Assessment of respiratory function in infants and young children wearing face masks during the COVID-19 pandemic

Importance: Face masks have been associated with effective prevention of diffusion of viruses via droplets. However, the use of face masks among children, especially those aged younger than 3 years, is debated, and the US Centers for Disease Control and American Academy of Physicians recommend the use of face mask only among individuals aged 3 years or older.Objective: To examine whether the use of surgical facial masks among children is associated with episodes of oxygen desaturation or respiratory distress.Design, Setting, and Participants: This cohort study was conducted from May through June 2020 in a secondary-level hospital pediatric unit in Italy. Included participants were 47 healthy children divided by age (ie, group A, aged ≤24 months, and group B, aged >24 months to ≤144 months). Data were analyzed from May through June 2020.Interventions: All participants were monitored every 15 minutes for changes in respiratory parameters for the first 30 minutes while not wearing a surgical face mask and for the next 30 minutes while wearing a face mask. Children aged 24 months and older then participated in a walking test for 12 minutes.Main Outcomes and Measures: Changes in respiratory parameters during the use of surgical masks were evaluated.Results: Among 47 children, 22 children (46.8%) were aged 24 months or younger (ie, group A), with 11 boys (50.0%) and median (interquartile range [IQR]) age 12.5 (10.0-17.5) months, and 25 children (53.2%) were aged older than 24 months to 144 months or younger, with 13 boys (52.0%) and median (IQR) age 100.0 (72.0-120.0) months. During the first 60 minutes of evaluation in the 2 groups, there was no significant change in group A in median (IQR) partial pressure of end-tidal carbon dioxide (Petco2; 33.0 [32.0-34.0] mm Hg; P for Kruskal Wallis =.59), oxygen saturation (Sao2; 98.0% [97.0%-99.0%]; P for Kruskal Wallis =.61), pulse rate (PR; 130.0 [115.0-140.0] pulsations/min; P for Kruskal Wallis =.99), or respiratory rate (RR; 30.0 [28.0-33.0] breaths/min; P for Kruskal Wallis =.69) or for group B in median (IQR) Petco2 (36.0 [34.0-38.0] mm Hg; P for Kruskal Wallis =.97), Sao2 (98.0% [97.0%-98.0%]; P for Kruskal Wallis =.52), PR (96.0 [84.0-104.5] pulsations/min; P for Kruskal Wallis test=.48), or RR (22.0 [20.0-25.0] breaths/min; P for Kruskal Wallis =.55). After the group B walking test, compared with before the walking test, there was a significant increase in median (IQR) PR (96.0 [84.0-104.5] pulsations/min vs 105.0 [100.0-115.0] pulsations/min; P<.02) and RR (22.0 [20.0-25.0] breaths/min vs 26.0 [24.0-29.0] breaths/min; P<.05).Conclusions and Relevance: This cohort study among infants and young children in Italy found that the use of facial masks was not associated with significant changes in Sao2 or Petco2, including among children aged 24 months and younger

Genetic variants associated with gastrointestinal symptoms in Fabry disease.

Gastrointestinal symptoms (GIS) are often among the earliest presenting events in Fabry disease (FD), an X-linked lysosomal disorder caused by the deficiency of α-galactosidase A. Despite recent advances in clinical and molecular characterization of FD, the pathophysiology of the GIS is still poorly understood. To shed light either on differential clinical presentation or on intervariability of GIS in FD, we genotyped 1936 genetic markers across 231 genes that encode for drug-metabolizing enzymes and drug transport proteins in 49 FD patients, using the DMET Plus platform. All nine single nucleotide polymorphisms (SNPs) mapped within four genes showed statistically significant differences in genotype frequencies between FD patients who experienced GIS and patients without GIS: ABCB11 (odd ratio (OR) = 18.07, P = 0,0019; OR = 8.21, P = 0,0083; OR=8.21, P = 0,0083; OR = 8.21, P = 0,0083),SLCO1B1 (OR = 9.23, P = 0,0065; OR = 5.08, P = 0,0289; OR = 8.21, P = 0,0083), NR1I3 (OR = 5.40, P = 0,0191) and ABCC5 (OR = 14.44, P = 0,0060). This is the first study that investigates the relationships between genetic heterogeneity in drug absorption, distribution, metabolism and excretion (ADME) related genes and GIS in FD. Our findings provide a novel genetic variant framework which warrants further investigation for precision medicine in FD

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Multiple Myeloma Impairs Bone Marrow Localization of Effector Natural Killer Cells by Altering the Chemokine Microenvironment.

Natural killer (NK) cells are key innate immune effectors against multiple myeloma, their activity declining in multiple myeloma patients with disease progression. To identify the mechanisms underlying NK cell functional impairment, we characterized the distribution of functionally distinct NK cell subsets in the bone marrow of multiple myeloma-bearing mice. Herein we report that the number of KLRG1(-) NK cells endowed with potent effector function rapidly and selectively decreases in bone marrow during multiple myeloma growth, this correlating with decreased bone marrow NK cell degranulation in vivo. Altered NK cell subset distribution was dependent on skewed chemokine/chemokine receptor axes in the multiple myeloma microenvironment, with rapid downmodulation of the chemokine receptor CXCR3 on NK cells, increased CXCL9 and CXCL10, and decreased CXCL12 expression in bone marrow. Similar alterations in chemokine receptor/chemokine axes were observed in patients with multiple myeloma. Adoptive transfer experiments demonstrated that KLRG1(-) NK cell migration to the bone marrow was more efficient in healthy than multiple myeloma-bearing mice. Furthermore, bone marrow localization of transferred CXCR3-deficient NK cells with respect to wild type was enhanced in healthy and multiple myeloma-bearing mice, suggesting that CXCR3 restrains bone marrow NK cell trafficking. Our results indicate that multiple myeloma-promoted CXCR3 ligand upregulation together with CXCL12 downmodulation act as exit signals driving effector NK cells outside the bone marrow, thus weakening the antitumor immune response at the primary site of tumor growt

Serum IgG levels in children 6 months after SARS-CoV-2 infection and comparison with adults

Since the outbreak of SARS-CoV-2 among the population has occurred quite recently, there is a lack of evidence on the long-term duration of antibody response, especially in children. It is therefore crucial to clarify this aspect, considering its implications in the development of successful surveillance strategies, therapies, and vaccinations. The aim of this study was to assess the antibody response in a children group after SARS-CoV-2 infection, and to compare it with that of their parents affected by SARS-CoV-2 infection. We enrolled 12 children and their parents, both groups being affected by COVID-19 in April 2020. In the children's group, we collected real-time RT-PCR cycle threshold (Ct) values and gene characterization of first nasal-throat swab at the time of diagnosis (T0); 30 days after the diagnosis (T30), we performed blood tests to detect anti-SARS-CoV-2 IgM and IgG. Finally, 180 days after the diagnosis (T180), we measured anti-SARS-CoV-2 IgG in both children and parents. In children, antibody levels declined significantly at 180 days (T180) after first measurement (T30). There were no significant differences in IgG level related to age, sex, and clinical manifestations. We found a significant correlation between IgG titers at T30 and Ct value of gene N. Children showed a lower level of antibodies against SARS-CoV-2 at T180 compared to their parents.Conclusion: Antibody responses in children waned 180 days after SARS-CoV-2 infection, and at the same time, their parents showed a different antibody response to the virus. These results highlight that serological tests should be used with caution in surveillance strategies among the general population. What is known: • Currently is not known how long antibody response will be maintained or if it protects from reinfection. • Recent reports in adults suggest that antibodies to SARS-CoV-2 declined several months after infection, but data are missing in pediatric age. What is new: • We showed that antibody responses to SARS-CoV-2 wane several months after infection also in children with quantitative differences in antibody levels between children and adults. • In this context, serological tests should be used with caution in surveillance strategie

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License