Human Factor Research Articles

Exploring the neutrophil-to-lymphocyte ratio as a prognostic biomarker in triple-negative breast cancer

Triple-negative breast cancer is a subtype characterized by the absence of estrogen receptor, progesterone Receptor, and Human Epidermal Growth Factor Receptor 2 receptors, limiting treatment options primarily to chemotherapy due to lack of targeted therapies typically used for other breast cancer types, hence necessitating research for improved therapeutic strategies and outcomes. The neutrophil and lymphocyte percentages, absolute counts, and the ratio of neutrophils to lymphocytes were evaluated in peripheral blood of 81 patients with triple-negative breast cancer (TNBC) and 25 healthy controls. This study observed trend of high neutrophil percentage was observed in patients with positive lymph node status as compared to negative lymph node status. Significant high absolute neutrophil count was observed in patients with positive LN status, High BR score and presence of metastasis. A trend of high neutrophil to lymphocyte ratio was observed in patients with presence of perineural invasion, presence of necrosis, and patients with presence of metastasis.

Preoperative prediction of HER-2 expression status in breast cancer based on MRI radiomics model

Objective: This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer. Methods: A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness. Results: The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model (P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model (P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort (P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort (P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions: T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Environmental Constraints and Human Agency in Early Medieval Village Formation: A Geoarchaeological Approach in the Western Pyrenees (Navarre, Spain)

ABSTRACT The interaction between human agency and environmental factors is a key topic in the archaeological study of early medieval village formation. Such interactions are particularly visible in the construction and maintenance of agrarian landscapes, which often become central to the local socio-economic development. This article explores these processes in a local context of the western Pyrenees (Navarre, Spain) through a combined analysis of documentary sources, toponymy, field survey, and core sampling for geochemical analysis. The foundations of the local landscape were laid down in the Early Middle Ages, closely related to the establishment of a village settlement and the collective appropriation of agrarian resources. The local geological and soil features, marked by the presence of thick and soft, mineral nutrient-rich soils derived from the weathered volcanic rock substrate, permitted the construction and maintenance of a terraced field system. This fact has been key for later landscape evolution at the local and regional scales, including the formation of a supra-local valley community during the Late Middle Ages, or the deep agrarian and demographic transformations that followed the introduction of New World crops during the Early Modern period.

Tuberculosis in wild animals in India.

India is renowned for its complex megadiverse ecosystems and abundant biodiversity. Bovine tuberculosis (bTB) often remains synonymous with Mycobacterium bovis infection in cattle. The domain of tuberculosis (TB) among wild animals, induced by members of the Mycobacterium tuberculosis complex organisms (MTBC), is often underexplored and underreported in India. Within this context, instances of wild animal tuberculosis (wTB) have manifested across both captive and free-roaming animals. The sources contributing to wTB in animals can be human, animal, or environmental factors, thus illuminating the complex transmission pathways. The diagnosis of wTB continues to pose a formidable challenge, a consequence of the expansive taxonomic diversity in both the host and the pathogen. Complications inherent in acquiring samples from wildlife, the absence of standardized diagnostic protocols, limited insights into infection prevalence, and resource constraints compound diagnosis. Amidst these, adopting the comprehensive One Health paradigm surfaces as an imperative, accentuating the interconnectedness bridging human, animal, and environmental health. Recognizing key stakeholders and fostering intersectoral collaboration to provide enhanced diagnostic techniques driven by skilled personnel and advanced infrastructure play pivotal roles in a comprehensive strategy. Additionally, leveraging vaccination efforts contributes to effective control. A national wTB surveillance program is a cornerstone, ensuring an integrated and holistic approach to disease management. Through this review, we delve into the current landscape of wTB in India, unveiling its multifaceted challenges, and further explore the multifarious strategies that the One Health approach proffers in this dynamic endeavor.

A vulnerability evaluation method of earthen sites based on entropy weight-TOPSIS and K-means clustering

The degradation of earthen sites due to natural and human factors has become a pressing issue, necessitating urgent protection measures. In this context, accurate assessment of the vulnerability of earthen sites is essential for the development of effective conservation strategies. In this study, a comprehensive evaluation framework that incorporates multiple indicators is proposed. In particular, the entropy weight- (Technique for Order Preference by Similarity to an Ideal Solution) TOPSIS method is employed for quantitative vulnerability assessment and combined with K-means clustering to define vulnerability levels for earthen sites. To validate the proposed approach, the vulnerability of 29 sections of the Ming Great Wall is evaluated. Eventually, the 29 earthen sites are categorized into three levels: high, medium, and low, according to their degree of vulnerability. The results of gray correlation analysis and entropy weight-TOPSIS method are compared using the ontology missing amount in the original data as the validation standard. The results show that the Pearson correlation coefficient value of the entropy weight-TOPSIS method with the ontology missing amount was 0.859, while the Pearson correlation coefficient value of the gray correlation analysis method with the ontology missing amount was 0.691, so that the results of the entropy weight-TOPSIS method can more accurately reflect the actual vulnerability of earthen sites.

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

AbstractUnderstanding the evolutionary patterns of ecological quality in transport corridor areas and their driving mechanisms is essential for maintaining regional sustainable development. However, an integrated assessment of the ecology of plateau transport corridors is still lacking. This study focuses on the Sino‐Nepalese Transport Corridor (SNTC) and comprehensively evaluates the spatio‐temporal patterns and evolution of eco‐environmental quality from 2000 to 2021 based on remote sensing data and quantifies and explores the potential driving factors. The results indicate significant spatial heterogeneity in the eco‐environmental quality of the SNTC, with an overall bipolar “northeast‐southwest” distribution pattern. The area of poor and worse quality is the largest (32,471.75 km2), accounting for about 47.20% of the total area of the SNTC, distributed in the plateau bare land and the Yarlung Tsangpo River valley. From 2000 to 2021, the eco‐environmental quality showed an initial decline and then an increase, with a relatively gentle overall trend. The increase in the remote sensing ecological index in Region (I) from 0.314 in the first 10 years to 0.334 in the second 10 years, an increase of 6.37%, was mainly attributed to afforestation projects in the “One River and two tributaries Nature Reserve” region. The eco‐environmental quality of the SNTC is influenced by multiple factors including human activities, climate, and topography. Grazing intensity, population density, and digital elevation model are the main negative disturbance factors, while temperature, precipitation, gross domestic product, and afforestation areas promote eco‐environmental quality. In particular, afforestation projects partially offset the negative impact of human activities. These results will provide useful information for understanding the complex effects of human activities and natural factors on the eco‐environmental quality in the plateau transport corridor region and for formulating ecological conservation policies.

Plant-Derived Anti-Human Epidermal Growth Factor Receptor 2 Antibody Suppresses Trastuzumab-Resistant Breast Cancer with Enhanced Nanoscale Binding.

Traditional monoclonal antibodies such as Trastuzumab encounter limitations when treating Human Epidermal Growth Factor Receptor 2 (HER2)-positive breast cancer, particularly in cases that develop resistance. This study introduces plant-derived anti-HER2 variable fragments of camelid heavy chain domain (VHH) fragment crystallizable region (Fc) KEDL(K) antibody as a potent alternative for overcoming these limitations. A variety of biophysical techniques, in vitro assays, and in vivo experiments uncover the antibody's nanoscale binding dynamics with transmembrane HER2 on living cells. Single-molecule force spectroscopy reveals the rapid formation of two robust bonds, exhibiting approximately 50 pN force resistance and bond lifetimes in the second range. The antibody demonstrates a specific affinity for HER2-positive breast cancer cells, including those that are Trastuzumab-resistant. Moreover, in immune-deficient mice, the plant-derived anti-HER2 VHH-FcK antibody exhibits superior antitumor activity, especially against tumors that are resistant to Trastuzumab. These findings underscore the plant-derived antibody's potential as an impactful immunotherapeutic strategy for treating Trastuzumab-resistant HER2-positive breast cancer.

Potential drug targets for tumors identified through Mendelian randomization analysis.

According to the latest cancer research data, there are a significant number of new cancer cases and a substantial mortality rate each year. Although a substantial number of clinical patients are treated with existing cancer drugs each year, the efficacy is unsatisfactory. The incidence is still high and the effectiveness of most cancer drugs remains unsatisfactory. Therefore, we evaluated the human proteins for their causal relationship to for cancer risk and therefore also their potential as drug targets. We used summary tumors data from the FinnGen and cis protein quantitative trait loci (cis-pQTL) data from a genome-wide association study, and employed Mendelian randomization (MR) to explore the association between potential drug targets and nine tumors, including breast, colorectal, lung, liver, bladder, prostate, kidney, head and neck, pancreatic caners. Furthermore, we conducted MR analysis on external cohort. Moreover, Bidirectional MR, Steiger filtering, and colocalization were employed to validate the main results. The DrugBank database was used to discover potential drugs of tumors. Under the threshold of False discovery rate (FDR) < 0.05, results showed that S100A16 was protective protein and S100A14 was risk protein for human epidermal growth factor receptor 2-positive (HER-positive) breast cancer, phosphodiesterase 5A (PDE5A) was risk protein for colorectal cancer, and melanoma inhibitory activity (MIA) was protective protein for non-small cell lung carcinoma (NSCLC). And there was no reverse causal association between them. Colocalization analysis showed that S100A14 (PP.H4.abf = 0.920) and S100A16 (PP.H4.abf = 0.932) shared causal variation with HER-positive breast cancer, and PDE5A (PP.H4.abf = 0.857) shared causal variation with colorectal cancer (CRC). The MR results of all pQTL of PDE5A and MIA were consistent with main results. In addition, the MR results of MIA and external outcome cohort were consistent with main results. In this study, genetic predictions indicate that circulating S100 calcium binding protein A14 (S100A14) and S100 calcium binding protein A16 (S100A16) are associated with increase and decrease in the risk of HER-positive breast cancer, respectively. Circulating PDE5A is associated with increased risk of CRC, while circulating MIA is associated with decreased risk of NSCLC. These findings suggest that four proteins may serve as biomarkers for cancer prevention and as potential drug targets that could be expected for approval.

Performance of The Trigona,Sapiens Honey Agribusiness Developed By Communities Around The Laiwoi KPH Forest Area In Amonggedo District, Konawe Regency, Southeast Sulawesi Province

The Trigona sp bee is a type of biodiversity that has high economic value and is a leading commodity for Non-Timber Forest Products (HhBk), which is developed by the community around the KPH Laiwoi forest area, Amonggedo District, Konawe Regency. The community and government of Amonggedo Baru sub-district, Mataiwoi Village, Puasana Village, and Amonggedo District have formed farmer groups and Gapoktan to cultivate Trigona sp bees. as a sector of economic improvement for society. This community partnership activity was conducted in Mataiwoi Village and Amonggedo Baru Village, Amonggedo District, Konawe Regency. The method used in this survey research is the Agribusiness Technology Transfer Approach. Data was collected through observation and interview methods. Based on the community profile above, the problem of research on the performance of the Trigona Honey Agribusiness developed by the community around the KPH Laiwoi Forest area, Amonggedo District, Konawe Regency is presented in detail as follows: 1. The performance of the Trigona, sp Honey Agribusiness is determined by human factors, capital, processing tools and machines, honey management methods and technology, markets, and non-economic environmental factors carried out using a Technology Transfer approach to the Trigona—Sp Honey Bee Agribusiness subsystem. The community around the KPH Laiwoi Forest Area, Amonggedo District, Konawe Regency developed them. 2. Trigona, sp honey bee production management developed by the community is moving the colony from the primary habitat on a dead tree to an artificial habitat in artificial STUP boxes with a start-up of 20 boxes per group

Transcription factors ERα and Sox2 have differing multiphasic DNA and RNA binding mechanisms.

Many transcription factors (TFs) have been shown to bind RNA, leading to open questions regarding the mechanism(s) of this RNA binding and its role in regulating TF activities. Here we use biophysical assays to interrogate the kon, koff, and Kd for DNA and RNA binding of two model human transcription factors, ERα and Sox2. Unexpectedly, we found that both proteins exhibited multiphasic nucleic acid binding kinetics. We propose that Sox2 RNA and DNA multiphasic binding kinetics could be explained by a conventional model for sequential Sox2 monomer association and dissociation. In contrast, ERα nucleic acid binding exhibited biphasic dissociation paired with novel triphasic association behavior, where two apparent binding transitions are separated by a 10-20 min "lag" phase depending on protein concentration. We considered several conventional models for the observed kinetic behavior, none of which adequately explained all the ERα nucleic acid binding data. Instead, simulations with a model incorporating sequential ERα monomer association, ERα nucleic acid complex isomerization, and product "feedback" on isomerization rate recapitulated the general kinetic trends for both ERα DNA and RNA binding. Collectively, our findings reveal that Sox2 and ERα bind RNA and DNA with previously unappreciated multiphasic binding kinetics, and that their reaction mechanisms differ with ERα binding nucleic acids via a novel reaction mechanism.

Impact of immunohistochemistry staining conditions on the incidence of human epidermal growth factor receptor 2 (HER2)-low breast cancer.

We investigated frequencies of HER2-low breast cancer (BC) (immunohistochemistry [IHC] 1+ or 2+ without gene amplification) before and after IHC conditions were modified in order to understand the impact of IHC staining conditions on frequencies of HER2-low BC. Primary BC cases diagnosed at the Yeungnam University Hospital (YUH, n = 728) or Keimyung University Dongsan Hospital (KUDH, n = 290) in 2022 were reviewed, and data on HER2 status and IHC conditions were collected (cohort 1). Both institutions used the 4B5 antibody for HER2 IHC but had different staining protocols. After modifications of the IHC conditions at both institutions, primary BC cases (YUH, n = 324 and KUDH, n = 135) diagnosed from April to July 2023 (cohort 2) were reviewed to assess any changes in the frequency of HER2 status. In cohort 1, of the 728 cases diagnosed at YUH, 556 (76.4%) were HER2-zero, 76 (10.4%) were HER2-low, and 96 (13.2%) were HER2-positive, and of the 290 cases diagnosed at KUDH, 135 (46.6%) were HER2-zero, 82 (28.3%) were HER2-low, and 73 (25.2%) were HER2-positive. Modifications in HER2 IHC staining conditions dramatically increased the frequencies of HER2-low BC in cohort 2 (YUH 38.9% and KUDH 49.6%), but they did not result in significant changes in the HER2-positive rates (YUH 15.4% and KUDH 25.2%) compared to cohort 1. In conclusion, minor modifications in HER2 IHC staining conditions significantly affected the frequency of HER2-low BC but had little impact on the HER2-positivity rate. Each pathology laboratory should verify IHC conditions using control slides (including 1+) to enable the accurate identification of HER2-low BC.

A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.

To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal growth factor receptor 2 (HER2) and to identify luminal histotype of the breast cancer. From four Italian centers were recruited 180 malignant lesions and 68 benign lesions. However, only the malignant lesions were considered for the analysis. All patients underwent contrast-enhanced mammography in cranium caudal (CC) and medium lateral oblique (MLO) view. Considering histological findings as the ground truth, four outcomes were considered: (1) G1 + G2 vs. G3; (2) HER2 + vs. HER2 - ; (3) HR + vs. HR - ; and (4) non-luminal vs. luminal A or HR + /HER2- and luminal B or HR + /HER2 + . For multivariate analysis feature selection, balancing techniques and patter recognition approaches were considered. The univariate findings showed that the diagnostic performance is low for each outcome, while the results of the multivariate analysis showed that better performances can be obtained. In the HER2 + detection, the best performance (73% of accuracy and AUC = 0.77) was obtained using a linear regression model (LRM) with 12 features extracted by MLO view. In the HR + detection, the best performance (77% of accuracy and AUC = 0.80) was obtained using a LRM with 14 features extracted by MLO view. In grading classification, the best performance was obtained by a decision tree trained with three predictors extracted by MLO view reaching an accuracy of 82% on validation set. In the luminal versus non-luminal histotype classification, the best performance was obtained by a bagged tree trained with 15 predictors extracted by CC view reaching an accuracy of 94% on validation set. The results suggest that radiomics analysis can be effectively applied to design a tool to support physician decision making in breast cancer classification. In particular, the classification of luminal versus non-luminal histotypes can be performed with high accuracy.

Abstract A007: Circulating tumor DNA and tissue staining analyses reveal heterogeneous ERBB2/HER2 status in urothelial cancer

Abstract Human epidermal growth factor receptor 2 (HER2) is encoded by the ERBB2 gene, and frequently mutated, amplified, and/or overexpressed in urothelial cancer (UC). Promising antibody-drug conjugates have led to new interest in HER2 as a UC clinical target. Patient selection for HER2-targeted therapy typically relies on immunohistochemistry (IHC) and fluorescence in-situ hybridization (FISH) of tumor tissue, however DNA sequencing can identify ERBB2 genomic alterations. Accurate biomarker-driven patient selection will be critical to optimize the clinical benefit of HER2-targeted therapy. Therefore, we evaluated plasma circulating tumor DNA (ctDNA) for ERBB2/HER2 status determination in UC, as compared to IHC and FISH of metachronous tissue. 411 plasma samples from 236 metastatic UC patients were profiled with targeted sequencing across &amp;gt;50 genes frequently altered in UC, including dense coverage flanking the ERBB2 locus. Using an established bioinformatics workflow, we determined the presence of ERBB2 alterations (mutations, amplifications, and/or structural variants) in the 181 patients with evidence of ctDNA in ≥1 sample. Clinical records were reviewed for the availability of archival tumor tissue; in total, 81 formalin-fixed paraffin-embedded tissue specimens were retrieved from 23 patients with ctDNA ERBB2 alterations and 20 ERBB2-wildtype controls. HER2 IHC was performed with a polyclonal rabbit anti-human Her2 antibody (Dako) and scored according to gastric cancer guidelines. HER2 FISH was performed with the PathVysion HER-2 DNA Probe Kit. Protein-altering ERBB2 mutations were identified in 14% of evaluable patients, with two-thirds at known oncogenic hotspots. ERBB2 copy gain was detected in 8% of patients overall, 9% when excluding low tumor fraction samples. IHC results were assessable for 82 tissue samples from 43 patients, and 33 patients had at least one sample with positive HER2 staining (2+/3+). IHC scores varied in 16/23 patients with ≥2 tissue samples, with the variation leading to a change in classification (HER2-negative [0/1+] versus positive [2+/3+]) in half (8/16). In two patients with mixed variant histology, the urothelial component showed IHC 3+ while the scores were 2+ (plasmacytoid) and 0 (squamous) in the variant regions. Frequent focal staining patterns were observed with both IHC and FISH. ERBB2 alterations in ctDNA were correlated with IHC positivity – when considering the most recent tissue sample per patient, 79% of ctDNA ERBB2-altered patient’s tumors were also positive by IHC. Conversely, 55% of ctDNA ERBB2-wildtype cases were positive by IHC. FISH results were available from 24 samples (20 positive, 4 negative), all from patients with ctDNA ERBB2 amplification. 18/20 samples with FISH positivity were HER2 IHC 2+/3+; the remaining two samples were IHC 1+. Our results demonstrate significant spatial and/or temporal heterogeneity in ERBB2/HER2 status, with implications for the rational implementation of biomarker-directed (HER2-targeted) therapy in UC. Citation Format: Gillian Vandekerkhove, Andrew J. Murtha, David C. Müller, Kimia Rostin, Carlos Vasquez-Rios, Jussi Nikkola, Maria Stephenson, Emily Fung, Jaskirat Atwal, Karan Parekh, Cecily Q. Bernales, Gráinne Donnellan, Gang Wang, Tilman Todenhöfer, Piet Ost, Peter C. Black, Kim N. Chi, Bernhard J. Eigl, Alexander W. Wyatt. Circulating tumor DNA and tissue staining analyses reveal heterogeneous ERBB2/HER2 status in urothelial cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr A007.

Clinical characteristics, treatment patterns, and outcomes in adult patients with germline BRCA1/2-mutated, HER2-negative advanced breast cancer: a retrospective medical record review in the United States

AimTo examine clinical characteristics, real-world treatment patterns, and health outcomes among patients with germline BRCA1/2-mutated, human epidermal growth factor receptor 2 (HER2)–negative advanced breast cancer (ABC).MethodsA retrospective analysis was conducted using medical records from patients with HER2-negative ABC with BRCA1/2 mutation who received cytotoxic chemotherapy. Data were stratified into groups with triple-negative breast cancer (TNBC) or hormone receptor–positive (HR+)/HER2-negative diagnoses. Time-to-event outcomes (i.e., real-world progression-free survival [rwPFS] and overall survival [OS]) were calculated to summarize health outcomes.ResultsWhen diagnosed with ABC, most patients were younger than 60 years (mean age = 57.3 years), were white (76.4%), and had a family history of BRCA-related cancer (71.5%). A total of 305 patient records were examined; 194 patients (63.6%) had advanced TNBC, and 111 patients (36.4%) had HR+/HER2-negative ABC. Chemotherapy was primarily used as first-line treatment for both subgroups, but the TNBC subgroup received poly (ADP-ribose) polymerase (PARP) inhibitors at triple the rate as a second-line treatment and double the rate as a third-line treatment compared with the HR+/HER2-negative subgroup. Two-year OS rates were similar between the TNBC (73.9%) and the HR+/HER2-negative subgroups (77.0%), and anemia, nausea, and neutropenia were the most commonly reported toxicities across all treatments.ConclusionClinicians should consider the use of targeted agents such as PARP inhibitors in earlier lines of therapy for ABC given the growing evidence that PARP inhibitors may improve PFS compared with chemotherapy while potentially offering a more manageable toxicity profile and improved quality of life.

A screen for Plasmodium falciparum sporozoite surface protein binding to human hepatocyte surface receptors identifies novel host–pathogen interactions

BackgroundSporozoite invasion of hepatocytes is an essential step in the Plasmodium life-cycle and has similarities, at the cellular level, to merozoite invasion of erythrocytes. In the case of the Plasmodium blood-stage, efforts to identify host–pathogen protein–protein interactions have yielded important insights including vaccine candidates. In the case of sporozoite-hepatocyte invasion, the host–pathogen protein–protein interactions involved are poorly understood.MethodsTo gain a better understanding of the protein–protein interaction between the sporozoite ligands and host receptors, a systematic screen was performed. The previous Plasmodium falciparum and human surface protein ectodomain libraries were substantially extended, resulting in the creation of new libraries comprising 88 P. falciparum sporozoite protein coding sequences and 182 sequences encoding human hepatocyte surface proteins. Having expressed recombinant proteins from these sequences, a plate-based assay was used, capable of detecting low affinity interactions between recombinant proteins, modified for enhanced throughput, to screen the proteins for interactions. The novel interactions identified in the screen were characterized biochemically, and their essential role in parasite invasion was further elucidated using antibodies and genetically manipulated Plasmodium parasites.ResultsA total of 7540 sporozoite-hepatocyte protein pairs were tested under conditions capable of detecting interactions of at least 1.2 µM KD. An interaction between the human fibroblast growth factor receptor 4 (FGFR4) and the P. falciparum protein Pf34 is identified and reported here, characterizing its affinity and demonstrating the blockade of the interaction by reagents, including a monoclonal antibody. Furthermore, further interactions between Pf34 and a second P. falciparum rhoptry neck protein, PfRON6, and between human low-density lipoprotein receptor (LDLR) and the P. falciparum protein PIESP15 are identified.Conditional genetic deletion confirmed the essentiality of PfRON6 in the blood-stage, consistent with the important role of this protein in parasite lifecycle. Pf34 was refractory to attempted genetic modification. Antibodies to Pf34 abrogated the interaction and had a modest effect upon sporozoite invasion into primary human hepatocytes.ConclusionPf34 and PfRON6 may be members of a functionally important invasion complex which could be a target for future interventions. The modified interaction screening assay, protein expression libraries and P. falciparum mutant parasites reported here may be a useful tool for protein interaction discovery and antigen candidate screening which could be of wider value to the scientific community.

Characterization of HER2-low breast cancer in young women with germline BRCA1/2 pathogenetic variants: Results of a large international retrospective cohort study.

Breast cancer (BC) in women aged ≤40 years carrying germline pathogenetic variants (PVs) in BRCA1/2 genes is infrequent but often associated with aggressive features. Human epidermal growth factor receptor 2 (HER2)-low-expressing BC has recently emerged as a novel therapeutic target but has not been characterized in this rare patient subset. Women aged ≤40 years with newly diagnosed early-stage HER2-negative BC (HER2-0 and HER2-low) and germline BRCA1/2 PVs from 78 health care centers worldwide were retrospectively included. Chi-square test and Student t-test were used to describe variable distribution between HER2-0 and HER2-low. Associations with HER2-low status were assessed with logistic regression. Kaplan-Meier method and Cox regression analysis were used to assess disease-free survival (DFS) and overall survival. Statistical significance was considered for p≤.05. Of 3547 included patients, 32.3% had HER2-low BC, representing 46.3% of hormone receptor-positive and 21.3% of triple-negative (TN) tumors. HER2-low vs. HER2-0 BC were more often of grade 1/2 (p<.001), hormone receptor-positive (p<.001), and node-positive (p=.003). BRCA2 PVs were more often associated with HER2-low than BRCA1 PVs (p<.001). HER2-low versus HER2-0 showed better DFS (hazard ratio [HR], 0.86; 95% CI, 0.76-0.97) in the overall population and more favorable DFS (HR, 0.78; 95% CI, 0.64-0.95) and overall survival (HR, 0.65; 95% CI, 0.46-0.93) in the TN subgroup. Luminal A-like tumors in HER2-low (p=.014) and TN and luminal A-like in HER2-0 (p=.019) showed the worst DFS. In young patients with HER2-negative BC and germline BRCA1/2 PVs, HER2-low disease was less frequent than expected and more frequently linked to BRCA2 PVs and associated with luminal-like disease. HER2-low status was associated with a modestly improved prognosis.

Pipe Crawler Robot

This pipe inspection robot aims at detecting the exact location of leakage and clearing the blockages, thus removing human factors from labor-intensive and dangerous work, thereby reducing the number of accidents that happen due to the lack of regular inspection. Detection Pipe leakage, water distribution system. An autonomous pipe crawler robot is designed to navigate through pipelines, offering a practical and efficient solution for inspecting and monitoring the condition of pipe interiors. This robot leverages advanced locomotion mechanisms and control strategies to maneuver through various pipe diameters and configurations, including straight sections, bends, and junctions. Equipped with sensors and cameras, it can detect anomalies such as cracks, corrosion, blockages, and leaks, providing real-time, high-resolution imagery and data. This technology significantly reduces the need for manual inspections, minimizes human exposure to hazardous environments, and improves the precision and efficiency of pipeline maintenance operations. The development of pipe crawler robots represents a significant advancement in the field of robotics and infrastructure management, promising enhanced safety, reliability, and cost-effectiveness for industries reliant on extensive pipeline networks. Key words: inspection, autonomous, locomotion, robot, crawler., etc.

Designing and Planning of Studies of Driver Behavior at Pedestrian Crossings Using Whole-Vehicle Simulators

The paper presents a proposed methodology for designing and planning research on driver behavior at pedestrian crossings using whole-vehicle simulators. It was assumed that dedicated research should be conducted in specific problem contexts. The problems identified were the identification of hazards and the risk of accidents involving vulnerable road users. The purpose of this identification is to determine the determinants of safety at pedestrian crossings, which should constitute guidance when designing new solutions for safety support systems at pedestrian crossings. A number of hazard factors were identified; divided into categories, including types of crossings, location, and surroundings; behavior of vulnerable road users; and attention (focus) distractors, both inside and outside the vehicle. A method for defining and selecting research scenarios and selecting a group of research participants was proposed. Additionally, it was proposed to conduct repeatable test scenarios for different driving speeds and different weather conditions. With respect to the publications on this topic, this work focuses on the process of designing and planning dedicated simulation studies, which may provide a source of guidance and good practices for other researchers. This is an example of how interdisciplinary research involving human factors, traffic organization, and ITS systems can be planned and implemented.

Predicting Drug Resistance in Gastric Cancer with Mutation in the Human Epidermal Growth Factor Receptor 2 (HER2) And Machine Learning Technique

Gastric cancer with mutations in the human epidermal growth factor receptor (HER2) can be regarded as one of the leading causes of cancer mortality in the world. Targeted tyrosine kinase inhibitors (TKIs) developed against HER2 yielded optimistic results in improving patients' survival rates and life quality. Nevertheless, drug resistance can influence the critical supportive documents of treatment plans and decrease the treatment effectiveness after about one year. Predicting the efficacy of HER2-TKI drugs or therapies for patients with HER2-mutated gastric cancer is a critical research field. In the present study, a personalized drug response prediction model based on molecular dynamics simulations and machine learning is presented to predict response to first-generation drugs approved by the Ministry of Health in patients with gastric cancer. In the molecular dynamics simulation, the patient's mutation status is considered. The patient's unique mutation status was modeled using molecular dynamics simulations to extract geometric features at the molecular level.Furthermore, additional clinical features are incorporated into the machine learning model to predict drug response. The complete features encompass demographic and clinical characteristics, geometrical properties of the drug-target binding site, and binding free energy (RBFE) of the drug-target complex from molecular dynamics simulations. Drug response prediction utilizes the XGBoost classifier, which achieved leading-edge performance for a 4-level drug response prediction task (PDRP) with 97.5% accuracy, 93% sensitivity, 96.5% specificity, and 94% F1 score. The present research has demonstrated that modeling the binding cavity geometry, in tandem with the binding free energy, can effectively predict drug response. Interestingly, the clinical information, while significant, did not significantly influence the model's performance. This exciting finding opens up new avenues for testing the proposed model on various types of cancers, potentially revolutionizing drug development strategies. DOI: https://doi.org/10.52783/pst.391

Retrospective analysis of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67 changes and their clinical significance between primary breast cancer and metastatic tumors.

To explore the relationship between receptor heterogeneity and clinicopathological characteristics in 166 patients with invasive breast cancer during metastasis. We conducted a retrospective analysis of 166 patients diagnosed with metastatic breast cancer through biopsy, who were admitted to our hospital from January 2018 to December 2022. Statistical analysis was employed to assess the heterogeneity of receptors in both primary and metastatic lesions, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER2), Ki67, as well as their association with clinicopathological features such as tumor size, lymph node metastasis, treatment regimen, and disease-free survival. The discordant expression rates of ER, PR, HER2, Ki-67 and Luminal classification between primary and metastatic lesions were 21.7%, 41.6%, 8.9%, 34.4% and 36.8%, respectively. There is a significant difference in disease-free survival between patients with consistent and inconsistent receptor status of primary and metastatic lesions, which is statistically significant. The median DFS for primary HER2(-) to metastatic HER2(+) was 84 months, which was relatively high. The Cox multivariate regression analysis revealed that the expression differences of ER, PR, HER2, and Ki67 were not influenced by endocrine therapy and chemotherapy. However, a statistically significant difference in HER2 expression was observed with targeted therapy. Tumor size was correlated with ER and Ki67 receptor status (P=0.019, 0.016). Tumor size was not correlated with PR, and HER2 (P=0.679, 0.440). Lymph node metastasis was not associated with changes in ER, PR, HER2, and Ki67. The discordant rates of ER, PR, HER2, and Ki-67 in patients with local recurrence were 22%, 23.7%, 5.1%, and 28.8% respectively, whereas those in patients with distant metastasis were 21.5%, 36.4%, 10.3%, and 31.8% respectively. The expression levels of ER, PR, HER2, and Ki-67 in primary and metastatic breast cancer exhibit heterogeneity, which is closely associated with the prognosis and treatment outcomes of patients.