is typically measured by the regression of the phenotypic values of individuals for a particular trait on their corresponding inbreeding coefficients (F). While genealogical records can provide these coefficients, they may be unavailable or incomplete, making molecular markers a useful alternative. The power to detect ID and its accuracy depend on the variation of F values of individuals, the sample sizes available, and the accuracy in the estimation of individual fitness traits and F values. In this study, we used Drosophila melanogaster to evaluate the effectiveness of molecular markers in estimating ID under suboptimal conditions. We generated two sets of 100 pairs of unrelated individuals from a large panmictic population and mated them for two generations to produce non-inbred and unrelated individuals (F = 0) and inbred individuals (full-sib progeny; F = 0.25). Using these expected genealogical F values, we calculated inbreeding depression for two fitness-related traits, pupae productivity and competitive fitness. We then sequenced the males from 17 non-inbred pairs and 17 inbred pairs to obtain their genomic inbreeding coefficients and estimate ID for the two traits. The scenario assumed was rather restrictive in terms of estimation of ID because: (1) the individuals belonged to the same generation of a large panmictic population, leading to low variation in individual F coefficients; (2) the sample sizes were small; and (3) the traits measured depended on both males and females while only males were sequenced. Despite the challenging conditions of our study, we found that molecular markers provided estimates of ID that were comparable to those obtained from simple pedigree estimations with larger sample sizes. The results therefore suggest that genomic measures of inbreeding are useful to provide estimates of inbreeding depression even under very challenging scenarios.

A comparison of marker-based estimators of inbreeding and inbreeding depression

BACKGROUND

The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (F_LH1 and F_LH2), VanRaden (F_VR1 and F_VR2), Yang and colleagues (F_YA1 and F_YA2), marker homozygosity (F_HOM), runs of homozygosity (F_ROH) and estimates based on pedigree (F_PED) in comparison with estimates obtained from IBD measures (F_IBD).

RESULTS

If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with F_IBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with F_IBD is generally obtained by F_LH1 and the best estimator of ΔID is F_YA2. The estimators F_VR2 and F_LH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with F_IBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (F_HOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (F_ROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (F_PED) show a lower correlation with F_IBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.

CONCLUSIONS

When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with F_IBD and provide good estimates of ΔID. When base population allele frequencies are unknown, F_LH1 is the marker frequency-based estimator that is most correlated with F_IBD, and F_YA2 provides the most accurate estimates of ΔID. Estimates from F_ROH are also very precise in most scenarios. The estimators F_VR2 and F_LH2 have the poorest performances.

SAFETY AND EFFICACY OF THYMIC PEPTIDES IN THE TREATMENT OF HOSPITALIZED COVID-19 PATIENTS IN HONDURAS

Coronavirus disease 2019 (Covid-19) active cases continue to demand the development of safe and effective treatments. This is the first clinical trial to evaluate the safety and efficacy of oral thymic peptides. ; We conducted a nonrandomized phase 2 trial with a historic control group to evaluate the safety and efficacy of a daily 250-mg oral dose of thymic peptides in the treatment of hospitalized Covid-19 patients. Comparisons based on standard care from registry data were performed after propensity score matching. The primary outcomes were survival, time to recovery, and number of participants with treatment-related adverse events or side effects by day 20. ; A total of 44 patients were analyzed in this study: 22 in the thymic peptide group and 22 in the standard care group. There were no deaths in the intervention group compared to 24% mortality in standard care by day 20 (log-rank P=0.02). Kaplan-Meier analysis showed a significantly shorter time to recovery by day 20 in the thymic peptide group than in the standard care group (median, 6 days vs. 12 days; hazard ratio for recovery, 2.75 [95% confidence interval, 1.34 to 5.62]; log-rank P=0.002). No side effects or adverse events were reported. ; In patients hospitalized with Covid-19, the use of thymic peptides resulted in no side effects, adverse events, or deaths by day 20. Compared with the registry data, a significantly shorter time to recovery and mortality reduction were measured.

The estimates of effective population size based on linkage disequilibrium are virtually unaffected by natural selection

The effective population size (N_e) is a key parameter to quantify the magnitude of genetic drift and inbreeding, with important implications in human evolution. The increasing availability of high-density genetic markers allows the estimation of historical changes in N_e across time using measures of genome diversity or linkage disequilibrium between markers. Directional selection is expected to reduce diversity and N_e, and this reduction is modulated by the heterogeneity of the genome in terms of recombination rate. Here we investigate by computer simulations the consequences of selection (both positive and negative) and recombination rate heterogeneity in the estimation of historical N_e. We also investigate the relationship between diversity parameters and N_e across the different regions of the genome using human marker data. We show that the estimates of historical N_e obtained from linkage disequilibrium between markers (N_eLD) are virtually unaffected by selection. In contrast, those estimates obtained by coalescence mutation-recombination-based methods can be strongly affected by it, which could have important consequences for the estimation of human demography. The simulation results are supported by the analysis of human data. The estimates of N_eLD obtained for particular genomic regions do not correlate, or they do it very weakly, with recombination rate, nucleotide diversity, proportion of polymorphic sites, background selection statistic, minor allele frequency of SNPs, loss of function and missense variants and gene density. This suggests that N_eLD measures mainly reflect demographic changes in population size across generations.

The inference of the demographic history of populations is of great relevance in evolutionary biology. This inference can be made from genomic data using coalescence methods or linkage disequilibrium methods. However, the assessment of these methods is usually made assuming neutrality (absence of selection). Here we show by computer simulations and analyses of human data that the estimates of historical effective population size obtained from linkage disequilibrium between markers are virtually unaffected by natural selection, either positive or negative. In contrast, estimates obtained by coalescence mutation-recombination-based methods can be strongly affected by it, which could have important consequences for recent estimations of human demography.

Estimates of recent and historical effective population size in turbot, seabream, seabass and carp selective breeding programmes

Background

The high fecundity of fish species allows intense selection to be practised and therefore leads to fast genetic gains. Based on this, numerous selective breeding programmes have been started in Europe in the last decades, but in general, little is known about how the base populations of breeders have been built. Such knowledge is important because base populations can be created from very few individuals, which can lead to small effective population sizes and associated reductions in genetic variability. In this study, we used genomic information that was recently made available for turbot (Scophthalmus maximus), gilthead seabream (Sparus aurata), European seabass (Dicentrarchus labrax) and common carp (Cyprinus carpio) to obtain accurate estimates of the effective size for commercial populations.

Methods

Restriction-site associated DNA sequencing data were used to estimate current and historical effective population sizes. We used a novel method that considers the linkage disequilibrium spectrum for the whole range of genetic distances between all pairs of single nucleotide polymorphisms (SNPs), and thus accounts for potential fluctuations in population size over time.

Results

Our results show that the current effective population size for these populations is small (equal to or less than 50 fish), potentially putting the sustainability of the breeding programmes at risk. We have also detected important drops in effective population size about five to nine generations ago, most likely as a result of domestication and the start of selective breeding programmes for these species in Europe.

Conclusions

Our findings highlight the need to broaden the genetic composition of the base populations from which selection programmes start, and suggest that measures designed to increase effective population size within all farmed populations analysed here should be implemented in order to manage genetic variability and ensure the sustainability of the breeding programmes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00680-9.

Long-term exhaustion of the inbreeding load in Drosophila melanogaster

Inbreeding depression, the decline in fitness of inbred individuals, is a ubiquitous phenomenon of great relevance in evolutionary biology and in the fields of animal and plant breeding and conservation. Inbreeding depression is due to the expression of recessive deleterious alleles that are concealed in heterozygous state in noninbred individuals, the so-called inbreeding load. Genetic purging reduces inbreeding depression by removing these alleles when expressed in homozygosis due to inbreeding. It is generally thought that fast inbreeding (such as that generated by full-sib mating lines) removes only highly deleterious recessive alleles, while slow inbreeding can also remove mildly deleterious ones. However, a question remains regarding which proportion of the inbreeding load can be removed by purging under slow inbreeding in moderately large populations. We report results of two long-term slow inbreeding Drosophila experiments (125-234 generations), each using a large population and a number of derived lines with effective sizes about 1000 and 50, respectively. The inbreeding load was virtually exhausted after more than one hundred generations in large populations and between a few tens and over one hundred generations in the lines. This result is not expected from genetic drift alone, and is in agreement with the theoretical purging predictions. Computer simulations suggest that these results are consistent with a model of relatively few deleterious mutations of large homozygous effects and partially recessive gene action.

Highly pleiotropic variants of human traits are enriched in genomic regions with strong background selection

Recent studies have shown the ubiquity of pleiotropy for variants affecting human complex traits. These studies also show that rare variants tend to be less pleiotropic than common ones, suggesting that purifying natural selection acts against highly pleiotropic variants of large effect. Here, we investigate the mean frequency, effect size and recombination rate associated with pleiotropic variants, and focus particularly on whether highly pleiotropic variants are enriched in regions with putative strong background selection. We evaluate variants for 41 human traits using data from the NHGRI-EBI GWAS Catalog, as well as data from other three studies. Our results show that variants involving a higher degree of pleiotropy tend to be more common, have larger mean effect sizes, and contribute more to heritability than variants with a lower degree of pleiotropy. This is consistent with the fact that variants of large effect and frequency are more likely detected by GWAS. Using data from four different studies, we also show that more pleiotropic variants are enriched in genome regions with stronger background selection than less pleiotropic variants, suggesting that highly pleiotropic variants are subjected to strong purifying selection. From the above results, we hypothesized that a number of highly pleiotropic variants of low effect/frequency may pass undetected by GWAS.

The value of genomic relationship matrices to estimate levels of inbreeding

BACKGROUND

Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (FNEJ), the Li and Horvitz matrix based on excess of homozygosity (FL&H), and the VanRaden (methods 1, FVR1, and 2, FVR2) and Yang (FYAN) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs.

RESULTS

Except for FNEJ, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both FNEJ and FL&H led to sensible results but this was not the case for FVR1, FVR2 and FYAN. When variability has increased relative to the base, FVR1, FVR2 and FYAN can indicate that it decreased. In fact, based on FYAN, variability is not expected to increase. When variability has decreased, FVR1 and FVR2 can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign.

CONCLUSIONS

Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

On the estimation of inbreeding depression using different measures of inbreeding from molecular markers

The inbreeding coefficient (F) of individuals can be estimated from molecular marker data, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. These different measures of F can then be used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some recent simulation studies have investigated the accuracy of this estimation with contradictory results. Whereas some studies suggest that estimates of inbreeding from ROH account more accurately for ID, others suggest that inbreeding measures from SNP-by-SNP homozygosity giving a large weight to rare alleles are more accurate. Here, we try to give more light on this issue by carrying out a set of computer simulations considering a range of population genetic parameters and population sizes. Our results show that the previous studies are indeed not contradictory. In populations with low effective size, where relationships are more tight and selection is relatively less intense, F measures based on ROH provide very accurate estimates of ID whereas SNP-by-SNP-based F measures with high weight to rare alleles can show substantial upwardly biased estimates of ID. However, in populations of large effective size, with more intense selection and trait allele frequencies expected to be low if they are deleterious for fitness because of purifying selection, average estimates of ID from SNP-by-SNP-based F values become unbiased or slightly downwardly biased and those from ROH-based F values become slightly downwardly biased. The noise attached to all these estimates, nevertheless, can be very high in large-sized populations. We also investigate the relationship between the different F measures and the homozygous mutation load, which has been suggested as a proxy of inbreeding depression.

An anti-CD6 antibody for the treatment of COVID-19 patients with cytokine-release syndrome: report of three cases

In COVID-19, the inflammatory cytokine-release syndrome is associated with the progression of the disease. Itolizumab is a monoclonal antibody that recognizes human CD6 expressed in activated T cells. The antibody has shown to be safe and efficacious in the treatment of moderate to severe psoriasis. Its effect is associated with the reduction of pro-inflammatory cytokines release, including IFN-γ, IL-6 and TNF-α. Here, we report the outcome of three severe and critically ill COVID-19 patients treated with itolizumab as part of an expanded access protocol. Itolizumab was able to reduce IL-6 concentrations in all the patients. Two of the three patients showed respiratory and radiological improvement and were fully recovered. We hypothesize this anti-inflammatory therapy in addition to antiviral and anticoagulant therapy could reduce COVID-19 associated morbidity and mortality.

Treatment of COVID-19 patients with the anti-CD6 antibody itolizumab

Objectives

COVID‐19 can lead to a hyperinflammatory state. CD6 is a glycoprotein expressed on mature T lymphocytes which is a crucial regulator of the T‐cell activation. Itolizumab is a humanised antibody targeting CD6. Nonclinical and clinical data in autoimmune diseases indicate that it lowers multiple cytokines primarily involving the Th1/Th17 pathway. The primary objective of this study was to assess the impact of itolizumab in arresting the lung function deterioration of COVID‐19 patients. Secondary objectives included safety, duration of ventilation, 14‐day mortality and evaluation of interleukin 6 concentration.

Methods

Patients with confirmed SARS‐CoV‐2 received itolizumab in combination with other therapies included in the national protocol for COVID‐19.

Results

Seventy critical, severe or moderate patients were treated with itolizumab in 10 Cuban hospitals. Median age was 68, and 94% had comorbidities. After 72 h, most patients improved the PO₂/FiO₂ ratio and reduced FiO2 requirements. Ventilation time was 8 days for critical and 1 day for severe cases. Ten patients had related adverse events while 3 subjects developed related serious events. In 30 patients, interleukin 6 decreased in individuals with high level and did not change in those with lower concentration. Fourteen‐day lethality rate was 4% and 18% for moderate and severe patients, respectively. The proportion of moderate or severe patients with ventilation or death at day 14 was 9.8%. Time to treatment, neurological manifestations and biomarkers such as NLR were significantly associated with higher lethality.

Conclusions

The opportune administration of itolizumab might interrupt the hyperinflammatory cascade and prevent COVID‐19 morbidity and mortality.

An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree

The estimation of the inbreeding coefficient (F) is essential for the study of inbreeding depression (ID) or for the management of populations under conservation. Several methods have been proposed to estimate the realized F using genetic markers, but it remains unclear which one should be used. Here we used whole-genome sequence data for 245 individuals from a Holstein cattle pedigree to empirically evaluate which estimators best capture homozygosity at variants causing ID, such as rare deleterious alleles or loci presenting heterozygote advantage and segregating at intermediate frequency. Estimators relying on the correlation between uniting gametes (F_UNI) or on the genomic relationships (F_GRM) presented the highest correlations with these variants. However, homozygosity at rare alleles remained poorly captured. A second group of estimators relying on excess homozygosity (F_HOM), homozygous-by-descent segments (F_HBD), runs-of-homozygosity (F_ROH) or on the known genealogy (F_PED) was better at capturing whole-genome homozygosity, reflecting the consequences of inbreeding on all variants, and for young alleles with low to moderate frequencies (0.10 < . < 0.25). The results indicate that F_UNI and F_GRM might present a stronger association with ID. However, the situation might be different when recessive deleterious alleles reach higher frequencies, such as in populations with a small effective population size. For locus-specific inbreeding measures or at low marker density, the ranking of the methods can also change as F_HBD makes better use of the information from neighboring markers. Finally, we confirmed that genomic measures are in general superior to pedigree-based estimates. In particular, F_PED was uncorrelated with locus-specific homozygosity.

Use of a Humanized Anti-CD6 Monoclonal Antibody (Itolizumab) in Elderly Patients with Moderate COVID-19

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a recent outbreak of coronavirus disease (COVID-19). In Cuba, the first case of COVID-19 was reported on March 11, 2020. Elderly individuals with multiple comorbidities are particularly susceptible to adverse clinical outcomes in the course of SARS-CoV-2 infection. During the outbreak, a local transmission event took place in a nursing home in Villa Clara province, Cuba, in which 19 elderly residents tested positive for SARS-CoV-2.

METHODS

Based on the increased susceptibility to cytokine release syndrome, inducing respiratory and systemic complications in this population, 19 patients were included in an expanded access clinical trial to receive itolizumab, an anti-CD6 monoclonal antibody.

RESULTS

All patients had underlying medical conditions. The product was well tolerated. After the first dose, the course of the disease was favorable, and 18 of the 19 patients (94.7%) were discharged clinically recovered with negative real-time reverse transcription polymerase chain reaction test results at 13 days. After one dose of itolizumab, circulating IL-6 decreased within the first 24-48 h in patients with high baseline values, whereas in patients with low levels, this concentration remained over low values. To preliminarily assess the effect of itolizumab, a control group was selected among the Cuban COVID-19 patients that did not receive immunomodulatory therapy. The control subjects were well matched regarding age, comorbidities, and severity of the disease. The percentage of itolizumab-treated, moderately ill patients who needed to be admitted to the intensive care unit was only one-third of that of the control group not treated with itolizumab. Additionally, treatment with itolizumab reduced the risk of death 10 times as compared with the control group.

CONCLUSION

This study corroborates that the timely use of itolizumab in combination with other antivirals reduces COVID-19 disease worsening and mortality. The humanized antibody itolizumab emerges as a therapeutic alternative for patients with COVID-19. Our results suggest the possible use of itolizumab in patients with cytokine release syndrome from other pathologies.

Recent Demographic History Inferred by High-Resolution Analysis of Linkage Disequilibrium

Inferring changes in effective population size (Ne) in the recent past is of special interest for conservation of endangered species and for human history research. Current methods for estimating the very recent historical Ne are unable to detect complex demographic trajectories involving multiple episodes of bottlenecks, drops, and expansions. We develop a theoretical and computational framework to infer the demographic history of a population within the past 100 generations from the observed spectrum of linkage disequilibrium (LD) of pairs of loci over a wide range of recombination rates in a sample of contemporary individuals. The cumulative contributions of all of the previous generations to the observed LD are included in our model, and a genetic algorithm is used to search for the sequence of historical Ne values that best explains the observed LD spectrum. The method can be applied from large samples to samples of fewer than ten individuals using a variety of genotyping and DNA sequencing data: haploid, diploid with phased or unphased genotypes and pseudohaploid data from low-coverage sequencing. The method was tested by computer simulation for sensitivity to genotyping errors, temporal heterogeneity of samples, population admixture, and structural division into subpopulations, showing high tolerance to deviations from the assumptions of the model. Computer simulations also show that the proposed method outperforms other leading approaches when the inference concerns recent timeframes. Analysis of data from a variety of human and animal populations gave results in agreement with previous estimations by other methods or with records of historical events.