•We propose a Semantic-kNN (Sk-NN) algorithm for ML.•Sk-NN deploys a process by leveraging on the semantic itemization.•Sk-NN used to filter the training dataset.•The proposed method is more ...efficient, intelligent and better accuracy.
The k-NN algorithm is one of the most renowned ML algorithms widely used in the area of data classification research. With the emergence of big data, the performance and the efficiency of the traditional k-NN algorithm is fast becoming a critical issue. The traditional k-NN algorithm is inefficient to solve the high volume multi-categorical training datasets Traditional k-NN algorithm has a constraint in filtering the training dataset to yield training data that are most relevant to the intended or the targeted test dataset/file. It has to scan through all the training datasets categories to classify the intended/targeted data. As such, traditional k-NN is considered not intelligent and consequently is suffering poor accuracy performance with high computational complexity. A Semantic-kNN (Sk-NN) algorithm for ML is thus proposed in this paper to address the limitations in the traditional k-NN. The proposed Sk-NN deploys a process by leveraging on the semantic itemization and bigram model to filter the training dataset in accordance with the relevant information engaged in the test dataset. It is aimed for general security applications such as finding (the confidentiality level of the data when the algorithm is trained with multiple training categories during the data classification phase. Ultimately, Sk-NN is to elevate the ML performance in pattern extraction and labeling in the big data context.
Although most women with luminal breast cancer do well on endocrine therapy alone, some will develop fatal recurrence thereby necessitating the need to prospectively determine those for whom ...additional cytotoxic therapy will be beneficial. Categorical combinations of immunohistochemical measures of ER, PR, HER2, and KI67 are traditionally used to classify patients into luminal A-like and B-like subtypes for chemotherapeutic reasons, but this may lead to the loss of prognostically relevant information. Here, we compared the prognostic value of quantitative measures of these markers, combined in the IHC4-score, to categorical combinations in subtypes. Using image analysis-based scores for all four markers, we computed the IHC4-score for 2498 patients with luminal breast cancer from two European study populations. We defined subtypes (A-like (ER + and PR + : and HER2- and low KI67) and B-like (ER + and/or PR + : and HER2 + or high KI67)) by combining binary categories of these markers. Hazard ratios and 95% confidence intervals for associations with 10-year breast cancer-specific survival were estimated in Cox proportional-hazard models. We accounted for clinical prognostic factors, including grade, tumor size, lymph-nodal involvement, and age, by using the PREDICT-score. Overall, Subtypes hazard ratio (95% confidence interval) B-like vs. A-like = 1.64 (1.25-2.14); P-value < 0.001 and IHC4-score hazard ratio (95% confidence interval)/1 standard deviation = 1.32 (1.20-1.44); P-value < 0.001 were prognostic in univariable models. However, IHC4-score hazard ratio (95% confidence interval)/1 standard deviation = 1.24 (1.11-1.37); P-value < 0.001; likelihood ratio chi-square (LRχ
) = 12.5 provided more prognostic information than Subtype hazard ratio (95% confidence interval) B-like vs. A-like = 1.38 (1.02-1.88); P-value = 0.04; LRχ
= 4.3 in multivariable models. Further, higher values of the IHC4-score were associated with worse prognosis, regardless of subtype (P-heterogeneity = 0.97). These findings enhance the value of the IHC4-score as an adjunct to clinical prognostication tools for aiding chemotherapy decision-making in luminal breast cancer patients, irrespective of subtype.
Water treatment (WT) is currently among the major areas of research due to the depletion of water resources and fearmongering regarding environmental pollution, which has compelled the upgrading of ...conventional WT technology towards recycling and reuse. This review aims to provide the current state of natural coagulants and their application in the purification of surface water as sufficient clean water is required for household needs, health security, and environmental safety. A thorough and systematic review of the existing literature was performed, and the information related to water treatment using natural coagulants was compiled from 237 articles under various sections using a computerized bibliographic search via PubMed, Scopus, Web of Science, Google Scholar, CAB Abstracts, and several websites. The work provides explicit information related to natural coagulants and their merits and limitations, outlines methods to increase their coagulation performance, and highlights their coagulation mechanism, efficacy, valorization potential, and sustainability. From the information obtained, it can be concluded that although chemical coagulants are efficient in WT, they are usually expensive, toxic, associated with health issues, and thus non-sustainable. A sustainable alternative is the use of natural coagulants, which are readily available, economical, easy to use, biodegradable, non-toxic, eco-friendly, effective, and generate lower sludge volumes. They work via an adsorption process that involves polymeric bridging or neutralization of the charge. The WT efficiency of natural coagulants ranges from 50–500 nephelometric turbidity units (NTUs), which is similar to chemicals. Thus, they can be deployed in WT regimes and can contribute to the health security of rural populations in developing countries. It is unfortunate that, despite the known benefits of natural coagulants, their acceptance, commercialization, and widespread industrial application across the globe are still low. Therefore, there is a need for more exhaustive investigations regarding the mode of action, adoption, and commercialization of natural coagulants as a sustainable alternative to chemicals for a circular economy.
Limited evidence, mostly from studies in Western populations, suggests that the prognostic effects of lifestyle-related risk factors may be molecular subtype-dependent. Here, we examined whether ...pre-diagnostic lifestyle-related risk factors for breast cancer are associated with clinical outcomes by molecular subtype among patients from an understudied Asian population.
In this population-based case series, we evaluated breast cancer risk factors in relation to 10-year all-cause mortality (ACM) and 5-year recurrence by molecular subtype among 3012 women with invasive breast cancer in Sarawak, Malaysia. A total of 579 deaths and 314 recurrence events occurred during a median follow-up period of ~ 24 months. Subtypes (luminal A-like, luminal B-like, HER2-enriched, triple-negative) were defined using immunohistochemical markers for hormone receptors and human epidermal growth factor receptor 2 (HER2) in conjunction with histologic grade. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between risk factors and ACM/recurrence were estimated in subtype-specific Cox regression models.
We observed heterogeneity in the relationships between parity/breastfeeding, age at first full-term pregnancy (FFP), family history, body mass index (BMI), and tumor subtype (p value < 0.05). Among luminal A-like patients only, older age at menarche HR (95% CI)
= 2.28 (1.05, 4.95) and being underweight HR
= 3.46 (1.21, 9.89) or overweight HR
3.14 (1.04, 9.50) were associated with adverse prognosis, while parity/breastfeeding HR
= 0.48 (0.27, 0.85) and older age at FFP HR
= 0.20 (0.04, 0.90) were associated with good prognosis. For these women, the addition of age at menarche, parity/breastfeeding, and BMI, provided significantly better fit to a prognostic model containing standard clinicopathological factors alone LRχ
(8df) = 21.78; p value = 0.005. Overall, the results were similar in relation to recurrence.
Our finding that breastfeeding and BMI were associated with prognosis only among women with luminal A-like breast cancer is consistent with those from previously published data in Western populations. Further prospective studies will be needed to clarify the role of lifestyle modification, especially changes in BMI, in improving clinical outcomes for women with luminal A-like breast cancer.
The eggplant (Solanum melongena L.) is among the vital fruit vegetables cultivated globally for its health and nutritional benefits. However, its production has been hindered by whiteflies (Bemisia ...tabaci G.) infestation worldwide. This study aims to assess the effect of some bio-pesticides in the control of whiteflies on eggplants under field conditions. The trial consists of seventeen (17) treatments replicated three times for 45 days. From the results obtained, neem leaf extract (60 mL/L) proved more effective against whiteflies, with 1.2 and 1.3 adults/leaf, while buttermilk and cow dung (50 mL/L) were less effective (10.1 and 10.8 adults/leaf) when compared to untreated plots (26.9 and 33.4 adults/leaf), two weeks after the third spray during the first and second trials. The highest reduction (%) in whitefly population was found using neem leaf extract (95.7 and 96.1%) and cow urine (85.8 and 96.1%), with cow dung and buttermilk exhibiting the least overall averages (65.9 and 62.3%), two weeks after the third spray during the respective trials. Neem extract and cow urine were more effective among the treatments examined and, thus, recommended to be incorporated into control strategies of whiteflies for the improved production of eggplants in the area.
The whitefly (Bemisia tabaci Gennadius) is a notorious devastating sap-sucking insect pest that causes substantial crop damage and yield losses due to direct feeding by both nymphs and adults and ...also through transmission of viruses and diseases. Although the foliar application of synthetic pesticides is crucial for efficient control of B. tabaci, it has adverse effects such as environmental pollution, resistance and resurgence of the pest, toxicity to pollinators, and crop yield penalty. Thus, a suitable, safe, and robust strategy for the control of whiteflies in the agricultural field is needed. The reports on whitefly-resistant transgenic plants are scanty, non-reproducible, and/or need secondary trials and clearance from the Genetic Engineering Appraisal Committee (GEAC), the Ministry of Environment and Forests (MoEF), and the Environmental Protection Agency (EPA). The present review encompasses explicit information compiled from 364 articles on the traditional, mechanical, biological, biotechnological, and chemical strategies for whitefly management (WFM), IPM strategy, and future prospects of WFM for food and agriculture security.
Purpose
In addition to impacting incidence, risk factors for breast cancer may also influence recurrence and survival from the disease. However, it is unclear how these factors affect combinatorial ...biomarkers for aiding treatment decision-making in breast cancer.
Methods
Patients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1–Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models.
Results
Overall, increasing parity (OR
trend
(95% CI) = 1.20(1.05–1.37);
P
trend
= 0.007), overweight (OR(95% CI)
vs normal
= 1.60(1.29–1.98)), and obesity (OR(95% CI)
vs normal
= 2.12(1.43–3.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (OR
trend
(95% CI) = 0.75(0.66–0.84);
P
trend
< 0.001) and positive family history of breast cancer (FHBC) (OR(95% CI) = 0.66(0.45–0.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI)
vs normal
= 0.82(0.66–1.02)) and obese (OR(95% CI)
vs normal
= 0.52(0.36–0.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status.
Conclusions
Our findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.
Abstract
Background
Emerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk ...of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast.
Methods
The study participants were 4108 healthy women ages 18–75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008–2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models.
Results
With increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP
β
(95% Confidence Interval (CI)) = −0.28 (− 0.43, − 0.13);
P
< 0.001 with ESP peaks at 30–40 years and 60–70 years among pre- and postmenopausal women, respectively. Pregnancy
β
(95%CI)
vs nulligravid
= 0.19 (0.08, 0.30);
P
< 0.001 and increasing number of live births (
P
-trend
< 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP
β
(95%CI)
vs no breastfeeding
= −0.15 (− 0.29, − 0.01);
P
= 0.036. A positive family history of breast cancer (FHBC)
β
(95%CI)
vs no FHBC
= 0.14 (0.02–0.26);
P
= 0.02, being overweight or obese
β
(95%CI)
vs normal weight
= 0.18 (0.06–0.30);
P
= 0.004 and 0.32 (0.21–0.44);
P
< 0.001, respectively, and Black race
β
(95%CI)
vs White
= 0.12 (− 0.005, 0.25);
P
= 0.06 were positively associated with ESP.
Conclusion
Our findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.
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•We evaluated air pollution and markers of breast cancer risk in cancer-free tissue.•PM2.5 levels were positively associated with epithelium-to-stroma proportion.•PM2.5 levels were ...inversely associated with proportion of stromal tissue area.•Associations with PM2.5 varied according to its chemical composition.•Breast histology is a potential pathway by which PM2.5 may influence breast cancer.
Biologic pathways underlying the association between outdoor air pollution and breast cancer risk are poorly understood. Breast tissue composition may reflect cumulative exposure to breast cancer risk factors and has been associated with breast cancer risk among patients with benign breast disease. Herein, we evaluated whether fine particulate matter (PM2.5) was associated with the histologic composition of normal breast tissue.
Machine-learning algorithms were applied to digitized hematoxylin and eosin-stained biopsies of normal breast tissue to quantify the epithelium, stroma, adipose and total tissue area from 3,977 individuals aged 18–75 years from a primarily Midwestern United States population who donated breast tissue samples to the Susan G. Komen Tissue Bank (2009–2019). Annual levels of PM2.5 were assigned to each woman’s residential address based on year of tissue donation. We applied predictive k-means to assign participants to clusters with similar PM2.5 chemical composition and used linear regression to examine the cross-sectional associations between a 5-μg/m3 increase in PM2.5 and square root-transformed proportions of epithelium, stroma, adipose, and epithelium-to-stroma proportion ESP, overall and by PM2.5 cluster.
Higher residential PM2.5 was associated with lower proportion of breast stromal tissue β = -0.93, 95% confidence interval: (-1.52, −0.33), but was not related to the proportion of epithelium β = -0.11 (-0.34, 0.11). Although PM2.5 was not associated with ESP overall β = 0.24 (-0.16, 0.64), the association significantly differed by PM2.5 chemical composition (p-interaction = 0.04), with a positive association evident only among an urban, Midwestern cluster with higher concentrations of nitrate (NO3–) and ammonium (NH4+) β = 0.49 (0.03, 0.95).
Our findings are consistent with a possible role of PM2.5 in breast cancer etiology and suggest that changes in breast tissue composition may be a potential pathway by which outdoor air pollution impacts breast cancer risk. This study further underscores the importance of considering heterogeneity in PM2.5 composition and its impact on breast carcinogenesis.
Heterogeneity of immune gene expression patterns of luminal breast cancer (BC), which is clinically heterogeneous and overall considered as low immunogenic, has not been well studied especially in ...non-European populations. Here, we aimed at characterizing the immune gene expression profile of luminal BC in an Asian population and associating it with patient characteristics and tumor genomic features.
We performed immune gene expression profiling of tumor and adjacent normal tissue in 92 luminal BC patients from Hong Kong using RNA-sequencing data and used unsupervised consensus clustering to stratify tumors. We then used luminal patients from The Cancer Genome Atlas (TCGA, N = 564) and a Korean breast cancer study (KBC, N = 112) as replication datasets.
Based on the expression of 130 immune-related genes, luminal tumors were stratified into three distinct immune subtypes. Tumors in one subtype showed higher level of tumor-infiltrating lymphocytes (TILs), characterized by T cell gene activation, higher expression of immune checkpoint genes, higher nonsynonymous mutation burden, and higher APOBEC-signature mutations, compared with other luminal tumors. The high-TIL subtype was also associated with lower ESR1/ESR2 expression ratio and increasing body mass index. The comparison of the immune profile in tumor and matched normal tissue suggested a tumor-derived activation of specific immune responses, which was only seen in high-TIL patients. Tumors in a second subtype were characterized by increased expression of interferon-stimulated genes and enrichment for TP53 somatic mutations. The presence of three immune subtypes within luminal BC was replicated in TCGA and KBC, although the pattern was more similar in Asian populations. The germline APOBEC3B deletion polymorphism, which is prevalent in East Asian populations and was previously linked to immune activation, was not associated with immune subtypes in our study. This result does not support the hypothesis that the germline APOBEC3B deletion polymorphism is the driving force for immune activation in breast tumors in Asian populations.
Our findings suggest that immune gene expression and associated genomic features could be useful to further stratify luminal BC beyond the current luminal A/B classification and a subset of luminal BC patients may benefit from checkpoint immunotherapy, at least in Asian populations.
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