Ethical implications of AI and robotics in healthcare: A review.

Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical innovation, promising enhanced diagnostics, streamlined processes, and improved patient care. However, this technological revolution is accompanied by intricate ethical implications that demand meticulous consideration. This article navigates the complex ethical terrain surrounding AI and robotics in healthcare, delving into specific dimensions and providing strategies and best practices for ethical navigation. Privacy and data security are paramount concerns, necessitating robust encryption and anonymization techniques to safeguard patient data. Responsible data handling practices, including decentralized data sharing, are critical to preserve patient privacy. Algorithmic bias poses a significant challenge, demanding diverse datasets and ongoing monitoring to ensure fairness. Transparency and explainability in AI decision-making processes enhance trust and accountability. Clear responsibility frameworks are essential to address the accountability of manufacturers, healthcare institutions, and professionals. Ethical guidelines, regularly updated and accessible to all stakeholders, guide decision-making in this dynamic landscape. Moreover, the societal implications of AI and robotics extend to accessibility, equity, and societal trust. Strategies to bridge the digital divide and ensure equitable access must be prioritized. Global collaboration is pivotal in developing adaptable regulations and addressing legal challenges like liability and intellectual property. Ethics must remain at the forefront in the ever-evolving realm of healthcare technology. By embracing these strategies and best practices, healthcare systems and professionals can harness the potential of AI and robotics, ensuring responsible and ethical integration that benefits patients while upholding the highest ethical standards.

Clinical significance and potential regulatory mechanism of overexpression of pituitary tumor-transforming gene transcription factor in bladder cancer.

BACKGROUND: Pituitary tumor transforming gene-1 (PTTG1) transcription factor is identified as carcinogenic and associated with tumor invasiveness, but its role in bladder cancer (BLCA) remains obscure. This research is intended to analyze the aberrant expression and clinical significance of PTTG1 in BLCA, explore the relationship between PTTG1 and tumor microenvironment characteristics and predict its potential transcriptional activity in BLCA tissue. METHODS: We compared the expression discrepancy of PTTG1 mRNA in BLCA and normal bladder tissue, using the BLCA transcriptomic datasets from GEO, ArrayExpress, TCGA, and GTEx. In-house immunohistochemical staining was implemented to determine the PTTG1 protein intensity. The prognostic value of PTTG1 was evaluated using the Kaplan-Meier Plotter. CRISPR screen data was utilized to estimate the effect PTTG1 interference has on BLCA cell lines. We predicted the abundance of the immune cells in the BLCA tumor microenvironment using the microenvironment cell populations-counter and ESTIMATE algorithms. Single-cell RNA sequencing data was applied to identify the major cell types in BLCA, and the dynamics of BLCA progression were revealed using pseudotime analysis. PTTG1 target genes were predicted by CistromeDB. RESULTS: The elevated expression level of PTTG1 was confirmed in 1037 BLCA samples compared with 127 non-BLCA samples, with a standardized mean difference value of 1.04. Higher PTTG1 expression status exhibited a poorer BLCA prognosis. Moreover, the PTTG1 Chronos genetic effect scores were negative, indicating that PTTG1 silence may inhibit the proliferation and survival of BLCA cells. With PTTG1 mRNA expression level increasing, higher natural killer, cytotoxic lymphocyte, and monocyte lineage cell infiltration levels were observed. A total of four candidate targets containing CHEK2, OCIAD2, UBE2L3, and ZNF367 were determined ultimately. CONCLUSIONS: PTTG1 mRNA over-expression may become a potential biomarker for BLCA prognosis. Additionally, PTTG1 may correlate with the BLCA tumor microenvironment and exert transcriptional activity by targeting CHEK2, OCIAD2, UBE2L3, and ZNF367 in BLCA tissue.

Empyema necessitans due to aspergillus in a 3-year-old paediatric patient at a referral hospital in Nairobi, Kenya.

We present a case of empyema necessitans due to aspergillus in a young child. The incidence of deep fungal mycoses in children, especially in developing countries is not known. There is paucity of data and access to diagnostics is usually limited. Our patient had received treatment for pulmonary tuberculosis which is endemic in Kenya for four months before diagnosis was made. We present this case to highlight the importance of considering alternative diagnosis when there is non-response to anti-tuberculous therapy.

Clinical value of survivin and its underlying mechanism in ovarian cancer: A bioinformatics study based on GEO and TCGA data mining.

OBJECTIVE: An increasing number of studies have confirmed that survivin (BIRC5) plays essential roles in ovarian cancer. Nevertheless, inconsistent or controversial results exist in some studies. In the present study, we sought to determine the clinical significance of survivin and its potential molecular pathways. METHODS: The correlation between survivin (BIRC5) expression and diagnostic value, prognostic value and clinicopathological features was assessed by meta-analysis with more than 4000 patients from literature, GEO and TCGA. In addition, the potential molecular mechanism of survivin in ovarian cancer was also determined. RESULTS: The pooled sensitivity and specificity were 0.71 (95%CI: 0.68-0.74) and 0.97 (95%CI: 0.94-0.98), respectively. The AUC of sROC was 0.8765. The results showed that there was also a significant relationship between survivin expression and poor overall survival (HR: 1.24, 95%CI: 1.14-1.35, p < 0.001), disease-free survival (HR: 1.53, 95%CI: 0.57-4.09, p < 0.001), as well as higher recurrence rate (HR: 1.11, 95%CI: 0.97-1.27). Moreover, survivin expression was also associated with tumor progression (cancerous vs. benign, OR: 11.29, 95%CI: 8.96-14.24, p < 0.001), TNM stage (III + IV vs. I + II, OR: 5.38, 95%CI: 4.16-6.97, p < 0.001), histological grades (G3 vs. G1 ∼ G2, OR: 4.36, 95%CI: 3.29-5.77, p < 0.001), and lymphatic metastasis (metastasis vs. non-metastasis, 3.35, 95%CI 2.36-4.75, p < 0.001). Bioinformatics analysis revealed the 50 most frequently altered neighboring genes of survivin in OC, and then Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. GO analysis showed that these genes were related to signal conduction, cell cycle, apoptosis, and metabolism. KEGG pathways analysis indicated that these genes were primarily enriched in mitotic prometaphase, PLK1 signaling events and the regulation of glucokinase by the glucokinase regulatory protein. CONCLUSION: Survivin (BIRC5) expression might become a specific but low-sensitivity biomarker in ovarian cancer patients, and its presence indicated poor prognosis and worse TNM stages. This protein might function as an oncoprotein by influencing specific pathways involving the 50 genes identified herein. Additional studies are needed to confirm these results.

Characterization of the Plasmodium Interspersed Repeats (PIR) proteins of Plasmodium chabaudi indicates functional diversity.

Plasmodium multigene families play a central role in the pathogenesis of malaria. The Plasmodium interspersed repeat (pir) genes comprise the largest multigene family in many Plasmodium spp. However their function(s) remains unknown. Using the rodent model of malaria, Plasmodium chabaudi, we show that individual CIR proteins have differential localizations within infected red cell (iRBC), suggesting different functional roles in a blood-stage infection. Some CIRs appear to be located on the surface of iRBC and merozoites and are therefore well placed to interact with host molecules. In line with this hypothesis, we show for the first time that a subset of recombinant CIRs bind mouse RBCs suggesting a role for CIR in rosette formation and/or invasion. Together, our results unravel differences in subcellular localization and ability to bind mouse erythrocytes between the members of the cir family, which strongly suggest different functional roles in a blood-stage infection.