Mild traumatic brain injury (mTBI) represents the majority of head injury presentations in emergency departments (EDs), yet only a minority of patients have acute intracranial lesions on computed tomography (CT). This leads to widespread use of unnecessary CT scans. Point-of-care (POC) biosensing, defined as analytical testing performed at or near the site of patient care, offers a promising solution to this dilemma by enabling rapid biomarker quantification to inform CT decision-making. This review aims to evaluate POC-compatible biosensing strategies for ultra-early mTBI triage, with emphasis on platforms, matrix effects, and benchmarking aligned with CT-based decision-making. Two key precedents support this approach: (1) the integration of S100B into Scandinavian Neurotrauma Committee guidelines, which has demonstrated the potential for safe reduction of CT scans, and (2) the regulatory clearance of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) testing to rule out the need for head CT in adults with suspected mTBI (Glasgow Coma Scale 13–15) when serum is collected within 12 hours of injury. Accordingly, this review focuses on the most implementable use case for mTBI, namely CT triage/rule-out. It synthesizes the current biomarker landscape (S100B, GFAP, UCH-L1), analyzes POC-suitable sensing modalities, and proposes a practical validation and benchmarking framework aligned with this intended use. A critical component is interference testing and real-world sample robustness, including vulnerabilities such as hemolysis-related elevation of UCH-L1. In conclusion, the most reliable path for biosensor translation in mTBI is to anchor development and validation to the ED CT-triage use case, emphasizing decision-point robustness and resilience to real-world sample variability over pure analytical sensitivity.

Gliomas remain a major challenge in brain cancer treatment. Although genetic mutations have been widely studied, recent research indicates that epigenetic changes, which alter gene activity without changing the DNA sequence, also contribute significantly to tumor growth and treatment resistance. This review seeks to elucidate the principal drivers and modulators of brain tumor development, emphasizing the complex interaction between tumor metabolism and epigenetic regulation. It highlights how metabolic intermediates influence chromatin structure and transcriptional events driving glioma progression. Metabolic intermediates, such as acetyl-CoA and S-adenosylmethionine, serve as essential epigenetic cofactors, directly impacting chromatin structure and gene expression. Additionally, metabolic disorders like diabetes not only frequently coexist with gliomas but also exacerbate tumor progression through mechanisms such as inflammation, oxidative stress, and epigenetic reprogramming. Tumors located near brain regions controlling heart function may also increase the risk of sudden death, particularly in diabetic patients. The review proposes a comprehensive framework to understand glioma development by linking metabolism, epigenetics, and overall health. This integrated perspective leads to novel personalized treatment approaches, targeting both the tumor and the patient’s broader metabolic health, with the potential to improve survival rates and quality of life for glioma patients.

Alpha-1 antitrypsin deficiency (AATD) is an autosomal codominant genetic disorder caused by mutations in the SERPINA1 gene. It results in reduced circulating levels of alpha-1 antitrypsin (AAT), a serine proteinase inhibitor (PI) primarily produced by hepatocytes. The most common deficient alleles are PI*S and PI*Z, with PI*ZZ homozygotes having the most severe deficiency and highest risk for lung and liver disease. While AATD is well established as a cause of early-onset emphysema and liver cirrhosis, emerging evidence suggests a potential association with the formation of arterial aneurysms. The pathophysiological rationale for this association centers on protease-antiprotease imbalance and potential extracellular matrix degradation of elastin in arterial vessel walls. Several studies have reported increased frequencies of AATD alleles in patients with abdominal aortic aneurysms and intracranial aneurysms compared to the general population, with some demonstrating statistically significant associations. Additionally, patients with the PI*ZZ genotype have been shown to have larger aortic diameters, greater aortic stiffness, and reduced distensibility compared to controls. However, the evidence is inconsistent, as several large studies have failed to demonstrate significant associations between AATD and aneurysm formation. Overall, current evidence suggests an association of AATD with the development of arterial aneurysms. However, it is also clear that the presence of AATD alone is not sufficient to increase the risk of developing new-onset arterial aneurysms.

Accurate identification of invasive fungal pathogens is crucial for appropriate antifungal therapy. The Department of Clinical Laboratory at Indus Hospital & Health Network, Karachi, Pakistan, reported two cases of invasive fungal infections between 1st January and 31st March 2024 in which conventional identification methods and automated systems produced discordant results, highlighting critical diagnostic challenges.

Two invasive yeast isolates initially showing budding yeast cells without pseudohyphae on Gram stain were subjected to conventional identification using cornmeal-Tween 80 agar, chrome agar, and BiGGY agar, followed by automated identification using the VITEK 2 ID-YST system and confirmatory API 20C AUX testing. Both isolates demonstrated typical soft, wrinkled, cream-colored colonies on Sabouraud dextrose agar, which on chrome agar appeared as dry, blue colonies and on BiGGY agar as dry, brown colonies. Characteristic arthroconidia and blastoconidia formation on cornmeal-Tween 80 agar were observed, consistent with Trichosporon species. However, the VITEK 2 ID-YST system identified both isolates as Cryptococcus laurentii with good confidence levels. India ink staining was negative for both isolates. Confirmatory API 20C AUX testing correctly identified both isolates as Trichosporon asahii (identification profile 3740734).

This discordance between automated and conventional methods underscores the continued importance of conventional identification techniques and highlights potential limitations of automated systems for certain uncommon yeasts. Laboratories should maintain proficiency in conventional methods and consider confirmatory testing when automated results conflict with morphological findings. The clinical implications of misidentification include inappropriate antifungal selection, given the different susceptibility patterns between these species.

Phenylethanoid glycosides (PhGs) are water-soluble natural compounds widely distributed in the plant kingdom, attracting significant attention from medicinal chemists due to their promising potential in pharmaceutical applications. PhGs exhibit a broad range of activities, including neuroprotective, hepatoprotective, anti-inflammatory, antioxidant, and immunomodulatory effects. This review aims to update the hepatoprotective effects of total PhG extracts and individual PhG compounds, as well as the underlying mechanisms. Additionally, we describe the structural characteristics, representative PhG compounds, and their structure–activity relationships. In brief, total PhG extracts can exert synergistic protection by reducing serum alanine aminotransferase/aspartate aminotransferase levels, suppressing oxidative stress, and attenuating inflammatory responses. Representative PhGs, including acteoside (verbascoside), echinacoside, forsythoside A (also known as forsythiaside A), and cistanoside A, protect against liver injury through modulation of the Nrf2/HO-1, NF-κB, MAPK, and TGF-β/Smad pathways, thereby regulating oxidative stress, inflammation, apoptosis, fibrosis, and lipid metabolism. Structurally, PhGs consist of a phenylethyl alcohol core, cinnamoyl residues, and glycosyl moieties. Structure–activity relationship analyses indicate that caffeoyl substitution, multiple phenolic hydroxyl groups, and optimal glycosylation patterns are key determinants of hepatoprotective efficacy.

Glioblastoma remains a highly challenging malignancy with a pronounced tendency for recurrence. The hypoxic microenvironment is a key contributor to its therapy resistance. Hyperbaric oxygen therapy (HBOT), which elevates tissue oxygen pressure and reverses hypoxia, exhibits a “dual effect” in glioblastoma management. This review aims to evaluate the therapeutic potential of HBOT in glioblastoma by examining its multifaceted effects on tumor biology and treatment response. On one hand, it enhances radiosensitivity through reactive oxygen species generation, increases chemotherapy efficacy by augmenting cytotoxicity and improving vascular perfusion, and remodels the tumor microenvironment via vessel normalization, edema reduction, and immune cell modulation. Furthermore, HBOT attenuates cancer stem cell properties by downregulating stemness markers and inhibiting self-renewal capacity. On the other hand, HBOT may also promote tumor progression: oxidative stress can induce genomic instability, while concomitant activation of HIF-, NF-κB-, and VEGF-mediated pro-survival pathways may facilitate malignant cell adaptation and proliferation. Given these opposing considerations, the clinical application of HBOT in glioblastoma management remains exploratory. In conclusion, future research should focus on optimizing HBOT protocols. In addition, exploring combination with other therapeutic approaches is equally important. These efforts are essential for the safe and effective integration of HBOT into comprehensive treatment strategies for glioblastoma.

Hashimoto’s thyroiditis (HT), an autoimmune disease with a prevalence 2–7 times higher in women than in men, is associated with daytime sleepiness. The present study aimed to test the hypothesis that thyroid function is associated with chronotype and daytime sleepiness in women with HT.

This retrospective cross-sectional study included women with confirmed HT. Demographic, clinical and laboratory data were collected. The reduced Morningness-Eveningness Questionnaire (rMEQ) and the Epworth Sleepiness Scale (ESS) were used to assess chronotype and daytime sleepiness, respectively. Based on rMEQ, women were categorized as having a morning (≥18), intermediate (12–17) or evening (≤11) chronotype. Based on ESS, women were categorized as having normal or increased daytime sleepiness.

Overall, 106 women, aged 43 ± 12 years, were included. Most had normal daytime sleepiness (68.9%), and the majority had an intermediate chronotype (61.3%), while only one had a morning chronotype (0.9%). Age was significantly associated with chronotype (P = 0.026). There was a significant association between chronotype and thyroglobulin antibodies (TgAb, P = 0.012). Free triiodothyronine (fT3) levels were significantly higher in women with an evening chronotype than in those with an intermediate chronotype (P = 0.045; OR = 0.500; 95% CI 0.25–0.98). Daytime sleepiness was significantly associated with TgAb (P = 0.016) and thyroid-stimulating hormone (TSH, P = 0.040). TgAb levels were significantly higher in women with increased daytime sleepiness (P = 0.049, OR = 1.003, 95% CI 1.00–1.01) than in those with normal daytime sleepiness.

Approximately one-third of women have an evening chronotype, and approximately one-third had increased daytime sleepiness. TgAb, fT3, and TSH are associated with daytime sleepiness or chronotype in women with HT. Further investigation is required for the underlying mechanisms.

Due to the lack of specific Western medicine therapies for post-coronavirus disease 2019 (COVID-19) syndrome in clinical practice, this study aimed to investigate the efficacy of traditional Chinese medicine (TCM) for post-COVID-19 syndrome using a cohort study design and to explore its clinical value in alleviating patients’ symptoms and improving clinical outcomes.

In this cohort study, patients were divided into two groups according to clinical treatment. The control group received conventional Western medicine, and the treatment group received additional TCM syndrome differentiation–based treatment. Propensity score matching methods were used to reduce selection bias by equating groups based on observed covariates. Clinical data, including TCM symptom scores, the Short Form 36 Health Survey, clinical efficacy, and adverse events at Day 7, were collected. The primary outcome was the efficacy rate, defined by improvement at Day 7 compared with the Day 0 score. Data were processed and analyzed using SPSS 23.0 and R 4.5.0 software.

A total of 434 patients were enrolled in the cohort, including 306 patients in the control group and 128 in the treatment group. After 1:1 matching, 94 matched pairs were analyzed. For the primary outcome, the effective rate in the treatment group was higher than that in the control group (30.8% vs. 17.2%; odds ratio (OR) = 2.17, 95% confidence interval (CI): 1.09–4.35, P = 0.003). After seven days of treatment, the TCM syndrome score improved more in the treatment group than in the control group (median difference (MD) = 2.00, 95% CI: 0.50–3.50, P = 0.009). Subgroup analyses showed generally favorable efficacy in the treatment group across subgroups, though not all reached statistical significance.

TCM syndrome differentiation–based therapy effectively relieves clinical symptoms in patients with post-COVID-19 syndrome.