Lumbar disc herniation (LDH) often results in significant pain and disability, and histopathologic (HP) evaluation of intervertebral discs (IVDs) offers critical insights into treatment outcomes. This prospective observational study explores HP changes in IVDs and their association with clinical outcomes following surgical treatment for LDH. A cohort of 141 patients undergoing MRI-confirmed LDH surgery underwent HP evaluation using a semi-quantitative HP degeneration score (HDS). Preoperatively and at a six-month follow-up, the comprehensive clinical assessment included the Oswestry disability index (ODI) and visual analog scale (VAS), with a minimal clinically important difference (MCID) calculated from ODI and VAS. Results indicated significant associations between higher HDS and adverse clinical outcomes, including persistent pain and greater disability post-surgery. Specifically, an HDS ≥ 7 was predictive (OR ═ 6.25, 95% CI: 2.56–15.23) of disability outcomes measured with MCID-ODI (AUC: 0.692, 95% CI: 0.609–0.767, P < 0.001), and HDS ≥ 8 was predictive (OR ═ 1.72, 95% CI: 1.04–2.77) of persistent pain measured with MCID-VAS (AUC ═ 0.628, 95% CI: 0.598–0.737, P ═ 0.008), highlighting the diagnostic potential of HDS in assessing postoperative recovery. This study underscores the potential of HP evaluation using HDS to provide valuable insights into disease progression and outcomes in LDH patients, complementing conventional radiologic methods. The findings support the application of personalized treatment strategies based on HP findings while acknowledging challenges in interpretation and clinical implementation.

Simple Summary This study explores hypoxia-inducible factors (HIFs) in glioblastoma development, progression, and treatment. Reviewing 104 relevant studies, it highlights diverse global contributions, with China leading at 23.1%. The most productive year was 2019, contributing 11.5% of the studies. Key factors studied included HIF1α, HIF2α, osteopontin, and cavolin-1, involving pathways such as GLUT1, GLUT3, VEGF, PI3K-Akt-mTOR, and ROS. HIF expression correlates with glioblastoma progression, survival, neovascularization, glucose metabolism, migration, and invasion. Overcoming treatment resistance and the lack of biomarkers is crucial for integrating HIF-related therapies into glioblastoma treatment to improve patient outcomes. Abstract Background: The study aims to investigate the role of hypoxia-inducible factors (HIFs) in the development, progression, and therapeutic potential of glioblastomas. Methodology: The study, following PRISMA guidelines, systematically examined hypoxia and HIFs in glioblastoma using MEDLINE (PubMed), Web of Science, and Scopus. A total of 104 relevant studies underwent data extraction. Results: Among the 104 studies, global contributions were diverse, with China leading at 23.1%. The most productive year was 2019, accounting for 11.5%. Hypoxia-inducible factor 1 alpha (HIF1α) was frequently studied, followed by hypoxia-inducible factor 2 alpha (HIF2α), osteopontin, and cavolin-1. Commonly associated factors and pathways include glucose transporter 1 (GLUT1) and glucose transporter 3 (GLUT3) receptors, vascular endothelial growth factor (VEGF), phosphoinositide 3-kinase (PI3K)-Akt-mechanistic target of rapamycin (mTOR) pathway, and reactive oxygen species (ROS). HIF expression correlates with various glioblastoma hallmarks, including progression, survival, neovascularization, glucose metabolism, migration, and invasion. Conclusion: Overcoming challenges such as treatment resistance and the absence of biomarkers is critical for the effective integration of HIF-related therapies into the treatment of glioblastoma with the aim of optimizing patient outcomes.

BACKGROUND When it comes to pandemic response, preparation can be the key. Between 2020 and 2024, the fast-paced development of COVID-19-often compounded by pubic policies' failures to reflect the latest reality and the public's divergent reactions to the pandemic and the policies-means that society should prepare for exit strategies that can reflect the reality of the pandemic and the interests of the people. Yet oftentimes societies only have one exit strategy with limited scope. This paper investigates the dangers of having only one pandemic exit strategy for pandemics like COVID-19. METHODS Analyses were based on a review of the literature on COVID-19 exit strategies and our own research. The PubMed literature search focused on two concepts-"COVID-19″ and "exit strategy"-and was limited to peer-reviewed papers published between 2020 and 2024 in English. RESULTS A total of 31 articles were included in the final review. Analyses showed that existing studies on COVID-19 exit strategies often focused on using the modelling method to gauge one exit strategy. Exit strategies were often discussed in the context of implementing, easing, or lifting specific pharmaceutical or non-pharmaceutical interventions. Staged and country-wide coordinated exit strategies were also discussed in the literature, both of which were often deemed as comparatively rigorous options compared to single or stand-alone exit strategies. Drawing on the overall development of COVID-19 and our own research, we presented and discussed the importance of having multiple exit strategies that are considerate of all possible pandemic trajectories, diverse interests of the public, and the communication challenges officials might face in introducing or implementing pandemic policies. CONCLUSION This paper underscored the importance of having multiple exit strategies for societies to prepare for pandemics. The insights of this study can help inform health policies so that they can more comprehensively and compassionately protect the needs and wants of the "public" in public health, particularly in grave times like COVID-19.

Introduction Clinicians encounter challenges in promptly diagnosing thoracolumbar injuries (TLIs) and fractures (VFs), motivating the exploration of Artificial Intelligence (AI) and Machine Learning (ML) and Deep Learning (DL) technologies to enhance diagnostic capabilities. Despite varying evidence, the noteworthy transformative potential of AI in healthcare, leveraging insights from daily healthcare data, persists. Research question This review investigates the utilization of ML and DL in TLIs causing VFs. Materials and methods Employing Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) methodology, a systematic review was conducted in PubMed and Scopus databases, identifying 793 studies. Seventeen were included in the systematic review, and 11 in the meta-analysis. Variables considered encompassed publication years, geographical location, study design, total participants (14,524), gender distribution, ML or DL methods, specific pathology, diagnostic modality, test analysis variables, validation details, and key study conclusions. Meta-analysis assessed specificity, sensitivity, and conducted hierarchical summary receiver operating characteristic curve (HSROC) analysis. Results Predominantly conducted in China (29.41%), the studies involved 14,524 participants. In the analysis, 11.76% (N = 2) focused on ML, while 88.24% (N = 15) were dedicated to deep DL. Meta-analysis revealed a sensitivity of 0.91 (95% CI = 0.86–0.95), consistent specificity of 0.90 (95% CI = 0.86–0.93), with a false positive rate of 0.097 (95% CI = 0.068–0.137). Conclusion The study underscores consistent specificity and sensitivity estimates, affirming the diagnostic test's robustness. However, the broader context of ML applications in TLIs emphasizes the critical need for standardization in methodologies to enhance clinical utility.

The culling of animals that are infected, or suspected to be infected, with COVID-19 has fuelled outcry. What might have contributed to the ongoing debates and discussions about animal rights protection amid global health crises is the lack of a unified understanding and internationally agreed-upon definition of “One Health”. The term One Health is often utilised to describe the imperative to protect the health of humans, animals, and plants, along with the overarching ecosystem in an increasingly connected and globalized world. However, to date, there is a dearth of research on how to balance public health decisions that could impact all key stakeholders under the umbrella of One Health, particularly in contexts where human suffering has been immense. To shed light on the issue, this paper discusses whether One Health means “human-centred connected health” in a largely human-dominated planet, particularly amid crises like COVID-19. The insights of this study could help policymakers make more informed decisions that could effectively and efficiently protect human health while balancing the health and well-being of the rest of the inhabitants of our shared planet Earth.

Introduction: Industrialization and urbanization led to a significant increase in the environment. Lead inhibits the activity of numerous enzymes, triggers oxidative stress, and causes protein biosynthesis dysregulation. Inhalation of lead particles is the most common route of intoxication associated with occupational exposure. This study aims to evaluate laboratory methods and biomarkers in the assessment of lead exposure. Methods: For non-experimental qualitative research, available scientific articles in English published in the relevant databases (MEDLINE and ScienceDirect) were used. The database search was performed using the keywords “Laboratory diagnostics”, “occupational exposure”, and “lead”. Results: Atomic absorption spectrometry (AAS) is the gold standard in laboratory monitoring of occupational lead exposure. Inductively coupled plasma with mass spectrometry is a commonly used method described as more sensitive than AAS due to its low detection limit. Lead concentrations can be determined in various samples, but blood and urine are the most commonly used in laboratory practice. The most important exposure biomarker is the enzyme δ-aminolevulinic acid dehydratase (ALAD) in the blood, which is characterized by progressive inactivation by lead and a negative correlation with its concentration. The concentration of urinary delta-aminolevulinic acid (δ-ALA-U) reflects the state of impaired enzyme function in heme biosynthesis. In addition, determining blood zinc protoporphyrin and urinary coproporphyrin levels significantly aids in assessing occupational lead exposure disorders. Conclusion: The availability of the laboratory methods used and the biomarker specificity and sensitivity play an important role in the adequacy of lead exposure monitoring. Accurate determination of ALAD and δ-ALA-U concentrations, along with other biomarkers, is critical for assessing individuals exposed to lead.

Introduction: Hypothyroidism is a common disorder of the endocrine system caused by insufficient biologically active hormones at the tissue level or the inability of the tissue to utilize thyroid hormones. Iron plays a crucial role in the synthesis and metabolism of thyroid hormones, and it is stored in the body as ferritin. We aimed to evaluate the correlation between serum ferritin (SF) levels and thyroid hormone panel levels in both hypothyroid and euthyroid subjects. Methods: In 2022, a matched case–control study was conducted. The study involved participants with hypothyroidism and a control group (n = 53). The levels of thyroid-stimulating hormone (TSH), free triiodothyronine (fT3), free thyroxine (fT4), and SF were measured using the chemiluminescence immunoassay on a Mindray Cl 900-i analyzer (Shenzhen Mindray Bio-Medical Electronics Co., China). Results: The hypothyroid group had TSH levels that were significantly higher (10.76 [8.54-18.76] vs. 1.76 [1.26-2.58]; p < 0.001) and SF concentrations that were significantly lower (39.08 [21.15-45.70] vs. 54.09 [41.41-71.82]; p < 0.001) compared to the control group. In both male and female subjects of the hypothyroid group, a strong negative correlation was found between SF concentration and TSH levels ([Rho = −0.855,p < 0.01]; [Rho = −0.747; p < 0.01]). In female subjects of the hypothyroid group, a weak positive correlation was found between SF concentration and fT3 (Rho = 0.488; p < 0.05). In the euthyroid group, a correlation of the same strength and direction was found for fT4 (Rho = 0.366; p < 0.05). Conclusion: Research results indicate a correlation between lower SF concentrations and hypothyroidism, which is of particular importance for understanding the etiopathogenesis, diagnosis, monitoring, and treatment modalities of patients with hypothyroidism.

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Introduction: The most important biochemical reactions of the human organism take place in the liver, and therefore it represents one of the most important organs for life. Parameters that play an important role in the diagnosis and monitoring of patients are the enzymes ALT, AST, GGT, ALP, and bilirubin. Objective: To evaluate the serum activity of enzymes and bilirubin in patients with liver cirrhosis and liver cancer. Materials and methods: The study included 120 patients aged over 50 years. Among them, 40 patients had liver cirrhosis, 40 had cancer and liver metastases, and 40 patients were apparently healthy (control group). The concentrations of AST, ALT, GGT, and ALP were determined on Abbott Architect i2000sr biochemical analyzer and Dimension analyzer. Results: The study showed that the mean values of the studied parameters were significantly higher in subjects with liver cirrhosis and cancer with liver metastases than in the control group. A statistically significant difference (p <0.05) was found in ALP and bilirubin concentrations between the studied groups. In addition, the study revealed a statistically significant difference (p <0.05) in ALT, AST, and GGT activity between subjects with cancer and the control group and subjects with cirrhosis and the control group. Conclusions: The results confirm that the activities of enzymes ALT, AST, GGT, ALP, and bilirubin were increased in subjects with cirrhosis and cancer compared to the control group.