Relationship between emergency department and inpatient occupancy and the likelihood of an emergency admission: a retrospective hospital database study.

BACKGROUND: We investigate whether admission from a consultant-led ED is associated with ED occupancy or crowding and inpatient (bed) occupancy. METHODS: We used general additive logistic regression to explore the relationship between the probability of an ED patient being admitted, ED crowding and inpatient occupancy levels. We adjust for patient, temporal and attendance characteristics using data from 13 English NHS Hospital Trusts in 2019. We define quintiles of occupancy in ED and for four types of inpatients: emergency, overnight elective, day case and maternity. RESULTS: Compared with periods of average occupancy in ED, a patient attending during a period of very high (upper quintile) occupancy was 3.3% less likely (relative risk (RR) 0.967, 95% CI 0.958 to 0.977) to be admitted, whereas a patient arriving at a time of low ED occupancy was 3.9% more likely (RR 1.039 95% CI 1.028 to 1.050) to be admitted. When the number of overnight elective, day-case and maternity inpatients reaches the upper quintile then the probability of admission from ED rises by 1.1% (RR 1.011 95% CI 1.001 to 1.021), 3.8% (RR 1.038 95% CI 1.025 to 1.051) and 1.0% (RR 1.010 95% CI 1.001 to 1.020), respectively. Compared with periods of average emergency inpatient occupancy, a patient attending during a period of very high emergency inpatient occupancy was 1.0% less likely (RR 0.990 95% CI 0.980 to 0.999) to be admitted and a patient arriving at a time of very low emergency inpatient occupancy was 0.8% less likely (RR 0.992 95% CI 0.958 to 0.977) to be admitted. CONCLUSIONS: Admission thresholds are modestly associated with ED and inpatient occupancy when these reach extreme levels. Admission thresholds are higher when the number of emergency inpatients is particularly high. This may indicate that riskier discharge decisions are taken when beds are full. Admission thresholds are also high when pressures within the hospital are particularly low, suggesting the potential to safely reduce avoidable admissions.

Therapeutic interventions on human breast cancer xenografts promote systemic dissemination of oncogenes.

Metastatic dissemination following successful treatment of the primary tumour remains a common cause of death. There is mounting evidence that therapeutic interventions themselves may promote development of metastatic disease. We earlier reported that cell-free chromatin particles (cfChPs) released from dying cancer cells are potentially oncogenic. Based on this observation we hypothesized that therapeutic interventions may lead to the release of cfChPs from therapy induced dying cancer cells which could be carried via the blood stream to distant organs to transform healthy cells into new cancers that would masquerade as metastasis. To test this hypothesis, we generated xenografts of MDA-MB-231 human breast cancer cells in severe combined immune-deficient mice, and using immuno-fluorescence and FISH analysis looked for cfChPs in their brain cells. We detected multiple human DNA signals representing cfChPs in nuclei of brain cells of mice which co-localized with eight human onco-proteins. No intact MDA-MB-231 cells were detected. The number of co-localizing human DNA and human c-Myc signals increased dramatically following treatment with chemotherapy, localized radiotherapy or surgery, which could be prevented by concurrent treatment with three different cfChPs deactivating agents. These results suggest that therapeutic interventions lead to the release cfChPs from therapy induced dying cancer cells carrying oncogenes and are transported via the blood stream to brain cells to potentially transform them to generate new cancers that would appear as metastases. cfChPs induced metastatic spread of cancer is preventable by concurrent treatment with agents that deactivate cfChPs.

Correction: Therapeutic interventions on human breast cancer xenografts promote systemic dissemination of oncogenes.

[This corrects the article DOI: 10.1371/journal.pone.0298042.].

Spontaneous early pregnancy with very low levels of progesterone during controlled ovarian stimulation-A case report.

One of the most widely accepted axioms of reproductive biology is that pregnancy requires the sole support of progesterone, without which pregnancy cannot be established or maintained. We report a rare case of ongoing third trimester pregnancy in a 41-year-old woman, where early gestational period was maintained despite extremely low progesterone levels of <1 ng/ml, and was discovered during controlled ovarian hyperstimulation (COS) for in vitro fertilization (IVF). She was started on ovarian stimulation (OS) with gonadotrophins after a withdrawal bleed during lactational amenorrhea. Baseline investigations on day 2 of the menstruation confirmed low serum estradiol and progesterone levels (<1 ng/ml). After 5 days of stimulation, on ultrasound scan, a sac-like structure was seen in the uterine cavity. Beta hCG levels were measured and confirmed the presence of early pregnancy despite progesterone levels below 1 ng/ml. COS was stopped, and progesterone support was started. Subsequent scan confirmed live intrauterine pregnancy and the fetus is currently growing uneventfully at 31 weeks of gestation (at the time of writing this report).

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

Investigating organic nitrogen production in activated sludge process: Size fraction and biodegradability.

The effect of sludge retention time (SRT) on the production of organic nitrogen (ON) fractions (particulate, colloidal and soluble) and the biodegradability of produced soluble ON in an activated sludge process was investigated. Synthetic wastewater with no ON was fed to the four laboratory-scale reactors operated at SRTs of 2, 5, 10 and 20 d, respectively. Effluent ON from each reactor was fractionated into particulate, colloidal, and soluble ON (pON, cON, and sON). The effluent total ON contained 5.7 to 11.9 mg/L pON, 3.6 to 3.8 mg/L cON, and 2.3 to 4.6 mg/L sON. cON fraction can be larger than sON fraction in the secondary effluent. Therefore, besides focusing on sON, water resource recovery facilities aiming to meet stricter effluent TN limits should also identify appropriate technologies to target cON. More than 50% of effluent sON was biodegradable under SRTs of 2, 5, and 10 d but the biodegradability decreased to 31% at 20-d SRT. Large fractions of non-biodegradable sON (69%) at SRT of 20-d could be contributed by extracellular polymeric substances and soluble microbial products, specifically biomass associated products due to endogenous respiration. Thus, sON generated at long SRTs may take longer to decompose in receiving waters.

High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs.

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts.

It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene1. The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches2-5. For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases6-8. This includes muscle biopsies from patients with undiagnosed rare muscle disorders6,9, and cultured fibroblasts from patients with mitochondrial disorders7. However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.

A cross-sectional comparative study of gut bacterial community of Indian and Finnish children.

The human gut microbiome plays a crucial role in the compositional development of gut microbiota. Though well documented in western pediatrics population, little is known about how various host conditions affect populations in different geographic locations such as the Indian subcontinent. Given the impact of distinct environmental conditions, our study assess the gut bacterial diversity of a small cohort of Indian and Finnish children and investigated the influence of FUT2 secretor status and birth mode on the gut microbiome of these populations. Using multiple profiling techniques, we show that the gut bacterial community structure in 13-14-year-old Indian (n = 47) and Finnish (n = 52) children differs significantly. Specifically, Finnish children possessed higher Blautia and Bifidobacterium, while genera Prevotella and Megasphaera were predominant in Indian children. Our study also demonstrates a strong influence of FUT2 and birth mode variants on specific gut bacterial taxa, influence of which was noticed to differ between the two populations under study.

Prospective enterprise-level molecular genotyping of a cohort of cancer patients.

Ongoing cancer genome characterization studies continue to elucidate the spectrum of genomic abnormalities that drive many cancers, and in the clinical arena assessment of the driver genetic alterations in patients is playing an increasingly important diagnostic and/or prognostic role for many cancer types. However, the landscape of genomic abnormalities is still unknown for less common cancers, and the influence of specific genotypes on clinical behavior is often still unclear. To address some of these deficiencies, we developed Profile, a prospective cohort study to obtain genomic information on all patients at a large tertiary care medical center for cancer-related care. We enrolled patients with any cancer diagnosis, and, for each patient (unselected for cancer site or type) we applied mass spectrometric genotyping (OncoMap) of 471 common recurrent mutations in 41 cancer-related genes. We report the results of the first 5000 patients, of which 26% exhibited potentially actionable somatic mutations. These observations indicate the utility of genotyping in advancing the field of precision oncology.