Human Factor Research Articles

Leadership and organizational change in high-risk industries: A model for managing engineering change in oil and gas operations

Leadership and organizational change are critical factors in high-risk industries like oil and gas operations, where safety, efficiency, and sustainability are paramount. This paper presents a comprehensive model for managing engineering change in oil and gas operations, emphasizing leadership strategies, organizational dynamics, and risk management. High-risk industries face unique challenges, including complex project environments, stringent regulatory compliance, and the need to adapt rapidly to technological advancements. Effective leadership plays a vital role in navigating these challenges by fostering a culture of innovation, collaboration, and continuous improvement. The proposed model integrates transformational leadership principles, change management theories, and engineering methodologies to address the multi-dimensional aspects of engineering change. It highlights the importance of clear communication, stakeholder engagement, and team empowerment in driving successful change initiatives. Additionally, it emphasizes the integration of advanced data analytics and decision-making tools to mitigate risks and enhance operational performance. The study draws on empirical research, case studies, and industry best practices to provide actionable insights for leaders and organizations in high-risk industries. Key findings indicate that leaders who exhibit adaptability, resilience, and technical competence can better manage the complexities of engineering change. Moreover, organizations that adopt a proactive approach to change management, incorporating predictive analytics and risk assessment frameworks, are more likely to achieve sustainable outcomes. This model also considers the human factor, addressing resistance to change and the need for continuous training and development to build a skilled workforce. By aligning leadership practices with organizational objectives and engineering requirements, the proposed framework offers a roadmap for managing change in a structured and efficient manner. The paper concludes with recommendations for implementing the model, including fostering a culture of safety and innovation, leveraging technology for decision support, and enhancing cross-functional collaboration. This work contributes to the growing body of knowledge on leadership and organizational change in high-risk industries and provides a practical guide for managing engineering change in oil and gas operations. Keywords: Leadership, Organizational Change, Engineering Change, High-Risk Industries, Oil and Gas Operations, Change Management, Risk Mitigation, Transformational Leadership, Data Analytics, Safety Culture.

Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.

For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed tofurther improve the accuracy and efficiency of HER2 amplification status detection with a deep learning model, and apply the model to predict the efficacy of neoadjuvant therapy. We combined Next-Generation Sequencing (NGS) data and IHC staining images of 606 breast cancer patients and developed a Vision Transformer (ViT) deep learning model to identify the amplification of HER2 through these IHC staining images. This model was then applied to predict the efficacy of neoadjuvant therapy in 399 HER2-positive breast cancer patients. The NGS data of 606 patients were split into training (N = 404), validation (N = 101), and testing (N = 101) sets. The top 3 genes with highest mutation frequency were TP53, ERBB2 and PIK3CA. With the NGS results as deep learning model labels, the accuracy of our ViT model was 93.1% for HER2 amplification recognition. The misidentifications was likely due to the heterogeneity of HER2 expression in cancer tissues. For predicting the efficacy of neoadjuvant therapy, receiver operating characteristic (ROC) curves were plotted, and the combination of image recognition result and clinical pathological features yielded an area under the curve (AUC) value of 0.855 in the training set and 0.841 in the testing set. Our study provided a method of HER2 status recognition based on IHC images, improving the efficiency and accuracy of HER2 status assessment, and can be used for predicting the efficacy of anti-HER2 targeted neoadjuvant therapy. We intend our deep learning model to assist pathologists in HER2 amplification recognition.

Enhanced preoperative prediction of breast lesion pathology, prognostic biomarkers, and molecular subtypes using multiple models diffusion-weighted MR imaging

This study aims to comprehensively evaluate the clinical utility of five diffusion models, including conventional mono-exponential (Mono), intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), stretched exponential (SEM), and continuous-time random-walk (CTRW), for preoperatively predicting of breast lesion pathology, prognostic biomarkers, and molecular subtypes. We retrospectively analyzed 132 patients with pathologically verified breast lesions (41 benign and 91 malignant) who underwent a full protocol preoperative breast MRI protocol, including a diffusion-weighted imaging (DWI) sequence with nine b values (0 to 2000 s/mm2) on a 3.0T MR scanner. The diffusion parameters from each model—Mono (ADC), IVIM (D, D*, f), DKI (MD, MK), SEM (DDC, α) and CTRW (Dm, α, β)—were quantitatively calculated and compared between benign and malignant breast lesions, as well as across different prognostic biomarker statuses in breast cancer, using Mann–Whitney U-tests. For molecular subtypes comparisons, we employed the Kruskal-Wallis test followed by Bonferroni. All parameters, except IVIM-D*, significantly differentiated benign from malignant lesions. Notably, IVIM-D and DKI-MK values were significantly different between estrogen receptor (ER)-positive and ER-negative tumors. Progesterone receptor (PR)-positive cancers exhibited lower Mono-ADC, IVIM-D, DKI-MD, SEM-DDC, CTRW-Dm, and CTRW-α values, alongside higher DKI-MK value compared to PR-negative cancers (p < 0.05). Significant differences in IVIM-D, IVIM-D*, and DKI-MK values were observed between human epidermal growth factor receptor 2 (HER2)-negative and HER2-positive tumors. Furthermore, higher SEM-α and CTRW-β values, along with lower DKI-MD and SEM-DDC values, were noted in the high Ki-67 expression group compared to the low Ki-67 group (p < 0.05). All five diffusion models proved valuable for breast cancer diagnosis, with the CTRW model exhibiting the highest diagnostic performance, although the difference was not statistically significant. The diffusion parameters derived from these models can effectively assist in distinguishing prognostic factors and molecular subtypes of breast cancer.

Targeted therapy and immunotherapy for gastric cancer: rational strategies, novel advancements, challenges, and future perspectives

Gastric cancer (GC) is one of the most common malignant tumors worldwide, and its treatment has been a focus of medical research. Herein we systematically review the current status of and advancements in targeted therapy and immunotherapy for GC, which have emerged as important treatment strategies in recent years with great potential, and summarize the efficacy and safety of such treatments. Targeted therapies against key targets in GC, including epidermal growth factor receptor (EGFR), human epidermal growth factor receptor 2 (HER2), and vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR), have shown remarkable therapeutic efficacies by inhibiting tumor progression and/or blood supply. In particular, markable breakthroughs have been made in HER2-targeting drugs for HER2-positive GC patients. To address intrinsic and acquired resistances to HER2-targeting drugs, novel therapeutic agents including bispecific antibodies and antibody–drug conjugates (ADC) targeting HER2 have been developed. Immunotherapy enhances the recognition and elimination of cancer cells by activating body anticancer immune system. Programmed cell death protein 1 (PD-1) and programmed cell death-ligand 1 (PD-L1) antibodies are the most commonly used immunotherapeutic agents and have been used with some success in GC treatment. Innovative immunotherapy modalities, including adoptive immune cell therapy, tumor vaccines, and non-specific immunomodulators therapy, and oncolytic viruses have shown promise in early-stage clinical trials for GC. Clinical trials have supported that targeted therapy and immunotherapy can significantly improve the survival and quality of life of GC patients. However, the effects of such therapies need to be further improved and more personalized, with advancement in researches on tumor immune microenvironment. Further studies remain needed to address the issues of drug resistance and adverse events pertaining to such therapies for GC. The combined application of such therapies and individualized treatment strategies should be further explored with novel drugs developed, to provide more effective treatments for GC patients.

Clinical characteristics, metastasis patterns, and treatment outcomes of HER2-low breast cancer

Breast cancer (BC) is a heterogeneous disease, traditionally classified by hormone receptor and HER2 (human epidermal growth factor receptor 2) status. HER2-low, characterized by low HER2 expression without gene amplification, recently gained attention. While new therapies are promising, its clinical significance remains unclear. We analysed 241,510 BC patients diagnosed between 2000 and 2020 in Germany using data from the German Cancer Registry Group. HER2 status was determined using immunohistochemistry and fluorescence in situ hybridization results, and patients were classified as HER2-positive, HER2-low or HER2-zero. Clinical features, chemosensitivity and long-term outcomes - metastasis-free survival (MFS), recurrence-free survival (RFS), and overall survival (OS) - were analysed using Cox models. HER2-low comprised 42% of female and 47% of male patients, predominantly hormone receptor positive. Metastatic patterns in HER2-low and HER2-zero were similar but differed from HER2-positive, which showed more liver metastasis and multiple metastatic sites. HER2-positive showed worse MFS, RFS, and OS than HER2-zero and HER2-low subtypes. Pathological complete response (pCR) rates after neoadjuvant chemotherapy were highest in HER2-positive. HER2-low has higher hormone receptor positivity, distinguishing it from HER2-zero. While metastatic behaviour, treatment and long-term response in HER2-low were comparable to HER2-zero, the hormone receptor status seems to play a critical role in these outcomes.

A rare case report of elderly Rubber Band Syndrome patient.

Rubber band syndrome is a relatively rare condition that occurs primarily in pediatric patients and is rarely seen in adults. Prolonged use of elastic bands may cause local contraction of the skin on the limbs, which gradually becomes lodged in the soft tissue, causing distal tissue edema, dysfunction and infection. In severe cases, damage to nerves, blood vessels and limbs can occur. Surgical exploration and resection are the main treatment methods. We present a case report of a 78-year-old patient with rubber band syndrome who recovered after surgery, innovative silver ion dressing combined with human epidermal growth factor gel dressing change and intravenous antibiotics.

Flight PK8303 crash: a disastrous failure of human factors

Research methodology The case study was developed based on secondary data from the publicly available initial accident report of PIA flight PK8303. The facts presented in the report were then analyzed in the light of the Human Factor Analysis and Classification System (HFACS). Case overview/synopsis The case revolves around the terrible aviation mishap that occurred on May 22, 2020, when Pakistan International Airlines (PIA) Flight 8303 crashed in a Karachi residential area. A total of 97 people lost their lives in this tragedy, and it was Pakistan’s 18th major aviation disaster. The case study explores the human errors and failures of ground handling agencies, air traffic controllers, regulatory agencies, airline employees and cockpit crew by using the HFACS. The focus remains on mistakes made by people, which revolve around inefficient and ineffective communication, and contempt of safety regulations at various stages of flight PK8303. Complexity academic level The case study is designed for the students of aviation management at undergraduate and graduate levels.

Geospatial modeling of geographical spread of Aedes species, in relation to climatic and topographical factors in Lagos State, Nigeria.

The ecology and biology of mosquito disease vectors of the genus Aedes are highly dynamic, adapting to various climatic and topographic factors which makes their control challenging. Evidence-based control of Aedes mosquitoes requires a detailed understanding of this adaptability, which is greatly influenced by environmental dynamics. Understanding the drivers of their distribution is hence pertinent to predict disease risk. To better understand drivers and dynamics, we studied the distribution of Aedes mosquitoes in Lagos State, Nigeria, and its connection to climatic and human factors. Aedes larvae and adults were collected from eight Local Government Areas (LGAs, four urban and four rural) in Lagos State, resulting in 98 occurrence points. Using 23 environmental variables, we modeled the geographic distribution of Aedes spp. under current climatic conditions. Human population density was overlaid to estimate the risk of arboviral diseases. Although Aedes mosquitoes were found in all the eight LGAs in different proportions, species distribution varied considerably. Both Aedes aegypti and Aedes albopictus were found across the LGAs with evidence of species partitioning. Virtually all the LGAs were predicted to be highly suitable environments for Aedes mosquitoes, with only two LGAs being moderately suitable. Anthropogenic factors including the extensive accumulation of tires contribute to larval habitat availability for both Aedes aegypti and Aedes albopictus. Urban areas with high population density were also associated with increased larval habitat availability when compared with rural areas. Furthermore, the model suggests that LGAs sharing border with Ogun State are highly suitable environments for Aedes spp. Our study highlights that the main contributing factors to Aedes distribution were precipitation and temperature in the coldest quarter. This paper aims to understand how human and climatic factors affect Aedes mosquitoes distribution in Lagos State, which is crucial to prevent disease transmission.

Time and depth variability of radon concentration and its relationship with other physicochemical parameters in an artificial lake subject to strong anthropogenic control.

Understanding the interaction between groundwater and surface water is crucial for an effective water management. This study investigates the vertical variability of radon gas (Rn-222) concentrations and other physicochemical parameters (pH, electrical conductivity, redox potential, and temperature) in an artificial lake (Aguieira Dam's reservoir) in the Mondego River, Portugal, that is intensively controlled by human factors. Over nine surveys conducted from May 2022 to September 2023, we observed significant vertical and temporal variations in these parameters, revealing complex patterns of water column stratification driven primarily by thermal dynamics and dam management practices. The study found that during periods of complete thermal stratification, Rn-222 concentrations were higher at mid-thermocline and at the riverbed, indicating traces of potential groundwater inputs, while at the epilimnion showed lower concentrations due to atmospheric exhalation. Conversely, during not complete stratification conditions, typically observed during higher water turbulence or lower water levels, the water column exhibited more homogeneous physicochemical profiles. Nevertheless, in some cases that could be related to increased precipitation prior to the sampling, it was observed also traces of groundwater input, highlighted by the radon tracer and confirmed by other physicochemical parameters. This study highlights the complex dynamics of water column stratification in artificial lakes whose inputs and outputs are heavily controlled by humans. The dam management itself is responsible for the complete inversion of the natural cycle of water level expected in a natural environment, thus these findings underscore the importance of considering both natural and anthropogenic factors in the management of water resources, particularly in dam-influenced systems, where vertical stratification and groundwater-surface water interactions can significantly impact water quality and the overall ecosystem health. This work contributes to a better understanding of the hydrological processes in dam-regulated river systems, providing insights for water resource management.

Lake chlorophyll responses to drought are related to lake type, connectivity, and ecological context across the conterminous United States

AbstractLocal and regional‐scaled studies point to the important role of lake type (natural lakes vs. reservoirs), surface water connectivity, and ecological context (multi‐scaled natural settings and human factors) in mediating lake responses to disturbances like drought. However, we lack an understanding at the macroscale that incorporates multiple scales (lake, watershed, region) and a variety of ecological contexts. Therefore, we used data from the LAGOS‐US research platform and applied a local water year timeframe to 62,927 US natural lakes and reservoirs across 17 ecoregions to examine how chlorophyll a responds to drought across various ecological contexts. We evaluated chlorophyll a changes relative to each lake's baseline and drought year. Drought led to lower and higher chlorophyll a in 18% and 20%, respectively, of lakes (both natural lakes and reservoirs included). Natural lakes had higher magnitudes of change and probabilities of increasing chlorophyll a during droughts than reservoirs, and these differences were particularly pronounced in isolated and highly‐connected lakes. Drought responses were also related to long‐term average lake chlorophyll a in complex ways, with a positive correlation in less productive lakes and a negative correlation in more productive lakes, and more pronounced drought responses in higher‐productivity lakes than lower‐productivity lakes. Thus, lake chlorophyll responses to drought are related to interactions between lake type and surface connectivity, long‐term average chlorophyll a, and many other multi‐scaled ecological factors (e.g., soil erodibility, minimum air temperature). These results reinforce the importance of integrating multi‐scaled ecological context to determine and predict the impacts of global changes on lakes.

Vegetation restoration effectiveness with main factors in the Beijing-Tianjin sandstorm source region during 2000-2020, China.

The Beijing-Tianjin Sandstorm Source Region (BTSSR), a region with significant vegetation degradation in China, has been subjected to ecological engineering intended to curb vegetation browning. Nevertheless, few studies have used multisource data to quantitatively evaluate the vegetation restoration effectiveness in the BTSSR, and the relationship between ecological engineering and vegetation restoration effectiveness in this region from statistical evidence has received little attention so far. Here, we employed the comprehensive vegetation parameters to describe the vegetation restoration effectiveness, and examined the driving mechanism of natural and human factors in different sub regions. First, we evaluated the vegetation restoration effectiveness in the BTSSR using an index that combined Fractional Vegetation Coverage (FVC) and Net Primary Productivity (NPP). Our results showed that the vegetation restoration effectiveness has significantly increased over time. From 2000 to 2020, 60.9% of the area achieved significant vegetation restoration, and the area with higher vegetation restoration effectiveness was concentrated in the southern part of the study area. Then, we used the Geodetector Model to explore the main factors and their interactions affecting vegetation restoration effectiveness. We found that the vegetation restoration effectiveness in the entire area was dominated by annual precipitation, in the northern part of the study area was led by climate, and in the southern part of the study area was dominated by ecological engineering. We further demonstrated that the interaction between ecological engineering and climate, soil conditions, geographical background and socioeconomic had the synergistic effect on vegetation restoration effectiveness, and the interaction between ecological engineering and annual precipitation had the greatest impact. We recommend that the northern region of the BTSSR continue to build low-density wind and sand control forests, while the southern region needs to be strengthened to prevent soil erosion problems caused by the expansion of human activities.

Breast cancer statistics for Japan in 2022: annual report of the national clinical database-breast cancer registry-clinical implications including chemosensitivity of breast cancer with low estrogen receptor expression.

This is an annual report by the Japanese Breast Cancer Society, which provides statistics on the clinical data on breast cancer in Japan, extracted from the National Clinical Database-Breast Cancer Registry (NCD-BCR). This report includes an update of 102,453 breast cancer cases at 1339 institutions registered in the NCD-BCR in 2022. Among the 101,793 female patients, the median age at cancer diagnosis was 62years (interquartile range, 50-73years), and 29.4% of the patients were premenopausal. Of these patients, 15,437 (15.2%) and 42,936 (42.2%) were diagnosed with stage 0 and I disease, respectively. Estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (HER2) were positive in 78.7%, 69.4%, and 12.8% of the patients, respectively. Of the 97,154 patients without distant metastasis, 40,521 (41.7%) underwent breast-conserving surgery, and 5780 (5.9%) patients underwent some form of breast reconstruction procedures at the time of mastectomy. A total of 66,894 (68.9%) patients were treated with sentinel lymph node biopsy and 7155 (7.4%) patients were treated with sentinel lymph node biopsy followed by axillary node dissection. In the group of patients treated with breast-conserving surgery (n = 40,521), 29,500 (72.8%) received whole-breast irradiation. In the group of patients who underwent mastectomy (n = 54,476), 6226 (11.4%) received radiation therapy to the chest wall. Of the 13,950 patients receiving preoperative chemotherapy with or without molecular targeted therapy, 4308 (30.9%) achieved a pathological complete response, with the highest rate of 60.5% in patients with the hormone receptor-negative/HER2-positive subtype.

The Impact of Job Satisfaction and Transformational Leadership on Turnover Intention of Front-End Employees at PT.XYZ

In an era of increasingly fierce and dynamic business competition, a strong drive and effort are needed to achieve success to become a winner in business competition. In the process, several factors cannot be separated, there is the human resource factor. Companies must improve the quality of human resources but also maintains the quantity of human resources supply ti maintain the stability of company’s performance. One of the obstacles that a company experiences difficulties or obstacles in the process of running its business is the high turnover rate within a company. Therefore, companies need to think about strategies to retain employees who have high-quality of performance and know what factors influence employees' intentions to leave the company. The purpose of this study is to determine the description of Job Satisfaction, description of Transformational Leadership and the description of Turnover Intention in Front End Employees at PT. XYZ, as well as a description of the effect of Job Satisfaction on Turnover Intention and a description of the effect of Transformational Leadership on Turnover Intention in Front End employees at PT. XYZ. in Indonesia. This research method was conducted with quantitative research - causality, with the population of Front-End permanent and contract employees at PT. XYZ with a minimum 3-month service period. This study uses data collection techniques through a questionnaire consisting of 41 questions regarding the variables studied and the number of samples determined by Slovin's formula of 178 respondents where the sample determination uses a Proportionate stratified random sampling technique. The data analysis technique uses Structural Equation Modelling (SEM) with Partial Least Squares (PLS) technique using SmartPLS software version 3.2.8. The results of hypothesis testing state that Job satisfaction (-0.246) and Transformational Leadership (-0.562) have a significant influence and have a negative effect on Turnover Intention. This highlights the importance of conducting a thorough review of company policies and strategies related to Job Satisfaction and the implementation of Transformational Leadership to reduce Turnover Intention of Front-End employees at PT.XYZ.

Predictive score for response to neoadjuvant chemotherapy in early-stage HR + /HER2- breast cancer.

Neoadjuvant chemotherapy (NACT) is a treatment option for early-stage hormone receptor-positive human epidermal growth factor receptor 2-negative (HR + /HER2-) breast cancer. Despite its use, pathological response rates in this subtype are often lower, and the impact of individual risk factors remains unclear. This study aimed to identify biomarkers and create a predictive score for NACT response. This retrospective, single-center study included patients with stage IIA-IIIC HR + /HER2- breast cancer treated with NACT and surgery (2019-2023). Multiple logistic regression analyzed associations between clinicopathological variables and pathologic response (partial/complete vs. absent) (p < 0.05). The best-performing model was used to develop a risk score. The study included 101 patients. Significant predictors of pathological response included tumor grade (G2/3 vs. G1), menopausal status (pre- vs. post-menopausal), and intrinsic subtype (luminal B vs. A). A dynamic calculator was created incorporating grade, hormonal status, intrinsic subtype, and Ki-67. This tool provides real-time input, facilitating personalized therapeutic decision-making.

Efficacy of Zenocutuzumab in NRG1 Fusion–Positive Cancer

BackgroundNeuregulin 1 (NRG1) fusions are recurrent oncogenic drivers found in multiple solid tumors. NRG1 binds to human epidermal growth factor receptor 3 (HER3), leading to heterodimerization with HER2 and activation of downstream growth and proliferation pathways. The efficacy and safety of zenocutuzumab, a bispecific antibody against HER2 and HER3, in patients with NRG1 fusion–positive solid tumors are unclear.MethodsIn this registrational, phase 2 clinical study, we assigned patients with advanced NRG1 fusion–positive cancer involving any tumor type to receive zenocutuzumab at a dose of 750 mg intravenously every 2 weeks. The primary end point was overall response (complete or partial response) according to investigator assessment. Secondary end points included duration of response, progression-free survival, and safety.ResultsA total of 204 patients with 12 tumor types were enrolled and treated. Among 158 patients who had measurable disease and were enrolled at least 24 weeks before the data-cutoff date, a response occurred in 30% (95% confidence interval [CI], 23 to 37). The median duration of response was 11.1 months (95% CI, 7.4 to 12.9); 19% of responses were ongoing at the data-cutoff date. Responses were observed in multiple tumor types — including in 27 of 93 patients (29%; 95% CI, 20 to 39) with non–small-cell lung cancer (NSCLC) and 15 of 36 patients (42%; 95% CI, 25 to 59) with pancreatic cancer — and across multiple NRG1 fusion partners. The median progression-free survival was 6.8 months (95% CI, 5.5 to 9.1). Adverse events were primarily grade 1 or 2. The most common adverse events that were considered by the investigator to be related to zenocutuzumab were diarrhea (in 18% of the patients), fatigue (in 12%), and nausea (in 11%). Infusion-related reactions (composite term) were observed in 14% of the patients. One patient discontinued zenocutuzumab owing to a treatment-related adverse event.ConclusionsZenocutuzumab showed efficacy in patients with advanced NRG1 fusion–positive cancer, notably NSCLC and pancreatic cancer, with mainly low-grade adverse events. (Funded by Merus; eNRGy ClinicalTrials.gov number, NCT02912949.)

Leveraging Large Language Models for Enhancing Safety in Maritime Operations

Maritime operations play a critical role in global trade but face persistent safety challenges due to human error, environmental factors, and operational complexities. This review explores the transformative potential of Large Language Models (LLMs) in enhancing maritime safety through improved communication, decision-making, and compliance. Specific applications include multilingual communication for international crews, automated reporting, interactive training, and real-time risk assessment. While LLMs offer innovative solutions, challenges such as data privacy, integration, and ethical considerations must be addressed. This review concludes with actionable recommendations and insights for leveraging LLMs to build safer and more resilient maritime systems.

DNA methylation and immune evasion in triple-negative breast cancer: challenges and therapeutic opportunities

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Chemotherapy remains the primary treatment option, yet TNBC frequently develops resistance, leading to relapse and metastasis. Emerging evidence highlights the potential of combining DNA methylation inhibitors with immune checkpoint inhibitors (ICIs). DNA methylation contributes to immune escape by silencing immune-regulatory genes, thereby reducing the tumor’s visibility to immune cells. Reversing this epigenetic modification can reinvigorate immune surveillance and enhance the efficacy of immunotherapies. This review discusses the role of DNA methylation in TNBC progression and immune evasion, focusing on recent advances in combination therapies involving DNA methylation inhibitors and ICIs. We discuss the underlying mechanisms that enable these therapeutic synergies, preclinical and clinical evidence supporting the approach, and the challenges posed by tumor heterogeneity, drug resistance, and toxicity. Finally, we explore the potential for personalized treatment strategies incorporating multi-omics data to optimize therapeutic outcomes. The integration of epigenetic therapies and immunotherapy offers a promising avenue for improving survival in TNBC patients.

Using Broken Windows Theory to Examine Flow Disruptions in Surgical Care: A Multispecialty Comparison.

Minimally invasive innovations enhance procedural technology. However, healthcare quality demands addressing mental and physical workloads. This study analyzes flow disruptions uncovering specialty-specific patterns and systemic weaknesses, to enhance quality, processes, and patient safety. Twenty-five cardiovascular, 40 orthopedic, 65 trauma care, and 30 neurosurgical cases were examined. The data were categorized using human factor taxonomy, and descriptive statistics were applied. Comparing the four specialties using RIPCORD TWA taxonomy, cardiovascular and trauma care were translated into one disruption every 2.2 minutes, followed by neurosurgery with one disruption every 2.7 minutes and orthopedics with one disruption every 3.7 minutes. Interruptions were the highest percentage for cardiovascular and orthopedics, with 54% and 46% of flow disruptions. Trauma care was heavily affected by communication flow disruption with 33%. Layout and coordination issues accumulate 26% of flow disruptions in neurosurgery. Cardiovascular, orthopedics, trauma care, and neurosurgery each feature distinct workflows, risks, and teamwork dynamics, demanding tailored process improvements. By analyzing flow disruptions and systemic weaknesses, this study highlights patterns unique to each specialty, advocating for tailored interventions to enhance communication, coordination, layout optimization, and equipment usability for improved surgical safety and quality.

Does management support drive sustained agile usage? a serial mediation model and cIPMA perspective.

Agile software development is immensely popular in the industry, but most teams struggle to sustain its use. Human factors like management support, agile training, agile mindset, and team resilience are often neglected, hindering long-term success. However, research has not explored their underlying mechanisms in depth. Therefore, this study examines if management support impacts the sustained usage of agile methodologies within software development teams. It subsequently investigates the individual and serial mediating effects of agile training, the agile mindset, and team resilience on this relationship. Additionally, it compares the importance and performance of management support, agile training, the agile mindset, and team resilience in infusing agile practices. Finally, it determines these antecedents' necessity for the enduring success of agile application. Data collected from 391 agile software development professionals using a structured questionnaire. Partial-least-squares structural equation modelling, importance-performance map analysis and necessary condition analysis were used to investigate relationships. The findings underscore the pivotal role of management support in infusing agile practices. Agile training, mindset, and team resilience emerge as critical mediators, with a strong serial mediation effect. While management support is paramount, its practical implementation falls short within teams. All four antecedents are found to be necessary for optimal agile sustainment. Thus, this study significantly advances theoretical understanding by introducing a serial mediation model that elucidates their mechanisms in impacting agile infusion. It extends prior organisational-level findings to the team-level. The study's quantitative verification of qualitative findings strengthens their generalisability to a broader spectrum of teams. It pioneers in expounding the constructs' relative importance, performance and necessity, to offer actionable insights for agile practitioners. Finally, it provides methodological guidance to apply importance performance map analysis and necessary condition analysis in agile software development research.

Spatial-temporal evolution of habitat quality in tropical monsoon climate region based on “pattern–process–quality” – a case study of Cambodia

Abstract Exploring the coupling relationship of “pattern–process–quality” is conducive to understanding the internal mechanism of habitat quality change, and is of great significance for the function maintenance and sustainable management of regional ecosystems. Existing studies mainly analyze the spatial-temporal evolution of habitat quality from the perspective of “pattern quality” and land use data. However, the variation in habitat quality is the result of many factors such as “pattern–process–quality” of the habitat. Therefore, it is necessary to consider these factors comprehensively when studying the change in habitat quality, so as to understand the change mechanism of habitat quality more comprehensively and deeply. This study takes Cambodia, a tropical monsoon climate region, as the research area, and uses land cover data from 2000 to 2022 as the data source. InVEST model is used to analyze the spatial-temporal evolution of habitat quality, and explore the relationship between habitat quality and land use, landscape pattern, and ecological process. The results show that (1) during 2000–2022, forest in Cambodia covered a wide range, showing a landscape pattern mainly distributed in the east and west. (2) The degree of fragmentation of impervious landscape pattern increased gradually from 2000 to 2022, indicating that it was seriously affected by human activities and natural factors, and with the increase in elevation and slope, the area of various types converted to impervious decreased. (3) During 2000–2022, high habitat quality areas were concentrated in Tonle SAP Lake in the east, southwest, and central part of Cambodia, while low habitat quality areas were concentrated in the central part. (4) Natural factors, socio-economic factors, policies, and regulations all have an impact on the change in land use pattern and habitat quality in Cambodia.