A study of violent behaviour among in-patients in a psychiatric hospital

A retrospective analysis of the violent incident forms returned over a one year period in a psychiatric hospital recorded 283 incidents involving 144 patients. Almost all were of a petty nature, none leading to lasting injuries. Compared with the average daily in-patient population, offending patients were more likely to be male, to be less than 45 years old, and to have a diagnosis of schizophrenia.

Language matters. Addressing the use of language in the care of people with diabetes: position statement of the English Advisory Group

The language used by healthcare professionals can have a profound impact on how people living with diabetes, and those who care for them, experience their condition and feel about living with it day-to-day. At its best, good use of language, both verbal and written, can lower anxiety, build confidence, educate and help to improve self-care. Conversely, poor communication can be stigmatizing, hurtful and undermining of self-care and can have a detrimental effect on clinical outcomes. The language used in the care of those with diabetes has the power to reinforce negative stereotypes, but it also has the power to promote positive ones. The use of language is controversial and has many perspectives. The development of this position statement aimed to take account of these as well as the current evidence base. A working group, representing people with diabetes and key organizations with an interest in the care of people with diabetes, was established to review the use of language. The work of this group has culminated in this position statement for England. It follows the contribution of Australia and the USA to this important international debate. The group has set out practical examples of language that will encourage positive interactions with those living with diabetes and subsequently promote positive outcomes. These examples are based on a review of the evidence and are supported by a simple set of principles.

Spatially Resolved Molecular Compositions of Insoluble Multilayer Deposits Responsible for Increased Pollution from Internal Combustion Engines

Internal combustion engines are used heavily in diverse applications worldwide. Achieving the most efficient operation is key to improving air quality as society moves to a decarbonized energy system. Insoluble deposits that form within internal combustion engine components including fuel injectors and filters negatively impact CO₂ and pollutant emissions. Understanding the composition, origins, and formation mechanisms of these complex materials will be key to their mitigation however, previous attempts only afforded nondiagnostic chemical assignments and limited knowledge toward this. Here, we uncover the identity and spatial distribution of molecular species from a gasoline direct injector, diesel injector, and filter deposit in situ using a new hyphenation of secondary ion mass spectrometry and the state-of-the-art Orbitrap mass analyzer (3D OrbiSIMS) and elemental analysis. Through a high mass resolving power and tandem MS we unambiguously uncovered the identity, distribution, and origin of species including alkylbenzyl sulfonates and provide evidence of deposit formation mechanisms including formation of longer chain sulfonates at the gasoline deposit's surface as well as aromatization to form polycyclic aromatic hydrocarbons up to C₆₆H₂₀, which were prevalent in the lower depth of this deposit. Inorganic salts contributed significantly to the diesel injector deposit throughout its depth, suggesting contamination over multiple fueling cycles. Findings will enable several strategies to mitigate these insoluble materials such as implementing stricter worldwide fuel specifications, modifying additives with adverse reactivity, and synthesizing new fuel additives to solubilize deposits in the engine, thereby leading to less polluting vehicles.

Prescribing in pregnancy for women with diabetes: use of potential teratogenic drugs and contraception

AIMS

To describe contraception use and the prescription of drugs that are either not recommended in pregnancy or are potentially teratogenic by diabetes type in women of child-bearing age.

METHODS

Retrospective, cross-sectional chart review undertaken in 22 general practices in Warwickshire, UK. Demographic, anthropometric, medical history, medication and contraception data were extracted from women aged 14 to 49 years with pre-existing diabetes. Independent sample t-test, Mann-Whitney test and χ(2) -test were used to test for univariable associations and multiple logistic regression was used to adjust for confounders.

RESULTS

Four hundred and seventy eligible women were identified; the majority had a diagnosis of Type 2 diabetes (67%). Thirty-six per cent and 64% of women with Type 1 and Type 2 diabetes, respectively, were prescribed drugs not recommended for use in pregnancy (P < 0.001). Less than half were using concomitant contraception (P < 0.001). No significant difference of contraception use was observed between women who were and were not taking drugs not recommended for use in pregnancy (40 vs. 41%, P = 0.4).

CONCLUSIONS

Use of drugs not recommended during pregnancy in women with diabetes of child-bearing age is common but is not associated with increased use of contraception. There is need to identify and overcome barriers to effective contraception use for this population group in order to facilitate optimal management of cardiovascular risk.

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets

Modern mass spectrometry techniques produce a wealth of spectral data, and although this is an advantage in terms of the richness of the information available, the volume and complexity of data can prevent a thorough interpretation to reach useful conclusions. Application of molecular formula prediction (MFP) to produce annotated lists of ions that have been filtered by their elemental composition and considering structural double bond equivalence are widely used on high resolving power mass spectrometry datasets. However, this has not been applied to secondary ion mass spectrometry data. Here, we apply this data interpretation approach to 3D OrbiSIMS datasets, testing it for a series of increasingly complex samples. In an organic on inorganic sample, we successfully annotated the organic contaminant overlayer separately from the substrate. In a more challenging purely organic human serum sample we filtered out both proteins and lipids based on elemental compositions, 226 different lipids were identified and validated using existing databases, and we assigned amino acid sequences of abundant serum proteins including albumin, fibronectin, and transferrin. Finally, we tested the approach on depth profile data from layered carbonaceous engine deposits and annotated previously unidentified lubricating oil species. Application of an unsupervised machine learning method on filtered ions after performing MFP from this sample uniquely separated depth profiles of species, which were not observed when performing the method on the entire dataset. Overall, the chemical filtering approach using MFP has great potential in enabling full interpretation of complex 3D OrbiSIMS datasets from a plethora of material types.

Time resolved growth of (N)-polycyclic aromatic hydrocarbons in engine deposits uncovered with OrbiSIMS depth profiling

Insoluble carbonaceous deposits were grown in internal combustion engine components and interrogated by OrbiSIMS depth profiling, and we uncovered the composition and proposed time resolved growth mechanisms of these materials.