Hematoxylin

The streptavidin alkaline phosphatase method was adapted to detect the viral antigen using a polyclonal anti-ZIKV antibody produced at the Evandro Chagas Institute^{2 (link)}. The biotin-streptavidin peroxidase method was used for immunostaining of tissues with antibodies specific for each marker studied. First, the tissue samples were deparaffinized in xylene and hydrated in a decreasing ethanol series (90%, 80%, and 70%). Endogenous peroxidase was blocked by incubating the sections in 3% hydrogen peroxide for 45 min. Antigen retrieval was performed by incubation in citrate buffer, pH 6.0, or EDTA, pH 9.0, for 20 min at 90 °C. Nonspecific proteins were blocked by incubating the sections in 10% skim milk for 30 min. The histological sections were then incubated overnight with the primary antibodies diluted in 1% bovine serum albumin (Supplementary Table S1). After this period, the slides were immersed in 1 × PBS and incubated with the secondary biotinylated antibody (LSAB, DakoCytomation) in an oven for 30 min at 37 °C. The slides were again immersed in 1X PBS and incubated with streptavidin peroxidase (LSAB, DakoCytomation) for 30 min at 37 °C. The reactions were developed with 0.03% diaminobenzidine and 3% hydrogen peroxide as the chromogen solution. After this step, the slides were washed in distilled water and counterstained with Harris hematoxylin for 1 min. Finally, the sections were dehydrated in an increasing ethanol series and cleared in xylene.

Preprocessing steps were applied as described above. QuPath’s Cell detection command was then used to identify cells across all cores based upon nuclear staining. This command additionally estimates the full extent of each cell based upon a constrained expansion of the nucleus region, and calculates up to 33 measurements of intensity and morphology, including nucleus area, circularity, staining intensity for hematoxylin and DAB, and nucleus/cell area ratio. Because not all of these measurements are expected to provide independent or useful information with regard to cell classification, a subset of 16 measurements was chosen empirically and supplemented for each cell by measuring the local density of cells, and taking a Gaussian-weighted sum of the corresponding measurements within neighboring cells using QuPath’s Add smoothed features command. A two-way random trees classifier was then interactively trained to distinguish tumor epithelial cells from all other detections (comprising non-epithelial cells, necrosis, or any artefacts misidentified as cells) and applied across all slides (see Supplementary Video 2). Intensity thresholds were set to further subclassify tumor cells as being negative, weak, moderate or strongly positive for p53 staining based upon mean nuclear DAB optical densities. An H-score was calculated for each tissue core by adding 3x% strongly stained tumor nuclei, 2x% moderately stained tumor nuclei, and 1x% weakly stained tumor nuclei^{32 (link)}, giving results in the range 0 (all tumor nuclei negative) to 300 (all tumor nuclei strongly positive).

After the initial TMA preprocessing steps described above, analysis of CD3 and CD8 was performed using QuPath’s Simple tissue detection and Fast cell counts commands. Briefly, tissue was detected within each TMA core by thresholding a downsampled and smoothed image of the core, followed by cleanup of the resulting binary image by morphological operations. Individual cells were identified by separating stains using color deconvolution and identifying peaks in either the hematoxylin channel (CD3) or sum of the hematoxylin and DAB channels (CD8) after smoothing, and assigning these as positive or negative cells based upon the smoothed DAB channel information. The number of positive cells and area detected were used to calculate the average number of positive cells per mm², and these results exported along with markup images showing the detected cells, for visual verification. The detection and export steps were fully automated using a batch processing script.

Authorizations for reporting these three cases were granted by the Eastern Ontario Regional Forensic Unit and the Laboratoire de Sciences Judiciaires et de Médecine Légale du Québec.
The sampling followed a relatively standardized protocol for all TBI cases: samples were collected from the cortex and underlying white matter of the pre-frontal gyrus, superior and middle frontal gyri, temporal pole, parietal and occipital lobes, deep frontal white matter, hippocampus, anterior and posterior corpus callosum with the cingula, lenticular nucleus, thalamus with the posterior limb of the internal capsule, midbrain, pons, medulla, cerebellar cortex and dentate nucleus. In some cases, gross pathology (e.g. contusions) mandated further sampling along with the dura and spinal cord if available. The number of available sections for these three cases was 26 for case1, and 24 for cases 2 and 3.
For the detection of ballooned neurons, all HE or HPS sections, including contusions, were screened at 200×.
Representative sections were stained with either hematoxylin–eosin (HE) or hematoxylin-phloxin-saffron (HPS). The following histochemical stains were used: iron, Luxol-periodic acid Schiff (Luxol-PAS) and Bielschowsky. The following antibodies were used for immunohistochemistry: glial fibrillary acidic protein (GFAP) (Leica, PA0026,ready to use), CD-68 (Leica, PA0073, ready to use), neurofilament 200 (NF200) (Leica, PA371, ready to use), beta-amyloid precursor-protein (β-APP) (Chemicon/Millipore, MAB348, 1/5000), αB-crystallin (EMD Millipore, MABN2552 1/1000), ubiquitin (Vector, 1/400), β-amyloid (Dako/Agilent, 1/100), tau protein (Thermo/Fisher, MN1020 1/2500), synaptophysin (Dako/Agilent, ready to use), TAR DNA binding protein 43 (TDP-43) ((Protein Tech, 10,782-2AP, 1/50), fused in sarcoma binding protein (FUS) (Protein tech, 60,160–1-1 g, 1/100), and p62 (BD Transduc, 1/25). In our index cases, the following were used for the evaluation of TAI: β-APP, GFAP, CD68 and NF200; for the neurodegenerative changes: αB-crystallin, NF200, ubiquitin, tau protein, synaptophysin, TDP-43, FUS were used.
For the characterization of the ballooned neurons only, two cases of fronto-temporal lobar degeneration, FTLD-Tau, were used as controls. One was a female aged 72 who presented with speech difficulties followed by neurocognitive decline and eye movement abnormalities raising the possibility of Richardson’s disorder. The other was a male aged 67 who presented with a primary non-fluent aphasia progressing to fronto-temporal demαentia. In both cases, the morphological findings were characteristic of a corticobasal degeneration.

The paraffin-embedded tissue sections were subjected to dewaxing, rehydration, as well as antigen repair. Next, the tissue sections were incubated at 4 °C overnight with Ki67 (1:100, Cell Signaling Technology), MAPK6 (1:50, Abcam) and Caspase-7-specific antibody (1:500, Abcam) followed by 1-h incubation at 37 °C with the biotin-labeled secondary antibody. Lastly, the tissues were stained with DAB and hematoxylin.

We selected three key proteins of the PI3K-Akt signaling pathway, including ErbB2, PIK3R1, and AKT3, to verify the pathway predictions. After dewaxing, the sections were subjected to antigen retrieval at high temperature and pressure for 3 min, washed with water, incubated with 3% hydrogen peroxide at room temperature for 10 min, washed again three times, and then placed in phosphate-buffered saline solution. We blocked the sections with 5% fetal bovine serum for 30 min, then added the first antibody for overnight incubation at 4 °C. The next day, the sections were washed three times, then incubated with a secondary antibody at room temperature for 30 min and washed three times. We then incubated the sections for 1–3 min with diaminobenzidine chromogenic solution, lightly stained the nuclei with hematoxylin, and differentiated the sections with 0.5% hydrochloric acid ethanol for 2 s. After three washes, the sections were dehydrated with graded alcohol, made transparent, and sealed with neutral gum. The antibodies used in the study were raised against CgA (dilution 1:1000, GT211407; Gene Tech, CHINA), SYP (dilution 1:1000, GT206507; Gene Tech), ErbB2 (dilution 1:1000, GT224507; Gene Tech), PIK3R1 (dilution 1:1000, ER64588; HUABIO), and AKT3 (dilution 1:1000, ER62638; HUABIO).
Based on the 2010 World Health Organization classification system, we examined two neuroendocrine biomarkers, CgA and SYP. Specimens in which CgA and/or SYP were present in 2–30% of immunoreactive cells were classified as NED [1 (link)]. All immunohistochemical sections were evaluated by two senior pathologists.