3,5-diisopropylsalicylic acid

The Breakthrough Generations Study is a long-term prospective cohort study focussed on potential aetiological factors for breast cancer in women. It has received appropriate ethics committee approval. The study cohort consists of volunteer women aged 16 years or older at entry. They have been recruited from the general population of the British Isles, and were initially identified from three principal sources. The first source was women on the list of supporters of Breakthrough Breast Cancer, the charity who funded the study. Secondly, as a consequence of publicity, especially at the launch of the study in September 2004, tens of thousands of women contacted the study team to express their interest via our website and telephone lines, or less often by personal contact. Thirdly, women who joined the study were asked if they would nominate female friends and family aged 16 years and older who they thought might also be interested in joining. The probands could discuss the study with the nominees, or not, as they wished, before nominating them.
Women from all these sources were mailed an initial invitation letter and information booklet explaining the study, and a form asking whether they would like to be sent the study pack, without obligation. Those who assented were mailed the study pack, which included a questionnaire, information booklet, consent form and blood pack. If they chose to take part, the women completed and returned to us the consent form and questionnaire. A freephone number was provided to answer any queries. For the blood sample, the majority took their blood pack to their general practice, where a 27-ml blood sample was taken and the cohort member then posted the blood tubes, at ambient temperature, to our laboratory. Some blood samples (<10%) were taken by nurses working for the study, and some samples were taken by others – for instance, phlebotomists at the subject's workplace, nurses or doctors in hospitals, or nurses or doctors otherwise known to the subjects.
For hormone and certain other analyses, it is highly desirable that blood samples be centrifuged, aliquoted and frozen down on the day of receipt. Thus, unlike a study solely collecting questionnaires, which can mail tens of thousands of questionnaires within a few days and then store the returns and process them subsequently over several months, a study collecting plasma needs to receive samples at as constant a rate as possible, avoiding peaks that exceed the laboratory's capacity, or dips that waste laboratory staff time and overhead costs. To achieve this, as we could not control when subjects chose to donate blood and post it, we calibrated the mailing-out rates to generate as constant a flow as possible, based on our experience of the time distribution of response times obtained in the initial stages of the study, allowing for day of the week and season of the year.
When premenopausal women joined the study, they were asked that if possible they should present for venipuncture at a standard point in their menstrual cycle, 7 days before they expected their next period, but if this was not possible, nevertheless to send a blood sample taken when practical. When the subjects returned their blood samples, they also returned a form on which they had recorded several variables relevant to the sample, including the time and date the sample was taken, the time the subject woke on that day, the date of their last menstrual period, and whether they were taking various medicines and supplements.

HE staining was conducted according to routine protocols [17 (link)]. Briefly, after deparaffinization and rehydration, 5 μm longitudinal sections were stained with hematoxylin solution for 5 min followed by 5 dips in 1% acid ethanol (1% HCl in 70% ethanol) and then rinsed in distilled water. Then the sections were stained with eosin solution for 3 min and followed by dehydration with graded alcohol and clearing in xylene. The mounted slides were then examined and photographed using an Olympus BX53 fluorescence microscope (Tokyo, Japan). The staining intensity of the trabecular bone was analyzed by Image-Pro Plus 6.0 software and expressed as IOD value.

Raw top-view movies were processed with custom MATLAB code. For RGB movies, the 80th percentile of a manually or automatically selected set of frames was used as background that was subtracted from all the frames. Then both for RGB and thermal movies, a threshold was manually selected on a GUI, and the resulting binary mask underwent a series of simple treatments: morphological closing, removal of small objects, another morphological closing and finally morphological opening. The values for the different parameters were set to accommodate the different conditions. For each frame, mice contour and center of gravity were obtained from the resulting mask and saved. A calibration (px_movie / cm_{real object} ratio) was also obtained from a manually drawn segment and the corresponding length of the object in cm, for later normalization. In the following analysis steps, speed and mouse position were derived from the center of gravity coordinates, which were slightly smoothed with a median filter. In addition, to capture general activity, even in the absence of locomotion, a motion measure was used: it is computed as percentage of pixel change in the mouse masks from one frame to the next (nonoverlapping pixels/total pixel count). Several body parts (snout, ears, front and hind paws and tail) were also tracked with python-code-based DeepLabCut^{52 (link),53 (link)}. Briefly, a Resnet-152 network was iteratively trained and refined on ~1,350 frames to be as performant as possible in all our various recording conditions and in particular yield accurate tail tracking (cf thermal data extraction). To not sacrifice any accuracy, only coordinates with a score ≥0.99 were included, and no interpolation was applied. A semi-automated threshold-based GUI was used to annotate the following behaviors: rearing, grooming, stretch-attend posture, head dips, immobility, fast locomotion and so-called area-bound (not any of the other defined behaviors, in particular, no immobility and no locomotion). Briefly, for each behavior, a global score was obtained from relevant position information, body parts’ angles/distances/speed and thresholded with their respective hard-coded thresholds. The behavioral bouts resulting from that initial detection were displayed in a GUI together with the original movie and the scores. The thresholds could then be dragged manually, updating the detected events plots, to get the best possible detection. Events were then checked and adjusted manually when needed within the same GUI, and occasional periods of obstruction (for example, cable between the camera and the mouse) were marked for later exclusion. In the specific case of the LDB, because the RGB camera was not able to capture the mouse’s activity in the dark side, thermal movies were used for behavioral detection. To this end, thermal movies were re-exported with a black-and-white color map, after inverting the intensities and adjusting the contrast, so that the resulting frames resemble their RGB counterparts. A DeepLabCut network was derived from our main network and refined with those new movies (tail points were discarded because of their changing nature on thermal movies). The tracked body parts were then used as previously mentioned to detect behaviors. Mouse tracking was performed blind to the conditions of the experiments.

In September 2020, a preliminary survey was conducted in the study sites, and most of the larval habitats were found to be located approximately 2 km from the centre of each community (Fig. 2). These areas were selected for detailed study. Thorough searches of Anopheles larval habitats (e.g., man-made ponds, wells, swamps, furrows, puddles) were conducted and their locations mapped using a global positioning system (GPS: Garmin etrex^® 10) unit. A total of 59 larval habitats within the study sites, identified to consistently have immature mosquitoes, were chosen: 18 in Dodowa, and 42 in Anyakpor (Fig. 2). These 59 positive habitats were sampled for mosquito larvae once every two weeks from October 2020 to May 2021.Fig. 2

The study sites and locations of larval habitats

Individual habitats were numbered, and their surface area recorded along with the land use type and vegetation cover. The percentage of vegetation covering the surface of the habitats was visually estimated, and categorized as: 0 if vegetation was not present in the habitat, ≤ 24% surface coverage, and 25–49, 50–74 and 75–100% surface coverage [41 (link)]. Habitats were classified into land use types based on the activities taking place on the land where the larval habitat was found. During each survey, the physiochemical properties (temperature, pH, conductivity, dissolved oxygen, temperature, salinity, total dissolved solids (TDS) of the water in the habitats were measured on site using handheld multi-parameter tester (APERA Instrument PC60 Premium Multi-Parameter) based on guidelines provided by the manufacturer. The multi-parameter was calibrated and rinsed with distilled water before each use.
The larval habitats were grouped into temporary or permanent habitats. Temporary habitats were mainly rain-dependent and dried up when rain ceased for a while [43 (link)]. The permanent habitats was defined as habitats in which Anopheles larvae were found at least once, and contained water that was fed by natural underground sources throughout the sampling period [43 (link)].
Habitat stability was indicated by the availability of water in a habitat for 14 days, following previous reported studies that showed that egg-adult cycle of An. gambiae s.l. can be completed in this length of time [17 (link), 37 (link)]. To determine productivity, the habitats were visited and examined once every two weeks for the presence of aquatic stages of anopheline and culicine mosquitoes. In addition, the area (length and width) of the water surface was measured and recorded in metres with a metal ruler and grouped as small (≤ 10 m²) or large (10–100 m²).
Mosquito larval surveys were also carried out to generate stage-specific estimates of larval densities. Water was dipped up to 20 times using a standard dipper (350 mL, BioQuip Products, Inc., CA, USA). When a habitat was too small to make 20 dips, water was dipped as many times as possible. Larval abundance was calculated as the number of larvae per number of dips made in each habitat. The number of larvae and pupae in each habitat was collected and recorded, with larvae classified as early instars (L1 and L2) or late instars (L3 and L4). Larval samples collected from each habitat were pooled into sterile plastic containers and transported to the insectary of the Department of Medical Microbiology, University of Ghana Medical School, where they were bred into adults. At the insectary, the larvae were fed on Tetramin^® fish meal and maintained at 27 ± 2 °C.