Recent Developments in the Regulation of Heritable Human Genome Editing

In 2018, the Chinese scientist He Jiankui presented his research at the Second International Summit on Human Genome Editing in Hong Kong. While it was intended that he facilitate a workshop, he was instead called on to present his research in heritable human genome editing, where he made the announcement that he had taken great strides in advancement of his research, to the extent that he had gene-edited human embryos and that this had resulted in the live births of two children. While his research ethic and methodology was interrogated, he insisted that two children, twin girls, had been born healthy and that there was another pregnancy (at the time) where birth of a third gene edited child would be imminent. This announcement generated a ripple effect in the scientific community and exposed the gaps in regulation and absence of law relating to the technology. This resulted in a flurry of activity and conversation around regulation of the technology, which scientists stated was not ready for human trials. This article reviews the Third Summit which was held in London in March 2023 and comments on the latest developments in the regulation of heritable human genome editing.

Steinernema shori n. sp., a new entomopathogenic nematode (Nematoda: Steinernematidae) from India

In this study, morphological and molecular features were used to identify a new Steinernema sp. from Chhattisgarh, India. Morphological and molecular features provide evidence for placing the new species into the "bicornutum" clade. The new species is characterized by the following morphological features: infective juveniles with a body length of 587 (494-671) μm; a distance from the anterior end to excretory pore of 46 (43-50) μm; a distance from anterior end to nerve ring of 72 μm (61-85 μm); and E% of 88 (77-97). The first-generation males are characterised by 27 genital papillae and very short spicules, with a length of 61 μm (53-67) μm. The SW% and GS% ratio of S. shori n. sp. are 139 (107-190) and 75 (62-90), respectively. The new species is further characterized by sequences of the internal transcribed spacer and partial 28S regions of the ribosomal DNA. Phylogenetic analyses show that S. shori n. sp. is most closely related to S. abbasi, S. kandii, and S. yirgalemense.

quEHRy: a question answering system to query electronic health records

OBJECTIVE

We propose a system, quEHRy, to retrieve precise, interpretable answers to natural language questions from structured data in electronic health records (EHRs).

MATERIALS AND METHODS

We develop/synthesize the main components of quEHRy: concept normalization (MetaMap), time frame classification (new), semantic parsing (existing), visualization with question understanding (new), and query module for FHIR mapping/processing (new). We evaluate quEHRy on 2 clinical question answering (QA) datasets. We evaluate each component separately as well as holistically to gain deeper insights. We also conduct a thorough error analysis for a crucial subcomponent, medical concept normalization.

RESULTS

Using gold concepts, the precision of quEHRy is 98.33% and 90.91% for the 2 datasets, while the overall accuracy was 97.41% and 87.75%. Precision was 94.03% and 87.79% even after employing an automated medical concept extraction system (MetaMap). Most incorrectly predicted medical concepts were broader in nature than gold-annotated concepts (representative of the ones present in EHRs), eg, Diabetes versus Diabetes Mellitus, Non-Insulin-Dependent.

DISCUSSION

The primary performance barrier to deployment of the system is due to errors in medical concept extraction (a component not studied in this article), which affects the downstream generation of correct logical structures. This indicates the need to build QA-specific clinical concept normalizers that understand EHR context to extract the "relevant" medical concepts from questions.

CONCLUSION

We present an end-to-end QA system that allows information access from EHRs using natural language and returns an exact, verifiable answer. Our proposed system is high-precision and interpretable, checking off the requirements for clinical use.

Cubosome Lipid Nanocarriers As a Drug Delivery Vehicle for Intracellular Mycobacterium tuberculosis Infections

Mycobacterium tuberculosis (MTB) causes the infectious disease tuberculosis (TB), responsible for more deaths than any other single infectious disease in history. Intracellular MTB are slow growing and difficult to target with traditional antitubercular drugs, leading to the emergence of multidrug resistance in TB infection, which is a major global public health issue. Recent advances in innovative lipid nanotechnologies for drug delivery have demonstrated promising outcomes for chronic infectious diseases but have not yet been tested as potential delivery systems for intracellular infections such as TB. The current study evaluates the potential of monoolein (MO)-based cationic cubosomes for the encapsulation and delivery of the first line antitubercular drug rifampicin (RIF) against an MTB-H37Ra in vitro culture model. In particular, we show that the use of cationic cubosomes as delivery vehicles reduced the minimum inhibitory concentration (MIC) of RIF by 2-fold against actively replicating MTB-H37Ra (compared to that of the free drug) and also shortened the lifecycle duration of axenic MTB-H37Ra from 5 to 3 days. The cubosome-mediated delivery was also found to be effective against intracellular MTB-H37Ra within THP-1 human macrophages, with a 2.8 log reduction in viability of the bacilli after 6 days incubation at the MIC. The killing time was also reduced from 8 to 6 days without distressing the host macrophages. Mechanistic studies on the uptake of RIF-loaded cationic cubosomes using total internal reflection fluorescence microscopy (TIRFM) demonstrated the capacity of these lipid particles to effectively target intracellular bacteria. Overall, these results demonstrate that cationic cubosomes are a potent delivery system for the antitubercular drug RIF for therapeutic management of TB.

Effects of oral probiotic and lactoferrin interventions on iron-zinc homeostasis, oxidant/antioxidant equilibrium and diarrhoea incidence of neonatal piglets

The objective of this study was to examine the effects of early-life host specific probiotic and lactoferrin (LF) supplementations on diarrhoea incidence, iron (Fe)-zinc (Zn) balance and antioxidant capabilities in serum of neonatal piglets. A total of eight sow litters obtained from parity matched sows were randomly divided into four groups and assigned to one of the four interventions: control (2.0 ml normal saline), bovine lactoferrin (bLF) (100 mg bLF in normal saline), probiotic (Pb) (1×10⁹ cfu of swine origin Pediococcus acidilactici FT28 strain) and bLF+Pb (both 100 mg bLF and 1×10⁹ cfu of P. acidilactici FT28). All the piglets received supplementations once daily orally for first 7 days of life. The incidence of diarrhoea markedly decreased in bLF group compared to control group. Notably, no incidences of diarrhoea were recorded in Pb and bLF+Pb groups. The Zn and Fe concentrations were significantly increased from day 7 to 21 in bLF and on day 21 in bLF+Pb group. No such changes were noted in Pb group. Total antioxidant capacity (TAC) in serum was significantly increased on days 7 and 15 in bLF group and on days 7 and 21 in bLF+Pb group. Malonaldehyde concentration was markedly reduced from day 7 to 21 in bLF and bLF+Pb groups. The concentrations of nitrate on days 15 and 21 and malonaldehyde on day 7 were significantly higher in Pb group, but mean TAC was unaltered from day 0 to 21. Although no correlation between the incidence of diarrhoea and Zn/Fe and oxidant/antioxidant homeostasis was noted in the Pb group, the supplementation of P. acidilactici FT28 alone was sufficient to prevent the incidence of diarrhoea in neonatal piglets. Taken together, it is concluded that strategic supplementation of P. acidilactici FT28 in early life could help in preventing diarrhoea until weaning of piglets.

Age differences in the behavioural economics of cannabis use: Do adolescents and adults differ on demand for cannabis and discounting of future reward?

BACKGROUND

Adolescence is a period of psychological and neural development in which harms associated with cannabis use may be heightened. We hypothesised that adolescent who use cannabis (adolescentsWUC) would have steeper delay discounting (preference for immediate over future rewards) and greater demand (relative valuation) for cannabis than adults who use cannabis (adultsWUC).

METHODS

This cross-sectional study, part of the 'CannTeen' project, compared adultsWUC (n = 71, 26-29 years old) and adolescentsWUC (n = 76, 16-17 years old), and gender- and age-matched adolescent (n = 63) and adult (n = 64) controls. AdolescentsWUC and adultsWUC used cannabis 1-7 days/week and were matched on cannabis use frequency (4 days/week). The Monetary Choice Questionnaire assessed delay discounting. A modified Marijuana Purchase Task (MPT) assessed cannabis demand in adolescentsWUC and adultsWUC. The MPT yielded five indices: intensity (amount of cannabis used at zero cost), O_max (total peak expenditure), P_max (price at peak expenditure), breakpoint (cost at which cannabis demand is suppressed to zero) and elasticity (degree to which cannabis use decreases with increasing price). Analyses were adjusted for covariates of gender, socioeconomic status, other illicit drug use.

RESULTS

Both adolescentsWUC and adultsWUC had steeper delay discounting than controls (F, (1,254)= 9.13, p = 0.003, η_p²= 0.04), with no significant age effect or interaction. AdolescentsWUC showed higher intensity (F, (1,138)= 9.76, p = 0.002, η_p²= 0.07) and lower elasticity (F, (1,138)= 15.25, p < 0.001, η_p²= 0.10) than adultsWUC. There were no significant differences in P_max, O_max or breakpoint.

CONCLUSION

Individuals who use cannabis prefer immediate rewards more than controls. AdolescentsWUC, compared to adultsWUC, may be in a high-risk category with diminished sensitivity to cannabis price increases and a greater consumption of cannabis when it is free.

Search for Subsolar-Mass Binaries in the First Half of Advanced LIGO's and Advanced Virgo's Third Observing Run

We report on a search for compact binary coalescences where at least one binary component has a mass between 0.2  M_{⊙} and 1.0  M_{⊙} in Advanced LIGO and Advanced Virgo data collected between 1 April 2019 1500 UTC and 1 October 2019 1500 UTC. We extend our previous analyses in two main ways: we include data from the Virgo detector and we allow for more unequal mass systems, with mass ratio q≥0.1. We do not report any gravitational-wave candidates. The most significant trigger has a false alarm rate of 0.14  yr^{-1}. This implies an upper limit on the merger rate of subsolar binaries in the range [220-24200]  Gpc^{-3} yr^{-1}, depending on the chirp mass of the binary. We use this upper limit to derive astrophysical constraints on two phenomenological models that could produce subsolar-mass compact objects. One is an isotropic distribution of equal-mass primordial black holes. Using this model, we find that the fraction of dark matter in primordial black holes in the mass range 0.2  M_{⊙}<m_{PBH}<1.0  M_{⊙} is f_{PBH}≡Ω_{PBH}/Ω_{DM}≲6%. This improves existing constraints on primordial black hole abundance by a factor of ∼3. The other is a dissipative dark matter model, in which fermionic dark matter can collapse and form black holes. The upper limit on the fraction of dark matter black holes depends on the minimum mass of the black holes that can be formed: the most constraining result is obtained at M_{min}=1  M_{⊙}, where f_{DBH}≡Ω_{DBH}/Ω_{DM}≲0.003%. These are the first constraints placed on dissipative dark models by subsolar-mass analyses.

Patient outcomes following transfer between intensive care units during the COVID-19 pandemic

Transferring critically ill patients between intensive care units (ICU) is often required in the UK, particularly during the COVID-19 pandemic. However, there is a paucity of data examining clinical outcomes following transfer of patients with COVID-19 and whether this strategy affects their acute physiology or outcome. We investigated all transfers of critically ill patients with COVID-19 between three different hospital ICUs, between March 2020 and March 2021. We focused on inter-hospital ICU transfers (those patients transferred between ICUs from different hospitals) and compared this cohort with intra-hospital ICU transfers (patients moved between different ICUs within the same hospital). A total of 507 transfers were assessed, of which 137 met the inclusion criteria. Forty-five patients underwent inter-hospital transfers compared with 92 intra-hospital transfers. There was no significant change in median compliance 6 h pre-transfer, immediately post-transfer and 24 h post-transfer in patients who underwent either intra-hospital or inter-hospital transfers. For inter-hospital transfers, there was an initial drop in median PaO₂ /F_I O₂ ratio: from median (IQR [range]) 25.1 (17.8-33.7 [12.1-78.0]) kPa 6 h pre-transfer to 19.5 (14.6-28.9 [9.8-52.0]) kPa immediately post-transfer (p < 0.05). However, this had resolved at 24 h post-transfer: 25.4 (16.2-32.9 [9.4-51.9]) kPa. For intra-hospital transfers, there was no significant change in PaO₂ /F_I O₂ ratio. We also found no meaningful difference in pH; PaCO₂ ;_, base excess; bicarbonate; or norepinephrine requirements. Our data demonstrate that patients with COVID-19 undergoing mechanical ventilation of the lungs may have short-term physiological deterioration when transferred between nearby hospitals but this resolves within 24 h. This finding is relevant to the UK critical care strategy in the face of unprecedented demand during the COVID-19 pandemic.

Toward a Neural Semantic Parsing System for EHR Question Answering

Clinical semantic parsing (SP) is an important step toward identifying the exact information need (as a machine-understandable logical form) from a natural language query aimed at retrieving information from electronic health records (EHRs). Current approaches to clinical SP are largely based on traditional machine learning and require hand-building a lexicon. The recent advancements in neural SP show a promise for building a robust and flexible semantic parser without much human effort. Thus, in this paper, we aim to systematically assess the performance of two such neural SP models for EHR question answering (QA). We found that the performance of these advanced neural models on two clinical SP datasets is promising given their ease of application and generalizability. Our error analysis surfaces the common types of errors made by these models and has the potential to inform future research into improving the performance of neural SP models for EHR QA.

Point Absorber Limits to Future Gravitational-Wave Detectors

High-quality optical resonant cavities require low optical loss, typically on the scale of parts per million. However, unintended micron-scale contaminants on the resonator mirrors that absorb the light circulating in the cavity can deform the surface thermoelastically and thus increase losses by scattering light out of the resonant mode. The point absorber effect is a limiting factor in some high-power cavity experiments, for example, the Advanced LIGO gravitational-wave detector. In this Letter, we present a general approach to the point absorber effect from first principles and simulate its contribution to the increased scattering. The achievable circulating power in current and future gravitational-wave detectors is calculated statistically given different point absorber configurations. Our formulation is further confirmed experimentally in comparison with the scattered power in the arm cavity of Advanced LIGO measured by in situ photodiodes. The understanding presented here provides an important tool in the global effort to design future gravitational-wave detectors that support high optical power and thus reduce quantum noise.

A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave

Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve the reliability of outputs. Here we report insights from ten weeks of collaborative short-term forecasting of COVID-19 in Germany and Poland (12 October-19 December 2020). The study period covers the onset of the second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) and subsequently a decay (Poland) or plateau and renewed increase (Germany) in reported cases. Thirteen independent teams provided probabilistic real-time forecasts of COVID-19 cases and deaths. These were reported for lead times of one to four weeks, with evaluation focused on one- and two-week horizons, which are less affected by changing NPIs. Heterogeneity between forecasts was considerable both in terms of point predictions and forecast spread. Ensemble forecasts showed good relative performance, in particular in terms of coverage, but did not clearly dominate single-model predictions. The study was preregistered and will be followed up in future phases of the pandemic.

Approaching the motional ground state of a 10-kg object

The motion of a mechanical object, even a human-sized object, should be governed by the rules of quantum mechanics. Coaxing them into a quantum state is, however, difficult because the thermal environment masks any quantum signature of the object's motion. The thermal environment also masks the effects of proposed modifications of quantum mechanics at large mass scales. We prepared the center-of-mass motion of a 10-kilogram mechanical oscillator in a state with an average phonon occupation of 10.8. The reduction in temperature, from room temperature to 77 nanokelvin, is commensurate with an 11 orders-of-magnitude suppression of quantum back-action by feedback and a 13 orders-of-magnitude increase in the mass of an object prepared close to its motional ground state. Our approach will enable the possibility of probing gravity on massive quantum systems.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15}. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.

Constraints on Cosmic Strings Using Data from the Third Advanced LIGO-Virgo Observing Run

We search for gravitational-wave signals produced by cosmic strings in the Advanced LIGO and Virgo full O3 dataset. Search results are presented for gravitational waves produced by cosmic string loop features such as cusps, kinks, and, for the first time, kink-kink collisions. A template-based search for short-duration transient signals does not yield a detection. We also use the stochastic gravitational-wave background energy density upper limits derived from the O3 data to constrain the cosmic string tension Gμ as a function of the number of kinks, or the number of cusps, for two cosmic string loop distribution models. Additionally, we develop and test a third model that interpolates between these two models. Our results improve upon the previous LIGO-Virgo constraints on Gμ by 1 to 2 orders of magnitude depending on the model that is tested. In particular, for the one-loop distribution model, we set the most competitive constraints to date: Gμ≲4×10^{-15}. In the case of cosmic strings formed at the end of inflation in the context of grand unified theories, these results challenge simple inflationary models.

Distinct genomic landscapes of gastroesophageal adenocarcinoma depending on PD-L1 expression identify mutations in RAS-MAPK pathway and TP53 as potential predictors of immunotherapy efficacy

BACKGROUND

The impact of molecular alterations on programmed death-ligand 1 (PD-L1) combined positive score (CPS) is not well studied in gastroesophageal adenocarcinomas (GEAs). We aimed to characterize genomic features of tumors with different CPSs in GEAs.

PATIENTS AND METHODS

Genomic alterations of 2518 GEAs were compared in three groups (PD-L1 CPS ≥ 10, high; CPS = 1-9, intermediate; CPS < 1, low) using next-generation sequencing. We assessed the impact of gene mutations on the efficacy of immune checkpoint inhibitors (ICIs) and tumor immune environment based on the Memorial Sloan Kettering Cancer Center and The Cancer Genome Atlas databases.

RESULTS

High, intermediate, and low CPSs were seen in 18%, 54% and 28% of GEAs, respectively. PD-L1 positivity was less prevalent in women and in tissues derived from metastatic sites. PD-L1 CPS was positively associated with mismatch repair deficiency/microsatellite instability-high, but independent of tumor mutation burden distribution. Tumors with mutations in KRAS, TP53, and RAS-mitogen-activated protein kinase (MAPK) pathway were associated with higher PD-L1 CPSs in the mismatch repair proficiency and microsatellite stability (pMMR&MSS) subgroup. Patients with RAS-MAPK pathway alterations had longer overall survival (OS) from ICIs compared to wildtype (WT) patients [27 versus 13 months, hazard ratio (HR) = 0.36, 95% confidence interval (CI): 0.19-0.7, P = 0.016] and a similar trend was observed in the MSS subgroup (P = 0.11). In contrast, patients with TP53 mutations had worse OS from ICIs compared to TP53-WT patients in the MSS subgroup (5 versus 21 months, HR = 2.39, 95% CI: 1.24-4.61, P = 0.016).

CONCLUSIONS

This is the largest study to investigate the distinct genomic landscapes of GEAs with different PD-L1 CPSs. Our data may provide novel insights for patient selection using mutations in TP53 and RAS-MAPK pathway and for the development of rational combination immunotherapies in GEAs.

An evaluation of two commercial deep learning-based information retrieval systems for COVID-19 literature

The COVID-19 pandemic has resulted in a tremendous need for access to the latest scientific information, leading to both corpora for COVID-19 literature and search engines to query such data. While most search engine research is performed in academia with rigorous evaluation, major commercial companies dominate the web search market. Thus, it is expected that commercial pandemic-specific search engines will gain much higher traction than academic alternatives, leading to questions about the empirical performance of these tools. This paper seeks to empirically evaluate two commercial search engines for COVID-19 (Google and Amazon) in comparison with academic prototypes evaluated in the TREC-COVID task. We performed several steps to reduce bias in the manual judgments to ensure a fair comparison of all systems. We find the commercial search engines sizably underperformed those evaluated under TREC-COVID. This has implications for trust in popular health search engines and developing biomedical search engines for future health crises.

Patient Cohort Retrieval using Transformer Language Models

We apply deep learning-based language models to the task of patient cohort retrieval (CR) with the aim to assess their efficacy. The task ofCR requires the extraction of relevant documents from the electronic health records (EHRs) on the basis of a given query. Given the recent advancements in the field of document retrieval, we map the task of CR to a document retrieval task and apply various deep neural models implemented for the general domain tasks. In this paper, we propose a framework for retrieving patient cohorts using neural language models without the need of explicit feature engineering and domain expertise. We find that a majority of our models outperform the BM25 baseline method on various evaluation metrics.

Deep learning in clinical natural language processing: a methodical review

OBJECTIVE

This article methodically reviews the literature on deep learning (DL) for natural language processing (NLP) in the clinical domain, providing quantitative analysis to answer 3 research questions concerning methods, scope, and context of current research.

MATERIALS AND METHODS

We searched MEDLINE, EMBASE, Scopus, the Association for Computing Machinery Digital Library, and the Association for Computational Linguistics Anthology for articles using DL-based approaches to NLP problems in electronic health records. After screening 1,737 articles, we collected data on 25 variables across 212 papers.

RESULTS

DL in clinical NLP publications more than doubled each year, through 2018. Recurrent neural networks (60.8%) and word2vec embeddings (74.1%) were the most popular methods; the information extraction tasks of text classification, named entity recognition, and relation extraction were dominant (89.2%). However, there was a "long tail" of other methods and specific tasks. Most contributions were methodological variants or applications, but 20.8% were new methods of some kind. The earliest adopters were in the NLP community, but the medical informatics community was the most prolific.

DISCUSSION

Our analysis shows growing acceptance of deep learning as a baseline for NLP research, and of DL-based NLP in the medical community. A number of common associations were substantiated (eg, the preference of recurrent neural networks for sequence-labeling named entity recognition), while others were surprisingly nuanced (eg, the scarcity of French language clinical NLP with deep learning).

CONCLUSION

Deep learning has not yet fully penetrated clinical NLP and is growing rapidly. This review highlighted both the popular and unique trends in this active field.

Renal impairment and its impact on clinical outcomes in patients who are critically ill with COVID-19: a multicentre observational study

Renal impairment is common in patients who are critically ill with coronavirus disease-19 (COVID-19). We examined the association between acute and chronic kidney disease with clinical outcomes in 372 patients with coronavirus disease-19 admitted to four regional intensive care units between 10 March 2020 and 31 July 2020. A total of 216 (58%) patients presented with COVID-19 and renal impairment. Acute kidney injury and/or chronic kidney disease was associated with greater in-hospital mortality compared with patients with preserved renal function (107/216 patients (50%) (95%CI 44-57) vs. 32/156 (21%) (95%CI 15-28), respectively; p < 0.001, relative risk 2.4 (95%CI 1.7-3.4)). Mortality was greatest in patients with renal transplants (6/7 patients (86%) (95%CI 47-100)). Mortality rates increased in patients with worsening renal injury according to the Kidney Disease: Improving Global Outcomes classification: stage 0 mortality 33/157 patients (21%) (95%CI 15-28) vs. stages 1-3 mortality 91/186 patients (49%) (95%CI 42-56); p < 0.001, relative risk 2.3 (95%CI 1.7-3.3). Survivors were less likely to require renal replacement therapy compared with non-survivors (57/233 patients (24%) vs. 64/139 patients (46%), respectively; p < 0.001, relative risk 1.9 (95%CI 1.4-2.5)). One-fifth of survivors who required renal replacement therapy acutely in intensive care continued to require renal support following discharge. Our data demonstrate that renal impairment in patients admitted to intensive care with COVID-19 is common and is associated with a high mortality and requirement for on-going renal support after discharge from critical care. Our findings have important implications for future pandemic planning in this patient cohort.

GW190521: A Binary Black Hole Merger with a Total Mass of 150 M_{⊙}

On May 21, 2019 at 03:02:29 UTC Advanced LIGO and Advanced Virgo observed a short duration gravitational-wave signal, GW190521, with a three-detector network signal-to-noise ratio of 14.7, and an estimated false-alarm rate of 1 in 4900 yr using a search sensitive to generic transients. If GW190521 is from a quasicircular binary inspiral, then the detected signal is consistent with the merger of two black holes with masses of 85_{-14}^{+21}  M_{⊙} and 66_{-18}^{+17}  M_{⊙} (90% credible intervals). We infer that the primary black hole mass lies within the gap produced by (pulsational) pair-instability supernova processes, with only a 0.32% probability of being below 65  M_{⊙}. We calculate the mass of the remnant to be 142_{-16}^{+28}  M_{⊙}, which can be considered an intermediate mass black hole (IMBH). The luminosity distance of the source is 5.3_{-2.6}^{+2.4}  Gpc, corresponding to a redshift of 0.82_{-0.34}^{+0.28}. The inferred rate of mergers similar to GW190521 is 0.13_{-0.11}^{+0.30}  Gpc^{-3} yr^{-1}.

Developing a Search Engine for Precision Medicine

Precision medicine focuses on developing new treatments based on an individual's genetic, environmental, and lifestyle profile. While this data-driven approach has led to significant advances, retrieving information specific to a patient's condition has proved challenging for oncologists due to the large volume of data. In this paper, we propose the PRecIsion Medicine Robust Oncology Search Engine (PRIMROSE) for cancer patients that retrieves scientific articles and clinical trials based on a patient's condition, genetic profile, age, and gender. Our search engine utilizes Elasticsearch indexes for information storage and retrieval, and we developed a knowledge graph for query expansion in order to improve recall. Additionally, we experimented with machine learning and learning-to-rank components to the search engine and compared the results of the two approaches. Finally, we developed a front-facing ReactJS website and a REST API for connecting with our search engine. The development of this front-facing website allows for easy access to our system by healthcare providers.

Paraphrasing to improve the performance of Electronic Health Records Question Answering

This paper describes a paraphrasing approach to improve the performance of question answering (QA) for electronic health records (EHRs). QA systems for structured EHR data usually rely on semantic parsing, which aims to generate machine-understandable logical forms from free-text questions. Training semantic parsers requires large datasets of question-logical form (QL) pairs, which are labor-intensive to create. Considering the scarcity of large QL datasets in the clinical domain, we propose a framework for expanding an existing dataset using paraphrasing. We experiment with different heuristics for multiple sample sizes and iterations to assess the effect of adding paraphrasing to the task of semantic parsing. We found that adding paraphrases to an existing dataset based on TERTHRESHOLD scores results in an improved performance in the majority (74%) of the experimental runs. Hence, the proposed paraphrasing-based framework has the potential to improve the performance of QA systems using a limited set of existing QL annotations.

HIV self-tests for men who have sex with men, accessed via a digital vending machine: a qualitative study of acceptability

As the number of people living with undiagnosed HIV infection in the UK declines, innovative ways to access those least engaged with services are needed. This study explores the attitudes of men who have sex with men (MSM) towards using HIV self-testing (HIVST) kits distributed via a vending machine in a sauna (a licenced sex-on-premise venue). Twenty-three MSM attending the sauna were recruited to take part in semi-structured qualitative interviews. The participants were overwhelmingly positive about the HIVST vending machine. They identified convenience and flexibility as major benefits to testing in this way. The sauna was felt to be an appropriate location for the intervention. Limitations identified included the potential to reduce screening for other sexually transmitted infections and the inappropriate use of HIVST kits as a tool for risk-assessment prior to condomless sex, with a poor understanding of the window period. The implications of receiving a positive result without immediate access to support were also a concern. HIVST vending machines are an acceptable, innovative way to encourage HIV testing. Providers need to ensure this intervention is supported by adequate information regarding the limitations of the test and how to access comprehensive services to avoid any unintended negative effects.

Using FHIR to Construct a Corpus of Clinical Questions Annotated with Logical Forms and Answers

This paper describes a novel technique for annotating logical forms and answers for clinical questions by utilizing Fast Healthcare Interoperability Resources (FHIR). Such annotations are widely used in building the semantic parsing models (which aim at understanding the precise meaning of natural language questions by converting them to machine-understandable logical forms). These systems focus on reducing the time it takes for a user to get to information present in electronic health records (EHRs). Directly annotating questions with logical forms is a challenging task and involves a time-consuming step of concept normalization annotation. We aim to automate this step using the normalized codes present in a FHIR resource. Using the proposed approach, two annotators curated an annotated dataset of 1000 questions in less than 1 week. To assess the quality of these annotations, we trained a semantic parsing model which achieved an accuracy of 94.2% on this corpus.

Quantum-Enhanced Advanced LIGO Detectors in the Era of Gravitational-Wave Astronomy

The Laser Interferometer Gravitational Wave Observatory (LIGO) has been directly detecting gravitational waves from compact binary mergers since 2015. We report on the first use of squeezed vacuum states in the direct measurement of gravitational waves with the Advanced LIGO H1 and L1 detectors. This achievement is the culmination of decades of research to implement squeezed states in gravitational-wave detectors. During the ongoing O3 observation run, squeezed states are improving the sensitivity of the LIGO interferometers to signals above 50 Hz by up to 3 dB, thereby increasing the expected detection rate by 40% (H1) and 50% (L1).

Search for Subsolar Mass Ultracompact Binaries in Advanced LIGO's Second Observing Run

We present a search for subsolar mass ultracompact objects in data obtained during Advanced LIGO's second observing run. In contrast to a previous search of Advanced LIGO data from the first observing run, this search includes the effects of component spin on the gravitational waveform. We identify no viable gravitational-wave candidates consistent with subsolar mass ultracompact binaries with at least one component between 0.2  M_{⊙}-1.0  M_{⊙}. We use the null result to constrain the binary merger rate of (0.2  M_{⊙}, 0.2  M_{⊙}) binaries to be less than 3.7×10^{5}  Gpc^{-3} yr^{-1} and the binary merger rate of (1.0  M_{⊙}, 1.0  M_{⊙}) binaries to be less than 5.2×10^{3}  Gpc^{-3} yr^{-1}. Subsolar mass ultracompact objects are not expected to form via known stellar evolution channels, though it has been suggested that primordial density fluctuations or particle dark matter with cooling mechanisms and/or nuclear interactions could form black holes with subsolar masses. Assuming a particular primordial black hole (PBH) formation model, we constrain a population of merging 0.2  M_{⊙} black holes to account for less than 16% of the dark matter density and a population of merging 1.0  M_{⊙} black holes to account for less than 2% of the dark matter density. We discuss how constraints on the merger rate and dark matter fraction may be extended to arbitrary black hole population models that predict subsolar mass binaries.

Introduction into nanotechnology and microbiology

The current chapter summaries the world of Microbiology and boom of Nanotechnology and how both the exciting fields come together to help men kind with various new applications in water, food, medical biology and immunology. Furthermore synthesis of nano materials utilising the potential of microorganisms also opens a newer avenue for 'green' synthesis.

PREDICTIVE VALUE OF SERUM IL-17A AND IP-10 FOR EVALUATION OF LIVER FIBROSIS PROGRESSION IN PATIENTS WITH HBV/HIV CO-INFECTION

The problem of HBV and HCV infections in addition to the HIV-infection in sub-Saharan African countries remains important due to the high prevalence and mortality after fast progressing fibrogenesis and development of hepatocellular carcinoma. Despite of the large number of investigations on diagnostics and prediction of the disease course, the exact role of the proinflammatory influence of IP-10 and IL-17A on the fibrogenesis during HIV/HBV-co-infection is still unknown. The aim of the study was to investigate IP-10 and IL-17A concentration in blood serum among HIV/HBV patients to consider their potential role in improvement of diagnostics of liver fibrosis progression. 53 HIV/HBV patients of Lewanika General Hospital (West Zambia) and 21 healthy blood donors were checked for serological markers, liver biopsy and IP-10, IL-17A in blood serum. The obtained results were analyzed by statistical package SPSS 12.0. Mean IP-10 was 753,6 pg/ml among HIV/HBV co-infected patients with F3-4 and it was reliably higher than in F1-2 patients and healthy responders (р=0,005). This group had also higher level of IL-17A (37,54 pg/ml) than comparison groups (р=0,032). We found out strong correlation between increasing IP-10 (r=0,6), IL-17A (r=0,52) and fibrotic severity (р<0,05). High IP-10, IL-17A amount increases the risk of F3-4 formation in HIV/HBV patients.

Cross cultural comparison of constipation profiles at tertiary care centers between India and USA

BACKGROUND

Despite potential differences in patient perception of chronic constipation (CC) in geographically and culturally distinct regions, head-to-head studies comparing the clinical profile, constipation severity, impact on quality of life (QOL) and economic impact are lacking.

METHODS

We conducted a cross-sectional cohort study of patients presenting with CC to tertiary care centers in the USA and India. Standardized instruments were used to assess constipation subtype, disease severity, disease-specific QOL, somatization, and psychiatric comorbidities. We used multivariable linear regression to determine the predictors of QOL and number of healthcare visits.

KEY RESULTS

Sixty-six and 98 patients with CC were enrolled in the USA and India, respectively. Indian patients with CC had significantly more frequent bowel movements/week compared to their USA counterparts (Median 5 vs 3, P < .0001). The proportion of patients with Bristol stool form scale type 1 and 2 was significantly higher in the USA compared to India (65.5% vs 48%, P = .04). Higher depression score (P = .001), more severe constipation symptoms (P = .001) and site of the study being USA (P = .008) independently predicted worse QOL. Indian patients (P < .001) and worse QOL (P = .02) were independent predictors of number of healthcare visits in the last 12 months.

CONCLUSIONS AND INFERENCES

Indian patients with CC have more frequent and softer bowel movements compared to those in the USA suggesting significant differences in perception of CC in different geographic and cultural settings. QOL and economic impact related to constipation varies with geographic/cultural setting irrespective of other clinical and psychosomatic features.

Impact of genetic variations in the MAPK signaling pathway on outcome in metastatic colorectal cancer patients treated with first-line FOLFIRI and bevacizumab: data from FIRE-3 and TRIBE trials

BACKGROUND

The MAPK-interacting kinase 1 (MKNK1) is localized downstream of the RAS/RAF/ERK and the MAP3K1/MKK/p38 signaling pathway. Through phosphorylation MKNK1 regulates the function of eukaryotic translation initiation factor 4E, a key player in translational control, whose expression is often upregulated in metastatic colorectal cancer patients (mCRC). Preclinical data suggest that MKNK1 increases angiogenesis by upregulating angiogenic factors. We therefore hypothesize that variations in the MKNK1 gene predict outcome in mCRC patients treated with first-line FOLFIRI and bevacizumab (bev).

PATIENTS AND METHODS

A total of 567 patients with KRAS wild-type mCRC in the randomized phase III FIRE-3 and TRIBE trials treated with first-line FOLFIRI/bev (discovery and validation cohorts) or FOLFIRI and cetuximab (cet) (control cohort) were included in this study. Five single-nucleotide polymorphisms in the MAPK signaling pathway were analyzed.

RESULTS

AA genotype carriers of the MKNK1 rs8602 single-nucleotide polymorphism treated with FOLFIRI/bev in the discovery cohort (FIRE-3) had a shorter progression-free survival (PFS) than those harboring any C (7.9 versus 10.3 months, Hazard ratio (HR) 1.73, P = 0.038). This association could be confirmed in the validation cohort (TRIBE) in multivariable analysis (PFS 9.0 versus 11.0 months, HR 3.04, P = 0.029). Furthermore, AA carriers in the validation cohort had a decreased overall response rate (25% versus 66%, P = 0.049). Conversely, AA genotype carriers in the control group receiving FOLFIRI/cet did not show a shorter PFS. By combining both FOLFIRI/bev cohorts the worse outcome among AA carriers became more significant (PFS 9.0 versus 10.5 months) in univariable (HR 1.74, P = 0.015) and multivariable analysis (HR 1.76, P = 0.022). Accordingly, AA carriers did also exhibit an inferior overall response rate compared with those harboring any C (36% versus 65%, P = 0.005).

CONCLUSION

MKNK1 polymorphism rs8602 might serve as a predictive marker in KRAS wild-type mCRC patients treated with FOLFIRI/bev in the first-line setting. Additionally, MKNK1 might be a promising target for drug development.