The impact of the UK’s first COVID-19 lockdown on rates of violence and aggression on psychiatric inpatient wards

AimsInpatient life in UK mental health hospitals was profoundly altered during the first wave of the COVID-19 pandemic. We analysed whether these changes impacted the rate of violent and aggressive incidents across acute adult wards and psychiatric intensive care units in a South London NHS Mental Health Trust during the first UK lockdown.MethodsWe used an interrupted time series analysis to assess whether the rate of violent and aggressive incidents changed during the lockdown period from 23rd March 2020 to 15th June 2020. We used a quasi-poisson general additive model to model the weekly rate of violent incidents as a function of a seasonal trend, time trend, and impact of lockdown, using data from 1st January 2017 to 27th September 2020.ResultsThere was a 35% increase in the rate of incidents of violence and aggression [IR = 1.35, 95% CI: 1.15 – 1.58, p < 0.001] between March 23rd 2020 and June 15th 2020. In addition, there was strong evidence of temporal (p < 0.001) and seasonal trends (p < 0.001).ConclusionsOur results suggest that restrictions to life increased the rate of violent incidents on the mental health wards studied here.

Use of pasture botanical composition data on the accuracy of satellite pasture biomass estimates

Pasture biomass estimates are valuable to farmers, and satellite pasture biomass estimates can potentially provide the required data for less time and labour. However, the accuracy of satellite estimates of pasture biomass can be affected by the botanical composition of the pasture. In this study, botanical composition data were combined in linear regression models and a general additive model with on-farm and satellite pasture biomass estimates to quantify the increase in predictive power from including botanical composition data. The inclusion of botanical composition data improved the accuracy (model R2) of the satellite pasture biomass estimation; the smallest increase was 0.035 (from 0.725 to 0.760) and the largest increase was 0.111 (from 0.599 to 0.710). Improving the accuracy of satellite estimations of pasture biomass will allow farmers to make more timely and accurate grazing management decisions.

PEMETAAN POLA PERGERAKAN PENANGKAPAN IKAN CAKALANG (Katsuwonus pelamis) DENGAN MENGGUNAKAN DATA SATELIT DAN PURSE SEINE DI SELAT MAKASSAR SELAMA JULI-OKTOBER 2018

Tujuan penelitian ini adalah untuk mengkaji dan memetakan pola pergerakan ikan Cakalang (Katsuwonus Pelamis) pada bulan Juli – Oktober 2018 dengan fishing base di Kabupaten Pinrang di Selat Makassar. Data yang digunakan yaitu data primer yang dikumpulkan dengan mengikuti operasi penangkapan purse seine dan dikombinasikan dengan data sekunder yaitu citra satelit suhu permukaan laut dan klorofil-a yang diperoleh dari satelit Aqua modis sesuai dengan waktu penelitian. Metode yang digunakan dalam penelitian ini adalah metode survey dimana data sampling dianalisis dengan menggunakan analisis statistic General Additive Model (GAM) yang menganalisis hasil tangkapan dan beberapa parameter oseanografi. Dari hasil tersebut kemudian dilakukan analisis dengan tehnik spasial analisis pada sistem informasi geografis (SIG) menggunakan perangkat lunak ArcGis 10.2 sehingga didapatkan pola pergerakan ikan cakalang di Perairan Selat Makassar. Hasil penelitian menunjukkan pola pergerakan ikan cakalang pada bulan Juli sampai Oktober secara signifikan dipengaruhi oleh konsentrasi Klorofil-a. Pola pergerakan ikan cakalang di Perairan Selat Makassar yaitu pada bulan Juli – Agustus 2018 berada di Perairan Pare pare – Barru, Sulawesi selatan dan bulan September gerombolan ikan bergerak ke arah barat lepas pantai. Selanjutnya pada bulan Oktober konsentrasi ikan cenderung bergerak terus ke arah barat mendekati perairan pantai Kotabaru, Kalimantan Selatan. Diduga kuat pola pergerakan ikan cakalang terkait dengan pola distribusi makanan ikan / nutrient yang diindikasikan oleh kondisi klorofil-a.

Tumor mutational burden (TMB) and PD-L1 expression as predictors of response to immunotherapy (IO) in NSCLC.

2630 Background: PD-L1 expression and TMB, as a proxy for neoantigen burden, have been correlated with response to IO in advanced NSCLC (aNSCLC) clinical trials, but their combined utility is unclear. We assessed TMB and PD-L1 as predictors of response in aNSCLC patients (pts) after IO monotherapy in a real-world setting. Methods: Pts had a diagnosis of aNSCLC, comprehensive genomic profiling of 186-315 genes/1.1 megabase (Mb), PD-L1 testing of pre-IO specimens, and were treated in the Flatiron Health network (1/2011 - 6/2018). Clinical characteristics and real-world tumor response (rwTR) were obtained via technology-enabled abstraction of clinician notes and radiology/pathology reports, and linked to genomic data in the Flatiron Health-Foundation Medicine Clinico-Genomic Database. A general additive model examined the predictive value of TMB (as continuous measure) and PD-L1 level on rwTR. A reduced PD-L1-only model was compared to the full model using Akaike Information Criterion (AIC). rwTR predictions at representative TMB and PD-L1 levels were calculated. Results: Of 426 pts, PD-L1 expression was high (≥50%) in 140, low (1-49%) in 123, and negative (<1%) in 163. Median TMB was 9.6 mut/Mb (IQR 4.4 - 14.8) overall, 11.3 in responders and 8.7 in non-responders. TMB did not correlate with PD-L1 level (Kruskal-Wallis p=0.29). The TMB + PD-L1 model had superior prediction of rwTR than the PD-L1 model, as assessed by lower AIC score. In the combined model, higher TMB and PD-L1 levels were each associated with higher rwTR likelihood (Table). Predicted rwTR probability, % (95% CI), by TMB and PD-L1 in line 1. Conclusions: TMB and PD-L1 expression are independent markers that, when combined, have increased predictive power for response to IO. High TMB + low/neg PD-L1 behaved similarly to low TMB + high PD-L1, and high TMB + high PD-L1 predicted the highest rwTR. Investigation of these biomarkers as complementary predictors of progression and overall survival is ongoing.[Table: see text]

Correction of copy number induced false positives in CRISPR screens

Cell autonomous cancer dependencies are now routinely identified using CRISPR loss-of-function screens. However, a bias exists that makes it difficult to assess the true essentiality of genes located in amplicons, since the entire amplified region can exhibit lethal scores. These false-positive hits can either be discarded from further analysis, which in cancer models can represent a significant number of hits, or methods can be developed to rescue the true-positives within amplified regions. We propose two methods to rescue true positive hits in amplified regions by correcting for this copy number artefact. The Local Drop Out (LDO) method uses the relative lethality scores within genomic regions to assess true essentiality and does not require additional orthogonal data (e.g. copy number value). LDO is meant to be used in screens covering a dense region of the genome (e.g. a whole chromosome or the whole genome). The General Additive Model (GAM) method models the screening data as a function of the known copy number values and removes the systematic effect from the measured lethality. GAM does not require the same density as LDO, but does require prior knowledge of the copy number values. Both methods have been developed with single sample experiments in mind so that the correction can be applied even in smaller screens. Here we demonstrate the efficacy of both methods at removing the copy number effect and rescuing hits from some of the amplified regions. We estimate a 70-80% decrease of false positive hits in regions of high copy number with either method.

A Descriptive Study of HumanSalmonellaSerotype Typhimurium Infections Reported in Ontario from 1990 to 1997

BACKGROUND:Salmonellainfections cause gastrointestinal and systemic diseases worldwide and are the leading causes of food-borne illnesses in North America (1-4).Salmonellaserotype typhimurium (ST), in particular, is increasingly becoming a major public health concern because of its ability to acquire multiple resistant genes (5,6).OBJECTIVE: To describe demographic, temporal and geographical distributions, and reported risk factors of nonoutbreak cases of ST reported to a surveillance system in Ontario.METHODOLOGY: Descriptive analyses were performed on data on salmonellosiscases reported in Ontario between 1990 and 1998. Direct age- and sex-standardized rates were computed, and temporal trend analyses were performed using simple linear regression and a general additive model with alocally weighted regression (LOESS) smoother.RESULTS: The mean annual rates of infections with allSalmonellaserotypes and with ST were 27 cases per 100,000 persons and 3.7 cases per 100,000 persons, respectively. Males and children under five years of age had significantly higher rates of both ST and ST definitive type 104 (DT104) infections. There was also evidence of temporal clustering of all strains ofSalmonella,with significantly more cases being reported during the summer. Significantly higher rates of ST DT104 were observed in urban areas compared with rural areas, suggesting potential differences in the geographical distribution of risk factors.CONCLUSIONS: Information on demographic, temporal and geographical distributions, and risk factors is critical in planning disease control strategies. Further prospective analytical observation studies are needed to gain a better understanding of the epidemiology of ST and ST DT104 in Ontario, which will better guide disease control decisions.