Anti-EGFR antibody-drug conjugate carrying an inhibitor targeting CDK restricts triple-negative breast cancer growth.

PURPOSE: Anti-EGFR antibodies show limited response in breast cancer, partly due to activation of compensatory pathways. Furthermore, despite clinical success of CDK4/6 inhibitors in hormone receptor-positive tumors, aggressive triple-negative breast cancers (TNBCs) are largely resistant due to CDK2/cyclin E expression, while free CDK2 inhibitors display normal tissue toxicity, limiting their therapeutic application. A cetuximab-based antibody drug conjugate (ADC) carrying a CDK inhibitor selected based on oncogene dysregulation, alongside patient subgroup stratification, may provide EGFR-targeted delivery. EXPERIMENTAL DESIGN: Expression of G1/S-phase cell cycle regulators were evaluated alongside EGFR in breast cancer. We conjugated cetuximab with CDK inhibitor SNS-032, for specific delivery to EGFR-expressing cells. We assessed ADC internalization, and its anti-tumor functions in vitro and in orthotopically-grown basal-like/TNBC xenografts. RESULTS: Transcriptomic (6173 primary, 27 baseline and matched post-chemotherapy residual tumors), scRNA-seq (150290 cells, 27 treatment-naïve tumors) and spatial transcriptomic (43 tumor sections, 22 TNBCs) analyses confirmed expression of CDK2 and its cyclin partners in basal-like/TNBCs, associated with EGFR. Spatiotemporal live-cell imaging and super-resolution confocal microscopy demonstrated ADC colocalization with late lysosomal clusters. The ADC inhibited cell cycle progression, induced cytotoxicity against high EGFR-expressing tumor cells and bystander killing of neighboring EGFR-low tumor cells, but minimal effects on immune cells. Despite carrying a small fraction of the drug, the ADC restricted EGFR-expressing spheroid and cell line/patient-derived xenograft tumor growth. CONCLUSIONS: Exploiting EGFR overexpression, and dysregulated cell cycle in aggressive and treatment-refractory tumors, a cetuximab-CDK inhibitor ADC may provide selective and efficacious delivery of cell cycle-targeted agents to basal-like/TNBCs, including chemotherapy-resistant residual disease.

A comprehensive case study on successful multimodal therapy in philadelphia chromosome-positive acute myeloid leukemia with NPM1 and IDH2 mutations.

A 67-year-old female came to Tampa General Hospital with Philadelphia chromosome-positive (Ph+) acute myeloid leukemia (AML) featuring an intriguing combination of mutations, including NPM1 and IDH2 mutations. Novel combination therapy with azacitidine, venetoclax and ponatinib allowed her to successfully achieve a complete response (CR) and undergo an allogeneic hematopoietic stem cell transplant (HSCT). This case report provides an overview of her clinical course, emphasizing the significance of integrated therapy and the challenges associated with balancing treatment for AML. It also underscores the importance of a multidisciplinary approach and careful monitoring of patients with complex hematologic conditions.

Impact of project managers emotional intelligence on megaprojects success through mediating role of human related agile challenges: Project management as a moderator.

Globalization and competition drive rapid adoption of new technologies, leading to a rise in complex projects. Project managers need to know how to lead teams through the planning and execution phases of a project while keeping in line with the organization's objectives. In order to successfully manage complex projects, emotional intelligence is an essential leadership quality. Therefore, the present research aimed to investigate the impact of project manager's emotional intelligence (PMEI) on megaprojects China-Pakistan Economic Corridor (CPEC) success through mediating roles of human-related agile challenges Inventory (HRACI) and project success factors (PSF), and project management as a moderator. The study employed convenience and purposive sampling methods to collect data from 533 project managers working on CPEC projects. The Smart PLS 4 software was utilized to evaluate the hypotheses. The results of this study indicated that the direct effect of a PMEI is not significant on CPEC. However, through mediating variables, HRACI exhibited a negative and significant association, while PSF positively and significantly mediate the relationship among PMEI and CPEC. Furthermore, project management as a moderator has a significant and positive effect on PMEI and PSF, however, insignificant between PMEI and CPEC, and negatively significant among PMEI and HRACI. The findings of this study are of great significance for project managers and project leaders. They will need to acquire the skills to prevent issues from arising, particularly when conflicts emerge, in order to ensure the success of megaproject. Therefore, current study recommend that PMEI appears to have a vital role in social interactions, promoting emotions of trust, efficient communication, and cooperation with other project teams in high-stress work environments like CPEC. Lastly, theoretical and practical contributions are discussed, as well as research constraints and future research directions.

AI in Hand Surgery: Assessing Large Language Models in the Classification and Management of Hand Injuries.

Background: OpenAI's ChatGPT (San Francisco, CA, USA) and Google's Gemini (Mountain View, CA, USA) are two large language models that show promise in improving and expediting medical decision making in hand surgery. Evaluating the applications of these models within the field of hand surgery is warranted. This study aims to evaluate ChatGPT-4 and Gemini in classifying hand injuries and recommending treatment. Methods: Gemini and ChatGPT were given 68 fictionalized clinical vignettes of hand injuries twice. The models were asked to use a specific classification system and recommend surgical or nonsurgical treatment. Classifications were scored based on correctness. Results were analyzed using descriptive statistics, a paired two-tailed t-test, and sensitivity testing. Results: Gemini, correctly classifying 70.6% hand injuries, demonstrated superior classification ability over ChatGPT (mean score 1.46 vs. 0.87, p-value < 0.001). For management, ChatGPT demonstrated higher sensitivity in recommending surgical intervention compared to Gemini (98.0% vs. 88.8%), but lower specificity (68.4% vs. 94.7%). When compared to ChatGPT, Gemini demonstrated greater response replicability. Conclusions: Large language models like ChatGPT and Gemini show promise in assisting medical decision making, particularly in hand surgery, with Gemini generally outperforming ChatGPT. These findings emphasize the importance of considering the strengths and limitations of different models when integrating them into clinical practice.

A RIPK1-specific PROTAC degrader achieves potent antitumor activity by enhancing immunogenic cell death.

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) functions as a critical stress sentinel that coordinates cell survival, inflammation, and immunogenic cell death (ICD). Although the catalytic function of RIPK1 is required to trigger cell death, its non-catalytic scaffold function mediates strong pro-survival signaling. Accordingly, cancer cells can hijack RIPK1 to block necroptosis and evade immune detection. We generated a small-molecule proteolysis-targeting chimera (PROTAC) that selectively degraded human and murine RIPK1. PROTAC-mediated depletion of RIPK1 deregulated TNFR1 and TLR3/4 signaling hubs, accentuating the output of NF-κB, MAPK, and IFN signaling. Additionally, RIPK1 degradation simultaneously promoted RIPK3 activation and necroptosis induction. We further demonstrated that RIPK1 degradation enhanced the immunostimulatory effects of radio- and immunotherapy by sensitizing cancer cells to treatment-induced TNF and interferons. This promoted ICD, antitumor immunity, and durable treatment responses. Consequently, targeting RIPK1 by PROTACs emerges as a promising approach to overcome radio- or immunotherapy resistance and enhance anticancer therapies.

Comparative Analysis of Artificial Intelligence Virtual Assistant and Large Language Models in Post-Operative Care.

In postoperative care, patient education and follow-up are pivotal for enhancing the quality of care and satisfaction. Artificial intelligence virtual assistants (AIVA) and large language models (LLMs) like Google BARD and ChatGPT-4 offer avenues for addressing patient queries using natural language processing (NLP) techniques. However, the accuracy and appropriateness of the information vary across these platforms, necessitating a comparative study to evaluate their efficacy in this domain. We conducted a study comparing AIVA (using Google Dialogflow) with ChatGPT-4 and Google BARD, assessing the accuracy, knowledge gap, and response appropriateness. AIVA demonstrated superior performance, with significantly higher accuracy (mean: 0.9) and lower knowledge gap (mean: 0.1) compared to BARD and ChatGPT-4. Additionally, AIVA's responses received higher Likert scores for appropriateness. Our findings suggest that specialized AI tools like AIVA are more effective in delivering precise and contextually relevant information for postoperative care compared to general-purpose LLMs. While ChatGPT-4 shows promise, its performance varies, particularly in verbal interactions. This underscores the importance of tailored AI solutions in healthcare, where accuracy and clarity are paramount. Our study highlights the necessity for further research and the development of customized AI solutions to address specific medical contexts and improve patient outcomes.

Artificial Intelligence Support for Informal Patient Caregivers: A Systematic Review.

This study aims to explore how artificial intelligence can help ease the burden on caregivers, filling a gap in current research and healthcare practices due to the growing challenge of an aging population and increased reliance on informal caregivers. We conducted a search with Google Scholar, PubMed, Scopus, IEEE Xplore, and Web of Science, focusing on AI and caregiving. Our inclusion criteria were studies where AI supports informal caregivers, excluding those solely for data collection. Adhering to PRISMA 2020 guidelines, we eliminated duplicates and screened for relevance. From 947 initially identified articles, 10 met our criteria, focusing on AI's role in aiding informal caregivers. These studies, conducted between 2012 and 2023, were globally distributed, with 80% employing machine learning. Validation methods varied, with Hold-Out being the most frequent. Metrics across studies revealed accuracies ranging from 71.60% to 99.33%. Specific methods, like SCUT in conjunction with NNs and LibSVM, showcased accuracy between 93.42% and 95.36% as well as F-measures spanning 93.30% to 95.41%. AUC values indicated model performance variability, ranging from 0.50 to 0.85 in select models. Our review highlights AI's role in aiding informal caregivers, showing promising results despite different approaches. AI tools provide smart, adaptive support, improving caregivers' effectiveness and well-being.

Assessment of textile effluent treatment by immobilized Trametes pubescens MB 89 for plant growth promotion.

Industrialization and the ever-increasing world population have diminished high-quality water resources for sustainable agriculture. It is imperative to effectively treat industrial effluent to render the treated water available for crop cultivation. This study aimed to assess the effectiveness of textile effluent treated with Trametes pubescens MB 89 in supporting maize cultivation. The fungal treatment reduced the amounts of Co, Pb and As in the textile effluent. The biological oxygen demand, total dissolved solids and total suspended solids were within the permissible limits in the treated effluent. The data indicated that the irrigation of maize with fungal-treated textile effluent improved the growth parameters of the plant including root, shoot length, leaf area and chlorophyll content. Moreover, better antioxidant activity, total phenol content and protein content in roots, stems and leaves of maize plants were obtained. Photosynthetic parameters (potential quantum yield, electron transport rate and fluorescence yield of non-photochemical losses other than heat) were also improved in the plants irrigated with treated effluent as compared to the control groups. In conclusion, the treatment of textile effluent with the immobilized T. pubescens presents a sustainable solution to minimize chemical pollution and effectively utilize water resources.

AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research.

INTRODUCTION: As large language models receive greater attention in medical research, the investigation of ethical considerations is warranted. This review aims to explore surgery literature to identify ethical concerns surrounding these artificial intelligence models and evaluate how autonomy, beneficence, nonmaleficence, and justice are represented within these ethical discussions to provide insights in order to guide further research and practice. METHODS: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Five electronic databases were searched in October 2023. Eligible studies included surgery-related articles that focused on large language models and contained adequate ethical discussion. Study details, including specialty and ethical concerns, were collected. RESULTS: The literature search yielded 1179 articles, with 53 meeting the inclusion criteria. Plastic surgery, orthopedic surgery, and neurosurgery were the most represented surgical specialties. Autonomy was the most explicitly cited ethical principle. The most frequently discussed ethical concern was accuracy (n = 45, 84.9%), followed by bias, patient confidentiality, and responsibility. CONCLUSION: The ethical implications of using large language models in surgery are complex and evolving. The integration of these models into surgery necessitates continuous ethical discourse to ensure responsible and ethical use, balancing technological advancement with human dignity and safety.

Genomic characterization of human respiratory syncytial virus circulating in Islamabad, Pakistan, during an outbreak in 2022-2023.

In this study, conducted at the National Institute of Health, Islamabad, during an outbreak of human respiratory syncytial virus (hRSV) from December 2022 to January 2023, the first whole-genome sequences of hRSV isolates from Islamabad, Pakistan, were determined. Out of 10 positive samples, five were sequenced, revealing the presence of two genotypes: RSV-A (GA2.3.5, ON1 strain) and RSV-B (GB5.0.5.a, BA-10 strain). A rare non-synonymous substitution (E232G) in G the protein and N276S in the F protein were found in RSV-A. In RSV-B, the unique mutations K191R, Q209R, and I206M were found in the F protein. These mutations could potentially influence vaccine efficacy and viral pathogenicity. This research underscores the importance of genomic surveillance for understanding RSV diversity and guiding public health responses in Pakistan.

Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer.

BACKGROUND: Invasive Lobular Carcinoma (ILC) is a morphologically distinct breast cancer subtype that represents up to 15% of all breast cancers. Compared to Invasive Breast Carcinoma of No Special Type (IBC-NST), ILCs exhibit poorer long-term outcome and a unique pattern of metastasis. Despite these differences, the systematic discovery of robust prognostic biomarkers and therapeutically actionable molecular pathways in ILC remains limited. METHODS: Pathway-centric multivariable models using statistical machine learning were developed and tested in seven retrospective clinico-genomic cohorts (n = 996). Further external validation was performed using a new RNA-Seq clinical cohort of aggressive ILCs (n = 48). RESULTS AND CONCLUSIONS: mRNA dysregulation scores of 25 pathways were strongly prognostic in ILC (FDR-adjusted P < 0.05). Of these, three pathways including Cell-cell communication, Innate immune system and Smooth muscle contraction were also independent predictors of chemotherapy response. To aggregate these findings, a multivariable machine learning predictor called PSILC was developed and successfully validated for predicting overall and metastasis-free survival in ILC. Integration of PSILC with CRISPR-Cas9 screening data from breast cancer cell lines revealed 16 candidate therapeutic targets that were synthetic lethal with high-risk ILCs. This study provides interpretable prognostic and predictive biomarkers of ILC which could serve as the starting points for targeted drug discovery for this disease.

Evaluation of antihypertensives for post partum management of hypertensive disorders of pregnancy: A systematic review and meta-analysis.

BACKGROUND: There is a lack of evidence that directly shows the best antihypertensive treatment options for post partum management of the hypertensive disorders of pregnancy. Our objective was to analyze the safest and most effective antihypertensive drugs post partum for patients with hypertensive disorders of pregnancy. METHODS: PubMed, Cochrane, and MEDLINE were searched to find relevant articles published from inception to Feb 2024. We included randomized control trials, in English, featuring a population of postnatal women with hypertensive disorders of pregnancy or postpartum women with de novo hypertension with a follow-up of up to 6 months in which any antihypertensive medication was compared with Placebo or a comparison between different doses of antihypertensives was done. The statistical analyses were conducted using Review Manager with a random-effects model. RESULTS: Our analysis revealed that almost all antihypertensives are effective in treating postpartum hypertension. However, some medications had alternating roles in controlling specific outcomes. Using calcium channel blockers resulted in a faster time to sustain BP control than the control (SMD: -0.37; 95% CI: -0.73 to -0.01; P = 0.04). In contrast, using ACE inhibitors or ARBs demanded the use of other antihypertensives in contrast to all other drugs assessed (RR: 2.09; 95% CI: 1.07 to 4.07; P = 0.03). CONCLUSION: Timely management of the hypertensive disorders of pregnancy postpartum is life-saving. All the traditional antihypertensives we assessed effectively manage hypertension postpartum, thus allowing the physician to tailor the particular drug regimen according to the patient's needs and comorbidities without any hindrance.

Shifting perspectives in coronary involvement of polyarteritis nodosa: case of 3-vessel occlusion treated with 4-vessel CABG and review of literature.

BACKGROUND: Polyarteritis Nodosa (PAN) is a systemic vasculitis (SV) historically thought to spare the coronary arteries. Coronary angiography and contemporary imaging reveal coronary stenosis and dilation, which are associated with significant morbidity and mortality. Coronary arteries in PAN are burdened with accelerated atherosclerosis from generalized inflammation adding to an inherent arteritic process. Traditional atherosclerotic risk factors fail to approximate risk. Few reports document coronary pathology and optimal therapy has been guarded. METHODS: Database publication query of English literature from 1990-2022. RESULTS: Severity of coronary involvement eludes laboratory monitoring, but coronary disease associates with several clinical symptoms. Framingham risk factors inadequately approximate disease burden. Separating atherosclerosis from arteritis requires advanced angiographic methods. Therapy includes anticoagulation, immunosuppression and revascularization. PCI has been the mainstay, though stenting is confounded by vagarious alteration in luminal diameter and reports of neointimization soon after placement. CONCLUSIONS: When graft selection avoids the vascular territory of SV's, CABG offers definitive therapy. We have contributed report of a novel CABG configuration in addition to reviewing, updating and discussing the literature. Accumulating evidence suggests discrete clinical symptoms warrant suspicion for coronary involvement.

Synthesis of Water-Dispersible Poly(dimethylsiloxane) and Its Potential Application in the Paper Coating Industry as an Alternative for PFAS-Coated Paper and Single-Use Plastics.

Polyethylene-, polyvinylidene chloride-, and per- and polyfluoroalkyl substance-coated paper generate microplastics or fluorochemicals in the environment. Here, we report an approach for the development of oil-resistant papers using an environmentally friendly, fluorine-free, water-dispersible poly(dimethylsiloxane) (PDMS) coating on kraft paper. Carboxylic-functionalized PDMS (PDMS-COOH) was synthesized and subsequently neutralized with ammonium bicarbonate to obtain a waterborne emulsion, which was then coated onto kraft paper. The water resistance of the coated paper was determined via Cobb60 measurements. The Cobb60 value was reduced to 2.70 ± 0.14 g/m2 as compared to 87.6 ± 5.1 g/m2 for uncoated paper, suggesting a remarkable improvement in water resistance. Similarly, oil resistance was found to be 12/12 on the kit test scale versus 0/12 for uncoated paper. In addition, the coated paper retained 70-90% of its inherent mechanical properties, and more importantly, the coated paper was recycled via pulp recovery using a standard protocol with a 91.1% yield.

Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care: A Scoping Review of Current Clinical Implementations.

Primary Care Physicians (PCPs) are the first point of contact in healthcare. Because PCPs face the challenge of managing diverse patient populations while maintaining up-to-date medical knowledge and updated health records, this study explores the current outcomes and effectiveness of implementing Artificial Intelligence-based Clinical Decision Support Systems (AI-CDSSs) in Primary Healthcare (PHC). Following the PRISMA-ScR guidelines, we systematically searched five databases, PubMed, Scopus, CINAHL, IEEE, and Google Scholar, and manually searched related articles. Only CDSSs powered by AI targeted to physicians and tested in real clinical PHC settings were included. From a total of 421 articles, 6 met our criteria. We found AI-CDSSs from the US, Netherlands, Spain, and China whose primary tasks included diagnosis support, management and treatment recommendations, and complication prediction. Secondary objectives included lessening physician work burden and reducing healthcare costs. While promising, the outcomes were hindered by physicians' perceptions and cultural settings. This study underscores the potential of AI-CDSSs in improving clinical management, patient satisfaction, and safety while reducing physician workload. However, further work is needed to explore the broad spectrum of applications that the new AI-CDSSs have in several PHC real clinical settings and measure their clinical outcomes.

Percutaneous Needle Decompression: A Novel Approach Toward Treating Compartment Syndrome of the Leg.

Percutaneous needle decompression (PND) can be a successful alternative to open fasciotomies for acute compartment syndrome (ACS). We present the case of a 45-year-old male patient who survived a road traffic accident and developed ACS following his open fracture of the tibia and fibula. He was treated by performing PND on all compartments of the affected leg using a 24 gauge needle thus avoiding the complications of a double incision fasciotomy.

Erratum: Clinical trials landscape in lower middle-income country (Pakistan) - CORRIGENDUM.

[This corrects the article DOI: 10.1017/cts.2023.701.].

Clinical trials landscape in a lower-middle-income country (Pakistan).

In recent times, there have been calls from within the developing nations for increased ownership by governmental research bodies and universities of the priority research setting and research that aligns with national health strategies. This is a review paper of the studies that have been published on clinical trials in developing countries, with a focus mainly on Pakistan. The literature review used online databases such as PubMed, Scopus, and Google Scholar, World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP), and ClinicalTrials.gov trial registries to search for clinical trials conducted in Pakistan between January 2000 and December 2022 and analyzed. The results revealed that clinical research in Pakistan is hindered by a number of barriers, including a lack of funding, skilled personnel, and regulatory issues. Lack of funding is a common obstacle, and the majority of funding for clinical trials originates from Western countries or pharmaceutical companies established in the West. In conclusion, clinical studies in developing countries, especially in Pakistan, are hindered by a plethora of barriers, and to improve the current state, increasing funding, streamlining ethical approval procedures, simplifying regulatory systems, addressing cultural and religious concerns, and participating in global efforts to bridge the gap in health-based research are crucial.

Racial disparities in rates of invasiveness of resected intraductal papillary mucinous neoplasms in the United States.

BACKGROUND: Racial and ethnic disparities have been observed in the multidisciplinary management of pancreatic ductal adenocarcinoma. Intraductal papillary mucinous neoplasm is the most common identifiable precursor to pancreatic ductal adenocarcinoma, where early surgical intervention before the development of an invasive intraductal papillary mucinous neoplasm improves survival. The association of race/ethnicity with the risk of identifying invasive intraductal papillary mucinous neoplasms during resection has not been previously defined. METHODS: The American College of Surgeons National Quality Improvement Program targeted pancreatectomy database (2014-2021) was queried for patients with race/ethnicity data who underwent resection of an intraductal papillary mucinous neoplasm. Backward Wald logistic regression modeling (P ≤ 0.05 for entry; P > .10 for removal) was used to identify independent predictors of invasion. RESULTS: A total of 4,505 cases of resected intraductal papillary mucinous neoplasms were identified, with 923 (20.5%) demonstrating invasive intraductal papillary mucinous neoplasms. The cohort of individuals other than non-Hispanic Whites were significantly more likely to have invasive intraductal papillary mucinous neoplasms (White, 19.9%; Black, 24.2%; Asian, 23.7%; Hispanic, 22.6%; P = .026). Such disparity could not be explained by greater comorbidity, as non-White patients were significantly younger (age <65 years: 41.7% vs 33.2%, P < .001) and had better physical status (American Society of Anesthesiologists score ≤2: 28.8% vs 25.2%, P = .053). After controlling for clinicodemographic variables, being an individual of race/ethnicity other than White was independently associated with higher odds of invasive intraductal papillary mucinous neoplasms (odds ratio, 1.280; 95% confidence interval, 1.046-1.566; P = .017). No differences in postoperative morbidity were observed. CONCLUSION: In a national cohort of patients with resected intraductal papillary mucinous neoplasms, individuals who identified as being of race/ethnicity other than White were significantly more likely to have invasive intraductal papillary mucinous neoplasms during surgical resection.