Seasonal prediction of Horn of Africa long rains using machine learning: the pitfalls of preselecting correlated predictors

The Horn of Africa is highly vulnerable to droughts and floods, and reliable long-term forecasting is a key part of building resilience. However, the prediction of the “long rains” season (March–May) is particularly challenging for dynamical climate prediction models. Meanwhile, the potential for machine learning to improve seasonal precipitation forecasts in the region has yet to be uncovered. Here, we implement and evaluate four data-driven models for prediction of long rains rainfall: ridge and lasso linear regressions, random forests and a single-layer neural network. Predictors are based on SSTs, zonal winds, land state, and climate indices, and the target variables are precipitation totals for each separate month (March, April, and May) in the Horn of Africa drylands, with separate predictions made for lead-times of 1–3 months. Results reveal a tendency for overfitting when predictors are preselected based on correlations to the target variable over the entire historical period, a frequent practice in machine learning-based seasonal forecasting. Using this conventional approach, the data-driven methods—and particularly the lasso and ridge regressions—often outperform dynamical seasonal hindcasts. However, when the selection of predictors is done independently of both the train and test data, by performing this predictor selection within the cross-validation loop, the performance of all four data-driven models is poorer than that of the dynamical hindcasts. These findings should not discourage future applications of machine learning for rainfall forecasting in the region. Yet, they should be seen as a note of caution to prevent optimistically biased results that are not indicative of the true power in operational forecast systems

Acatalasemic mice are mildly susceptible to adriamycin nephropathy and exhibit increased albuminuria and glomerulosclerosis

Background: Catalase is an important antioxidant enzyme that regulates the level of intracellular hydrogen peroxide and hydroxyl radicals. The effects of catalase deficiency on albuminuria and progressive glomerulosclerosis have not yet been fully elucidated. The adriamycin (ADR) nephropathy model is considered to be an experimental model of focal segmental glomerulosclerosis. A functional catalase deficiency was hypothesized to exacerbate albuminuria and the progression of glomerulosclerosis in this model. Methods: ADR was intravenously administered to both homozygous acatalasemic mutant mice (C3H/AnLCs(b)Cs(b)) and control wild-type mice (C3H/AnLCs(a)Cs(a)). The functional and morphological alterations of the kidneys, including albuminuria, renal function, podocytic, glomerular and tubulointerstitial injuries, and the activities of catalase were then compared between the two groups up to 8 weeks after disease induction. Moreover, the presence of a mutation of the toll-like receptor 4 (tlr4) gene, which was previously reported in the C3H/HeJ strain, was investigated in both groups. Results: The ADR-treated mice developed significant albuminuria and glomerulosclerosis, and the degree of these conditions in the ADR-treated acatalasemic mice was higher than that in the wild-type mice. ADR induced progressive renal fibrosis, renal atrophy and lipid peroxide accumulation only in the acatalasemic mice. In addition, the level of catalase activity was significantly lower in the kidneys of the acatalasemic mice than in the wild-type mice during the experimental period. The catalase activity increased after ADR injection in wild-type mice, but the acatalasemic mice did not have the ability to increase their catalase activity under oxidative stress. The C3H/AnL strain was found to be negative for the tlr4 gene mutation. Conclusions: These data indicate that catalase deficiency plays an important role in the progression of renal injury in the ADR nephropathy model

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland

Broad and narrow personality traits as markers of one-time and repeated suicide attempts: A population-based study

<p>Abstract</p> <p>Background</p> <p>Studying personality traits with the potential to differentiate between individuals engaging in suicide attempts of different degrees of severity could help us to understand the processes underlying the link of personality and nonfatal suicidal behaviours and to identify at-risk groups. One approach may be to examine whether narrow, i.e., lower-order personality traits may be more useful than their underlying, broad personality trait dimensions.</p> <p>Methods</p> <p>We investigated qualitative and quantitative differences in broad and narrow personality traits between one-time and repeated suicide attempters in a longitudinal, population-based sample of young French Canadian adults using two multivariate regression models.</p> <p>Results</p> <p>One broad (Compulsivity: OR = 2.0; 95% CI 1.2–3.5) and one narrow personality trait (anxiousness: OR = 1.1; 95% CI 1.01–1.1) differentiated between individuals with histories of repeated and one-time suicide attempts. Affective instability [(OR = 1.1; 95% CI 1.04–1.1)] and anxiousness [(OR = .92; 95% CI .88–.95)], on the other hand, differentiated between nonattempters and one-time suicide attempters.</p> <p>Conclusion</p> <p>Emotional and cognitive dysregulation and associated behavioural manifestations may be associated with suicide attempts of different severity. While findings associated with narrow traits may be easier to interpret and link to existing sociobiological theories, larger effect sizes associated with broad traits such as Compulsivity may be better suited to objectives with a more clinical focus.</p

Oxidative/Nitrative Stress and Inflammation Drive Progression of Doxorubicin-Induced Renal Fibrosis in Rats as Revealed by Comparing a Normal and a Fibrosis-Resistant Rat Strain

Chronic renal fibrosis is the final common pathway of end stage renal disease caused by glomerular or tubular pathologies. Genetic background has a strong influence on the progression of chronic renal fibrosis. We recently found that Rowett black hooded rats were resistant to renal fibrosis. We aimed to investigate the role of sustained inflammation and oxidative/nitrative stress in renal fibrosis progression using this new model. Our previous data suggested the involvement of podocytes, thus we investigated renal fibrosis initiated by doxorubicin-induced (5 mg/kg) podocyte damage. Doxorubicin induced progressive glomerular sclerosis followed by increasing proteinuria and reduced bodyweight gain in fibrosis-sensitive, Charles Dawley rats during an 8-week long observation period. In comparison, the fibrosis-resistant, Rowett black hooded rats had longer survival, milder proteinuria and reduced tubular damage as assessed by neutrophil gelatinase-associated lipocalin (NGAL) excretion, reduced loss of the slit diaphragm protein, nephrin, less glomerulosclerosis, tubulointerstitial fibrosis and matrix deposition assessed by periodic acid-Schiff, Picro-Sirius-red staining and fibronectin immunostaining. Less fibrosis was associated with reduced profibrotic transforming growth factor-beta, (TGF-beta1) connective tissue growth factor (CTGF), and collagen type I alpha 1 (COL-1a1) mRNA levels. Milder inflammation demonstrated by histology was confirmed by less monocyte chemotactic protein 1 (MCP-1) mRNA. As a consequence of less inflammation, less oxidative and nitrative stress was obvious by less neutrophil cytosolic factor 1 (p47phox) and NADPH oxidase-2 (p91phox) mRNA. Reduced oxidative enzyme expression was accompanied by less lipid peroxidation as demonstrated by 4-hydroxynonenal (HNE) and less protein nitrosylation demonstrated by nitrotyrosine (NT) immunohistochemistry and quantified by Western blot. Our results demonstrate that mediators of fibrosis, inflammation and oxidative/nitrative stress were suppressed in doxorubicin nephropathy in fibrosis-resistant Rowett black hooded rats underlying the importance of these pathomechanisms in the progression of renal fibrosis initiated by glomerular podocyte damage

Pollutant effects on genotoxic parameters and tumor-associated protein levels in adults: a cross sectional study

<p>Abstract</p> <p>Background</p> <p>This study intended to investigate whether residence in areas polluted by heavy industry, waste incineration, a high density of traffic and housing or intensive use of pesticides, could contribute to the high incidence of cancer observed in Flanders.</p> <p>Methods</p> <p>Subjects were 1583 residents aged 50–65 from 9 areas with different types of pollution. Cadmium, lead, p,p'-DDE, hexachlorobenzene, PCBs and dioxin-like activity (Calux test) were measured in blood, and cadmium, t,t'-muconic acid and 1-hydroxypyrene in urine. Effect biomarkers were prostate specific antigen, carcinoembryonic antigen and p53 protein serum levels, number of micronuclei per 1000 binucleated peripheral blood cells, DNA damage (comet assay) in peripheral blood cells and 8-hydroxy-deoxyguanosine in urine. Confounding factors were taken into account.</p> <p>Results</p> <p>Overall significant differences between areas were found for carcinoembryonic antigen, micronuclei, 8-hydroxy-deoxyguanosine and DNA damage. Compared to a rural area with mainly fruit production, effect biomarkers were often significantly elevated around waste incinerators, in the cities of Antwerp and Ghent, in industrial areas and also in other rural areas. Within an industrial area DNA strand break levels were almost three times higher close to industrial installations than 5 kilometres upwind of the main industrial installations (p < 0.0001). Positive exposure-effect relationships were found for carcinoembryonic antigen (urinary cadmium, t,t'-muconic acid, 1-hydroxypyrene and blood lead), micronuclei (PCB118), DNA damage (PCB118) and 8-hydroxy-deoxyguanosine (t,t'-muconic acid, 1-hydroxypyrene). Also, we found significant associations between values of PSA above the p90 and higher values of urinary cadmium, between values of p53 above the p90 and higher serum levels of p,p'-DDE, hexachlorobenzene and marker PCBs (PCB 138, 153 and 180) and between serum levels of p,p'-DDE above the p90 and higher serum values of carcinoembryonic antigen. Significant associations were also found between effect biomarkers and occupational or lifestyle parameters.</p> <p>Conclusion</p> <p>Levels of internal exposure, and residence near waste incinerators, in cities, or close to important industries, but not in areas with intensive use of pesticides, showed positive correlations with biomarkers associated with carcinogenesis and thus probably contribute to risk of cancer. In some rural areas, the levels of these biomarkers were not lower than in the rest of Flanders.</p