Breast cancer is diagnosed using histopathological imaging. This task is extremely time-consuming due to high image complexity and volume. However, it is important to facilitate the early detection of breast cancer for medical intervention. Deep learning (DL) has become popular in medical imaging solutions and has demonstrated various levels of performance in diagnosing cancerous images. Nonetheless, achieving high precision while minimizing overfitting remains a significant challenge for classification solutions. The handling of imbalanced data and incorrect labeling is a further concern. Additional methods, such as pre-processing, ensemble, and normalization techniques, have been established to enhance image characteristics. These methods could influence classification solutions and be used to overcome overfitting and data balancing issues. Hence, developing a more sophisticated DL variant could improve classification accuracy while reducing overfitting. Technological advancements in DL have fueled automated breast cancer diagnosis growth in recent years. This paper reviewed studies on the capability of DL to classify histopathological breast cancer images, as the objective of this study was to systematically review and analyze current research on the classification of histopathological images. Additionally, literature from the Scopus and Web of Science (WOS) indexes was reviewed. This study assessed recent approaches for histopathological breast cancer image classification in DL applications for papers published up until November 2022. The findings of this study suggest that DL methods, especially convolution neural networks and their hybrids, are the most cutting-edge approaches currently in use. To find a new technique, it is necessary first to survey the landscape of existing DL approaches and their hybrid methods to conduct comparisons and case studies.

Background: Research in natural substances for their anticancer potential has become increasingly popular. Lunasin, a soybean protein, is known to inhibit cancer progression via various pathways. The aim of this study was to investigate the effect of Lunasin Extract (LE) on the expression of Intercellular Adhesion Molecule 1 (ICAM-1) and epithelial cadherins (E-Cadherin) in breast cancer. Methods: In this true-experimental in vivo study, 24 Sprague-Dawley rats that were induced by 7,12-Dimethylbenz[a]anthracene (DMBA), were used. Based on the therapy given, the groups were divided into, normal, positive control (PC), negative control (NC), adjuvant, curative, and preventive. Lunasin was extracted from soybean seeds of the Grobogan variety in Indonesia. Tissue samples were obtained, processed, stained with anti-ICAM-1 and anti-E-Cadherin antibodies, examined under a microscope, and quantified using H-score. The data were analyzed using ANOVA, which was then followed by Duncan's test. Results: Statistically significant difference in ICAM-1 expression was observed between the following groups: adjuvant and NC, normal and NC, PC and NC, adjuvant and preventive, normal and preventive, PC and preventive, adjuvant and curative, normal and curative, PC and curative. E-Cadherin expression was significantly different between preventive and NC, adjuvant and NC, PC and NC, normal and NC, adjuvant and curative, PC and curative, normal and curative, normal and preventive. Significant negative correlation was found between ICAM-1 and E-Cadherin [-0.616 (-0.8165; -0.283)] with p = 0.001. Conclusion: Preventive dose of LE was able to reduce ICAM-1 expression while increasing E-Cadherin expression.

Background. Colorectal cancer (CRC) is a malignancy derived from the glandular epithelial cells in the colon. Patients with inflammatory bowel disease (IBD) are more likely to develop CRC. Cancer proliferation is characterized by the loss of inhibition of apoptosis, which involves caspase-3 activation. This study examined the effects of the pomegranate peel extract on the expression of caspase-3 in mice crypt cells induced by dextran sodium sulfate (DSS) 2. Methods. The experimental study was done in six groups. All treatments were done in 42 days. The groups were all induced by DSS through water drinking, except for the normal group, which was only given water. The treatments given included the pomegranate extract in two doses (240mg and 480mg/kg bw/day), aspirin, and ellagic acid. The specimens were then fixated and stained for the immunohistochemistry scoring for the expression of caspase-3, which was then analyzed statistically. Results. The H-scores of each treatment group were 213.23±8.32 (DSS group), 243.81±18.69 (normal group), 226.10±12.38 (pomegranate peel extract of 240mg/kg/d), 238.84±15.81 (pomegranate peel extract of 480mg/kg/d), 227.47±12.15 (aspirin), and 224.01±18.39 (ellagic acid). Statistical differences were found in one-way analysis of variance (ANOVA) and post hoc analysis among the DSS group, normal group, and dose 2 group (pomegranate peel extract of 480mg/kg/day). Conclusions. The ethanol extract of pomegranate was able to induce apoptosis, which was demonstrated by the increase of caspase-3 expression.

Background: Invasive breast carcinoma of no special type (IBC-NST) is the most common type of breast cancer and mainly causes regional lymph-node metastasis (LNM). We investigated the potential for AKT2 expression as a predictive biomarker for LNM in IBC-NST.Methods: Forty-eight paraffin blocks containing IBC-NST primary tumors were divided into two groups based on presence or absence of LNM. Age, tumor grade, tumor size, lymphovascular invasion (LVI), and AKT expression were assessed. AKT2 expression was assessed based on immunohistochemical staining, while other data were collected from archives. Results: Multiple logistic regression results showed that AKT2 expression and LVI were significantly associated with LNM (odds ratio [OR], 5.32; 95% confidence interval [CI], 1.42 to 19.93 and OR, 4.46; 95% CI, 1.17 to 16.97, respectively). AKT2 expression was able to discriminate against LNM (area under the receiver operating characteristic, 0.799 ± 0.063; 95% CI, 0.676 to 0.921) at an H-score cutoff of 104.62 (83.3% sensitivity, 62.5% specificity). Conclusions: AKT2 expression has potential as a predictor of LNM in IBC-NST. The H-score cutoff for AKT2 expression can be used as a classification guide in future studies.

The increase in progesterone (P4) levels on the day of human chorionic gonadotropin (hCG) administration have a negative effect on endometrial receptivity. There are few reports regarding the expression of homeobox A10 (HOXA10) as one of many biomolecular factors of endometrial receptivity. To evaluate the effect of increased P4 concentration on the day of hCG administration on HOXA10, a total of 16 Macaca nemestrina were divided into three dose groups of recombinant-follicle stimulating hormone (rFSH) (30IU, 50IU, and 70IU) and one control group. Injection of rFSH combined with gonadotropin release hormone (GnRH) at 160 ug/day was given subcutaneously using a long protocol technique. Blood samples for estradiol (E2) and (P4) concentration measurements were taken on the day of injecting hCG in the final follicular phase, while the collection of endometrial tissue for HOXA10 measurement was carried out 8 to 10 days after hCG administration. E2 and P4 were measured by ELISA, whereas HOXA10 expression was measured with immunohistochemical (IHC) techniques. The concentration of E2 and P4 was found to be higher in dose groups compared with the natural group, but no significant differences were found within the group. For the Hscore for HOXA10 expression, no significant differences within dose groups were found. In addition, no significant differences for the Hscore for HOXA10 were found when compared to E2 groups. Significantly, the Hscore of HOXA10 was found to be >1 ng/mL in the P4 group compared with the Hscore HOXA10 in the P4 natural group (p = 0.022). The high concentration of P4 caused by ovarian hyperstimulation in the follicular phase stimulates the expression of HOXA10 in the secretion phase.

Diabetes mellitus (DM) is a chronic metabolic disorder characterized by hyperglycemia, which affects multiple tissues including kidneys. Soursop leaves (Annona muricata) are known to have antidiabetic potential, but their molecular and cellular effects are poorly characterized. We identified the bioactive compounds in soursop leaf ethanol extract (SLEE). The SLEE substances demonstrated the total alkaloid and total flavonoid contents. Twelve bioactive compounds profiles were identified in SLEE classified as alkaloid, flavonol glycoside, and monoterpenoid lactone derivatives. The SLEE treatments in mice were performed by dividing Swiss Webster mice into five groups, including negative and positive controls and three experimental groups provided with SLEE (doses 150, 300, and 600 mg/kg BW) for 14 days. The mice in the experimental groups were treated with alloxan to induce diabetes. The renal samples were stained for H&E for morphological changes. However, 600 mg/kg of SLEE showed a significant effect (p < 0.05) on the height of the Bowman’s space and prevented the tubularization of the left kidney’s glomerulus (p < 0.05). Altogether, we report no significant difference in the glomerular diameter, the thickness of the proximal convoluted tubules, the height of the Bowman’s space, and the glomerular tubularization after 14 days of treatment with SLEE.