Abstract: Background: Respiratory infections in critically ill patients remain a major challenge in intensive care units (ICUs), with high morbidity and mortality. Conventional microbiological methods often fail to identify the causative pathogen promptly, particularly in patients previously exposed to antibiotics. Multiplex molecular platforms, such as the BioFire FilmArray® Pneumonia Panel Plus (FAPP), allow rapid detection of multiple respiratory pathogens and resistance markers, potentially improving early therapeutic decision-making. Objectives: To evaluate the impact of implementing FAPP on antimicrobial therapeutic decisions in critically ill patients with suspected respiratory infection. Methods: We conducted a retrospective cohort study in two mixed ICUs between 2023 and 2024. All respiratory samples in which FAPP was requested were analyzed. Results were compared with conventional cultures, and changes in antimicrobial therapy following FAPP results were assessed, classified as escalation/initiation or de-escalation/discontinuation. Concordance between FAPP and culture was evaluated, and clinical and demographic variables were analyzed. Differences between groups were assessed using p-values obtained from the chi-square test or the Mann–Whitney test. Results: A total of 363 respiratory samples were included, 88.4% from mechanically ventilated patients. FAPP was positive in 65.3% of samples, whereas cultures were positive in 23.1%. Overall concordance between FAPP and culture was 57.3%. In 42.4% of cases, pathogens were detected exclusively by FAPP. Antimicrobial therapy was modified in 29.8% of patients, predominantly through de-escalation or discontinuation (69.4% of changes). Therapeutic modifications were more frequent in nosocomial infections and in patients with a positive FAPP result. Conclusions: The use of FAPP in critically ill patients with suspected respiratory infection provides rapid microbiological information that significantly influences antimicrobial decision-making, particularly by facilitating antibiotic de-escalation. Although discrepancies with conventional cultures remain and require careful clinical interpretation, FAPP represents a valuable tool for antimicrobial stewardship in the ICU setting.

Abstract: Background Pre-travel health consultations require individualised risk assessment across itinerary, destination epidemiology, traveller characteristics, vaccine history, comorbidities, medication profile, pregnancy status, immune status, activities, timing, and access to care [8,10,11]. Artificial intelligence (AI), particularly large language models (LLMs), may support pre-consultation education, structured history collection, guideline retrieval, multilingual communication, and post-consultation reinforcement, but unsafe use may introduce hallucinated, outdated, or insufficiently personalised recommendations [5,6,14,15]. Objectives This scoping review maps the current evidence on AI tools relevant to pre-travel health consultations, characterises implementation gaps, identifies patient-safety risks, and proposes a supervised implementation model for travel medicine clinics [1,28-30]. Methods The review was conducted as a scoping review using the Arksey and O'Malley framework as advanced by Levac and colleagues and operationalised through the JBI scoping review guidance, with reporting aligned to the PRISMA Extension for Scoping Reviews (PRISMA-ScR) [1,28-30]. The review was not prospectively registered. Eligibility was defined by a Population–Concept–Context (PCC) framework. Targeted retrieval was conducted in May 2026 through PubMed/MEDLINE (one direct search string), academic and web-indexed search tools, citation chasing from Journal of Travel Medicine and Travel Medicine and Infectious Disease, and authoritative guideline and regulator websites. The search date range was January 2017 to May 2026. Sources were eligible if they addressed AI or digital decision support in pre-travel health, travel medicine, travel-related clinical decision support, clinical LLM safety, or guidance defining the standard pre-travel consultation. Screening and data charting were conducted by a single reviewer using a structured eligibility checklist (Supplement S2). Results Seventy records were identified, one duplicate was removed, 69 records were screened, 12 reports were sought for retrieval, one record could not be retrieved within the search window, and 11 reports were assessed in full text and included in the synthesis. Included sources comprised four direct pre-travel AI sources, one travel-related decision-support study, four guideline and context sources, and two clinical LLM safety sources. Direct evidence is thin: the only patient-level implementation report involved 26 travellers using a GPT-4 Travel Clinic Assistant in a Singapore tertiary travel clinic, where physicians and travellers reported acceptability and workflow benefit but objective effectiveness outcomes were not measured [3]. A ChatGPT pre-travel advice evaluation found generally readable and comprehensive answers to common questions, but responses lacked sufficient personalisation to itinerary, comorbidity, vaccine history, and cost considerations [2]. Broader clinical LLM evidence indicates that evaluation methods remain heterogeneous and that LLMs may repeat or elaborate false clinical details and hallucinate clinical guidelines in simulated decision-support tasks [13,14,16]. Conclusions Current evidence supports supervised AI augmentation of pre-travel consultations but does not support autonomous AI-led vaccine selection, malaria prophylaxis, contraindication screening, or individualised travel-risk clearance [2-6,14,15,48,50]. Near-term deployment should be restricted to clinician-supervised education, structured intake, source-grounded guideline retrieval, after-visit reinforcement, and escalation-triggered workflow support [4,5,34,49]. Travel medicine specialists, clinic leaders, regulators, and digital health developers should prioritise domain-specific hallucination audits, equity testing across visiting friends and relatives, migrant, older-adult, First Nations Australian, and Pacific Islander travellers, and prospective trials reported under CONSORT-AI, SPIRIT-AI, and TRIPOD+AI standards [31-33,37,38,41-44].

Abstract: Background: Climate change is increasingly recognized as a major global health threat, with disproportionate impacts on vulnerable populations, including women living with breast cancer who are receiving palliative care. These women often experience compounded physical, psychological, and socioeconomic burdens that may be intensified by climate-related stressors such as heatwaves, flooding, and disruptions to healthcare delivery. However, there is limited evidence from low- and middle-income countries, including Ghana, on how climate change affects the palliative care continuum and quality of life (QoL) among this population. Materials and Methods: A qualitative descriptive phenomenological design was employed to explore the experiences of women with breast cancer receiving palliative care at Ho Teaching Hospital, Ghana. Fourteen participants were purposively sampled between January and March 2026. Data were collected through semi-structured in-depth interviews conducted face-to-face. Interviews were audio-recorded, transcribed verbatim, and analyzed using Graneheim and Lundman’s conventional content analysis approach. Trustworthiness was ensured through credibility, dependability, confirmability, and transferability strategies. Ethical clearance was received before data collection began (HTH-REC/EX/2026/003) Results: Four main themes and thirteen sub-themes emerged: (1) Climate-related environmental disruptions (extreme heat, flooding, and unreliable electricity supply); (2) Health-related consequences along the palliative care continuum (symptom exacerbation, treatment interruptions, and reduced care accessibility); (3) Psychosocial and economic strain (emotional distress, financial hardship, food and water insecurity); and (4) Adaptive and coping responses (spiritual coping, family support, and reliance on healthcare providers and community networks). Conclusion: The study demonstrates that climate change significantly disrupts the palliative care continuum and diminishes the quality of life of women with breast cancer through interconnected environmental, clinical, and psychosocial pathways. Strengthening climate-resilient palliative care systems, improving healthcare infrastructure, and integrating psychosocial and environmental adaptation strategies into oncology and palliative care practice are urgently needed.

Abstract: The Alliance of Bioversity International and CIAT curates the world’s largest cassava (Manihot esculenta Crantz) germplasm collection, held at its Future Seeds genebank in Cali, Colombia. Since first collection expeditions in 1969, a primary focus was to assemble and conserve the diversity from the crop’s center of origin in the American tropics. Later additions expanded representation from Asia and Africa as secondary centers of diversity. The collection consists mainly of landraces (about 5000 accessions), bred lines from CIAT (375) and from partner institutions (253), and related wild Manihot (377 accessions from 23 species or subspecies). Secure conservation, first as a field collection and then in a slow-growth in vitro system, gave priority to pathogen testing and methods to assure successful clonal propagation over many generations. Cryopreservation research is ongoing to achieve additional security and efficiency. CIAT extensively characterized accessions through morphological, biochemical and molecular criteria. As a core goal, the collection has been a foundation for genetic improvement of the crop globally. The paper provides perspectives on the future management and use of the collection in the context of the recently established Future Seeds genebank facilities at CIAT, and new tools and technologies that support more effective conservation, evaluation and use.

Abstract: Bestrophin-1 (BEST1) was first linked to retinal disease, yet in the central nervous system BEST1 has been assigned a distinct functional scope spanning transmitter permeation, circuit set point control, and injury responses. In this mini-review, current evidence is examined for BEST1 as a neurotransmitter-gated anion channel, with emphasis placed on structural and biophysical studies that have clarified gating, pore behavior, and ligand-dependent tuning. The long-running dispute over CNS localization is critically revisited, because broad conclusions have often rested on antibodies lacking stringent validation. Astrocytic BEST1 is then considered in the setting of tonic inhibition, where regulated GABA flux has been linked to sensory coding, network excitability, and behavior across circuits. Its contribution to ischemic pathology is also assessed, with attention given to the timing-dependent shift from acute injury mechanisms to post-stroke recovery windows. Finally, emerging evidence for BEST1 in microglia and neurons is weighed cautiously and framed as a tractable agenda for direct testing. A more rigorous BEST1 field is argued to depend on cell-type-resolved genetics, validated localization pipelines, and temporally precise intervention studies.

Abstract: Inspired by the holographic theory of gravity originating from the microscopic degrees of freedom of black holes, as well as the profound connection between quantum entanglement and space-time revealed by the AdS/CFT correspondence, this paper attempts to establish a connection among quantum measurement, quantum entanglement, and space-time, thereby proposing a "Multi-Space-Time" scheme. Under this scheme, the "problem of the preferred basis" and the "problem of definite outcomes" in quantum measurement can be solved simultaneously. Furthermore, it reveals that classical space-time originates from quantum measurement. However, a derived result of this scheme is that the number of classical space-times in the universe is not unique; rather, there may exist a multitude of them. The "Multi-Space-Time" scheme demotes measuring instruments or observers to a status of parity, establishing an egalitarian relationship between the measured system and the measuring instrument. Nevertheless, the proposal remains largely a conceptual or epistemic framework at present, and its verification relies on the establishment of quantum gravity. Yet, it provides a potential direction for future quantum gravity research when dealing with classical space-time, quantum measurement, and quantum entanglement simultaneously.

Abstract: Breast cancer surgical management encompasses a spectrum of options that extend beyond oncologic control and carry substantially different cumulative surgical burdens. Although breast-conserving therapy (BCT) and mastectomy offer equivalent survival outcomes in many clinical scenarios, the downstream implications of these choices, including the number of operations, complication profiles, recovery timelines, and need for revision, are often underrecognized during initial treatment planning. This review aims to provide non–plastic surgeons with a practical framework for understanding the surgical burden associated with BCT compared with mastectomy and, when mastectomy is selected, the implications of subsequent reconstructive pathways. By discussing breast cancer surgery through the lens of cumulative surgical burden rather than isolated procedural choices, this review seeks to support more informed, multidisciplinary counseling and shared decision-making. A clearer understanding of reconstructive trajectories may help align surgical recommendations with patient values, optimize expectations, and reduce unanticipated downstream interventions across the continuum of breast cancer care.

Abstract: Background: Aerobic vaginitis (AV) is characterized by dysbiotic vaginal microflora with overgrowth of aerobic pathogens of enteric origin, presence of vaginal inflammation and immature epithelial cells. This study aimed to evaluate, over a period of 10 years, women of reproductive age (non-pregnant and pregnant) as well as menopausal women affected by AV. Methods: We included non-pregnant, pregnant and menopausal women diagnosed with AV over a period of 10 years. Diagnosis of AV was determined according to the criteria proposed by Donders in 2002. The isolated pathogens were identified with the rapid identification system I-dOne (Alifax S.r.l, Polverara, Italy) and the automated system VITEK2 (Biomerieux, Marcy l’Etoile, France), which was used for antimicrobial susceptibility testing. Results: The overall aerobic vaginitis prevalence rate during the studied period was 9.5%. The most common isolated pathogens were Escherichia coli 27.3%, Enterococcus faecalis 25.0%, Streptococcus agalactiae 22.2%, Klebsiella pneumoniae 8.9%, Proteus spp 4.7%, Staphylococcus aureus 3.5%. E. coli infection significantly increased the odds of mild AV by 1.65 times (p=0.002) and Proteus species infection was over 6 times more likely to progress to severe disease (p=0.000). Furthermore, pregnant women were more likely to be infected with E. faecalis (p=0.000) while menopausal women were diagnosed significantly more with severe AV (p=0.000) compared to the other groups. Conclusions: The prevalence of aerobic vaginitis in the population studied was in concordance to global rates. Menopausal women displayed significantly more severe AV cases while, in contrast, mild cases were recorded during pregnancy. The most commonly isolated pathogens were of enteric origin.

Abstract: In this work, we extracted silk fibroin (SF) by a tertiary solvent system (CaCl2:Ethanol:H2O), and then blended with chitosan (CS) solution to construct microparticles using the water−in−oil−emulsion−diffusion method. The mixture of SF/CS solution aqueous phase; W) was prepared at ratios of 4:0, 3:1, 1:1, 1:3, and 0:4, using ethyl acetate as the oil phase (O). After the microparticles were prepared, their morphology was examined using scanning electron microscopy (SEM). The results indicated that the optimal preparation conditions were a 1% (w/v) aqueous phase with a volume of 1 milliliter, 100 milliliters of oil phase, and a stirring speed of 700 rpm. The average microparticle size was 50−100 micrometers.ATR−FTIR spectra showed unique functional groups of SF and CS, as well as interactions between the two polymers. The results of the thermal property study using a TGA instrument showed that SF microparticles had a higher maximum decomposition temperature (Td, max) than chitosan, and the blended microparticles' Td, max increased with the proportion of SF. Most microparticles exhibited a semi-crystalline polymer structure, with SF microparticles being the most hydrophobic, followed by blended microparticles and CS, respectively. Testing for absorption capacity, the SF microparticles were more effective at absorbing used engine oil than vegetable oil and chloroform, while CS microparticles showed the highest capacity for vegetable oil.The experimental results indicated that all SF/CS blended particles played an efficiency of absorption variable by ratios of SF or CS blended. This suggested that the prepared microparticles might be useful for oil/water separation application.

Abstract: Extracellular cold-inducible RNA-binding protein (eCIRBP) is a key driver of sterile inflammation following ischemia/reperfusion (I/R) injury, such as during cardiac surgery. While eCIRBP’s interaction with the TLR4/MD2 complex is known to activate the NF-κB pathway, its role in activating the JAK/STAT3 pathway via the IL-6 receptor (IL-6R) is less understood. To investigate this, human THP-1-derived macrophage-like cells were stimu-lated with a recombinant human active peptide to CIRBP (rhCIRBP) with or without Stattic pre-treatment, a selective STAT3 phosphorylation (Y705) inhibitor. Activation of NF-κB and STAT3 was assessed by Western blotting, while gene expression of inflammatory markers (IL-6, IL-1β, TNF-α, MCP-1, ICAM, and SOCS3) was measured via RT-qPCR. We observed rhCIRBP stimulation significantly activated both signaling pathways, resulting in increased inflammatory gene expression. Notably, STAT3 inhibition with Stattic sup-pressed these effects, indicating STAT3’s critical role in eCIRBP-driven inflammation. Our findings confirm eCIRBP as a potent inflammatory mediator, corresponding with reported elevated concentrations of circulatory eCIRBP in patients after cardiac surgery and those suffering from hemorrhagic shock and sepsis. Additionally, targeting eCIRBP-induced ac-tivation of NF-κB and STAT3 may offer a novel therapeutic strategy for managing I/R-induced inflammation.

Abstract: Medicinal plants grown outside their native forest habitat may produce phytochemical profiles that differ from wild-harvested material, yet the ecological mechanisms underlying these differences remain poorly synthesized across disciplines. This review proposes that the forest understory functions as a multi-signal elicitation system in which canopy light filtering, arbuscular mycorrhizal fungi (AMF), and above-ground biotic interactions collectively shape secondary metabolite profiles. AMF-mediated induced systemic resistance and above-ground biotic interactions operate through confirmed jasmonate-mediated pathways. Sunfleck-driven reactive oxygen species signaling is hypothesized but untested, and the red-to-far-red ratio modulated phytochrome B pathway characterized in Arabidopsis remains unconfirmed in shade-tolerant species. Using three saponin-rich herbs (Panax vietnamensis, P. ginseng/P. quinquefolius, and Paris polyphylla) as case studies, we formalize this as a testable chemical terroir hypothesis with three falsifiable predictions. We also translate it into an ecological co-cultivation design principle with three production levels and a two-step operational framework, and identify priority experiments, analytical methods, and implementation challenges needed for validation. These contributions bridge forest ecology and medicinal plant science while identifying critical evidence gaps requiring resolution before field implementation.

Abstract: This study aimed to compare the levels of sialic acid (SA) in saliva during pregnancy between groups of women with preeclampsia (PE) without severity criteria and with severity criteria. 60 pregnant women diagnosed with PE were studied in total. The patients were divided into two groups: 30 women with PE without severity criteria (PEOS) and 30 women with PE diagnosis with severity criteria (PEWS). Salivary SA levels were determined using surface-enhanced Raman spectroscopy (SERS), and citrate-covered silver nanoparticles as an amplifying substrate. The mean SA concentrations of PEOS and PEWS patients were 34 ± 15.6 vs 75 ± 22 mg/dL, respectively. Participants with severity criteria had more than twice the median SA levels as those without severity criteria, as determined by the SERS-calibrated technique. Our results indicate that SA determination from saliva using SERS may become a very effective, rapid, and cost-effective diagnostic tool for PE severity.

Abstract: With contemporary social movements related to civil rights, personal freedoms, and tensions in higher education institutions around academic freedom, ideological open-mindedness has become an increasingly popular research topic in recent decades. Such openness has been defined as a disposition to engage meaningfully with novel ideas that may conflict with one’s own, and to accommodate or disregard such views with delicacy, precision, and care (Cormier et al., 2026; Kwong, 2023). Findings on effective interventions to reduce ideological polarization remain limited, highlighting the need for a cohesive review. This review catalogued and analyzed findings on individual differences related to ideological open-mindedness through an exploratory research question: Are there measured individual differences (psychological and demographic variables such as personality traits, political beliefs, and gender) that relate meaningfully to ideological open-mindedness? The search process retained 152 records. Results showed associations between ideological open-mindedness and personality traits, age, gender, sexual orientation, culture, language, political standing, socioeconomic status, religious beliefs, education level and type, personal past experience, competence, personal beliefs and interests, and emotional tendencies. Considering varied associations between individual characteristics and differences in ideological open-mindedness, this review serves as a guide towards better understanding this complex construct as precursor to informing effective interventions.

Abstract: The escalating global crisis of water scarcity, exacerbated by the increasing prevalence of heavy metal contamination from anthropogenic activities, necessitates the development of innovative and sustainable remediation technologies. Recognizing the inherent metal-binding capabilities of Cannabis sativa L. (hemp), this study introduces a novel approach for copper(II) ion removal from aqueous solutions. We investigated the synergistic potential of combining hemp-derived cannabinoids with chitosan-polyvinyl alcohol (PVA) hydrogels to create a bio-based adsorbent. Hemp oil, rich in cannabinoids, was incorporated into chitosan-PVA hydrogels synthesized to enhance mechanical stability. The resulting hemp hydrogels (HHGs) were characterized using Fourier Transform Infrared Spectroscopy (FTIR), confirming the integration of the oil within the hydrogel matrix. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) analysis of copper-contaminated solutions treated with HHGs over 24 hours demonstrated a reduction in copper ion concentration, suggesting a biosorption mechanism. Swelling studies revealed an inverse relationship between hemp oil content and water uptake capacity. Thermal studies showed excellent stability amongst gel types. This work establishes the feasibility of utilizing hemp-modified hydrogels as a promising avenue for heavy metal removal, paving the way for future optimization of these bio-composites in both drinking water purification and industrial wastewater treatment applications.

Abstract: Geochemical anomaly detection plays a critical role in mineral exploration, yet conven-tional methods are often limited by compositional effects, sensitivity to outliers, and in-sufficient consideration of spatial relationships. To address these issues, this study pro-poses an integrated analytical framework that combines compositional data analysis and spatial statistics for robust geochemical anomaly identification. The framework incor-porates isometric log-ratio (ILR) transformation to eliminate the closure effect, robust principal component analysis (RPCA) to extract stable geochemical patterns, local indi-cators of spatial association (LISA) to characterize spatial clustering, and compositional balance analysis (CoBA) to enhance anomaly signals. The method is applied to the Barkol Lake area in the Eastern Tianshan, a key metallogenic belt within the Central Asian Orogenic Belt. The results reveal significant geochemical anomalies characterized by Cu-associated element assemblages (e.g., Cu–Ni–Cr), which are spatially correlated with major fault zones and volcanic–intrusive complexes. The identified anomalies show strong consistency with known mineral occurrences and delineate several prospective targets for copper polymetallic mineralization. Compared with conventional approaches, the proposed framework demonstrates improved robustness to outliers, enhanced sensi-tivity to weak anomalies, and better integration of compositional and spatial constraints. These advantages highlight its effectiveness for geochemical anomaly detection and mineral prospectivity mapping in complex geological settings.

Abstract: Sweet potato (Ipomoea batatas L.) is a key food security crop in the developing world. Its production is, however, constrained by low-quality, virus-infected planting material derived from conventional vegetative propagation. In this study, we developed an efficient and reproducible in vitro micropropagation protocol for the orange-fleshed sweet potato cv. ‘Kulfo’. Nodal and apical shoot explants were cultured on Murashige and Skoog (MS) medium containing different combinations of 6-benzylaminopurine (BAP), naphthalene acetic acid (NAA), and gibberellic acid (GA₃) for shoot initiation and multiplication, and indole-3-butyric acid (IBA) and NAA for rooting. The maximum shoot regeneration was achieved (62% from nodal and 59% from apical explants) on MS medium supplemented with 0.5 mg L⁻¹ BAP and 0.1 mg L⁻¹ GA₃. MS medium supplemented with 1.0 mg L⁻¹ BAP and 0.1 mg L⁻¹ NAA produced a mean of 7.2 shoots per explant per subculture with vigorous growth during the shoot multiplication stage. Half-strength MS medium supplemented with 0.1 mg L⁻¹ IBA and 0.1 mg L⁻¹ NAA was the best rooting medium. The acclimatized plantlets from the optimal treatment showed a 98.2% survival rate in the greenhouse. The optimized cultivar-specific protocol provides a reliable system for the mass production of high-quality, orange-fleshed sweet potato planting material to support food security, genetic improvement, and germplasm conservation.

Abstract: Wearable electronic textiles (e-textiles) are increasingly being explored for healthcare, sports, military, and smart wearable applications, creating a growing demand for sustainable and flexible energy harvesting systems. In this study, a cost-effective and ultra-flexible textile-assisted thermoelectric generator (TEG) was developed using recycled electronic and textile waste materials. Discarded copper and aluminum foils recovered from electronic waste were integrated into a recycled woven fabric composed of 70% cotton, 28% polyester, and 2% elastane to fabricate the wearable thermoelectric device. The fabricated system demonstrated a measurable thermoelectric response, producing a maximum output voltage of 180.75 mV under a temperature difference (ΔT) of 5.82 K. The results demonstrate the feasibility of utilizing waste-derived conductive materials and recycled textiles for flexible thermoelectric energy harvesting applications. In addition to its lightweight and wearable structure, the developed device highlights the potential of sustainable smart textile systems for low-power wearable electronics and self-powered sensing applications. This work contributes to the advancement of environmentally sustainable smart textiles by combining waste reutilization, wearable energy harvesting, and flexible electronic integration within a single textile platform. Future research may focus on improving thermal contact efficiency, long-term durability, output stability, and scalable fabrication strategies for practical wearable energy harvesting applications.

Abstract: Background: As the society ages, the number of patients with early cognitive impairment that can progress to Alzheimer’s disease also increases. Early diagnosis and risk as-sessment allows effectively initiate the necessary lifestyle changes and monitoring. The use of artificial intelligence (AI), when analyzing medical histories, enables more pro-ductive evaluation of large datasets and identify patterns that may go unnoticed in clinical practice. This kind of approach can improve early screening, reduce physicians’ workload and develop bigger support for personalized treatment. The aim of the study: To compare the performance of machine learning (ML) algorithm with a physician (neurologist) in assessing patient’s subjective cognitive decline and Alz-heimer’s disease risk in early stages. Research methods: The research was designed as a retrospective, comparative cohort study that used two data sources. Firstly, the National Alzheimer’s Coordination Center (NACC) longitudinal dataset to train the ML model. Secondly, medical records gathered from Pauls Stradins Clinical University Hospital dating from 2020 till May 2025 to evaluate the al-gorithm’s precision. Results: The research included 154 patients, predominantly women (68.8%), with a mean age of 80.3 years. Class distribution consisted of dementia (n=139); mild cognitive im-pairment (MCI) (n=13); subjective cognitive decline (SCD) (n=2). Dementia was identified the best – 128/139 (accuracy – 92.1%) with errors tending towards MCI. MCI was correct in 9/13 cases (accuracy – 69.2%) All SCD cases were classified as dementia. Overall model’s accuracy was 91.6% (141/154). Conclusions: ML algorithm can match to neurologist made diagnoses with high precision but is struggles to separate adjacent early-stage diagnoses. At this moment, ML models are great decision supporters, but no yet alone diagnosticians. Nevertheless, this technology has high potential to being integrated in the future to aid triage and early screening, especially when advanced diagnostics are limited.

Abstract: Two geometrical problems of negative time metric and abuse of distance factors for angular coordinates and other two physical problems of revisit redshift and covariant acceleration were put forward to investigate the traditional frames of general relativity. It is found that sub-indexes of Christoffel symbols in gravitational fields are not really alterable. The concept of trajectory derivative was carried out to clarify the derivatives on motion trajectories which perform far from field derivatives. Calculations on trajectory derivatives of frequency shift and acceleration lead to conclusions that light speed keeps general covariance in gravitational fields but light energy momentum would not, may as well, the motions of massive matters in gravitational fields do not perform general covariance thoroughly. The conservativeness of light angular momentum has been discovered in most surprising forms, as well as that of massive matters. Renovated kinematic equations for light ray propagations and massive matter motions have been carried out that forcefully impact the traditional methodologies on solutions of trajectory and time spending. Dynamic models of fluid planet rings were founded to interpret the evolutions of accretions of quasars and active galactic nuclei. Consequently, the mechanism of relativistic release was raised up based on light speed covariance and energy conservation, although it has not been completely proved. But the equations on relativistic release and relativistic frequency shifts so far as the line widths of emission and absorption could be astonishingly verified in observations, especially on the predictions of the broad line regions and narrow line regions. It could be imagined that the spectrums of relativistic emission and absorption may have been involved with fantastic mystery of matter’s intrinsic structures that we know less.

Abstract: Background: Hepatocellular carcinoma (HCC) is one of the most common and deadliest cancers worldwide. Alpha-fetoprotein (AFP), a widely used and accessible tumoral marker, has limited performance in the early detection of HCC among high-risk populations. This study aims to evaluate the potential added value of ccfDNA (circulating cell-free DNA), alone or in combination with AFP, using accessible, feasible ccfDNA analysis. Methods: A prospective cohort of 125 patients with chronic liver disease was analyzed. Patients with incomplete clinical or laboratory data and patients without cirrhosis were excluded from the final analysis. Nonparametric tests, logistic regression and ROC curve analysis were performed. ccfDNA concentration was assessed by fluorimetry and fragment size was measured using on-chip electrophoresis. Results: ccfDNA fragment size was significantly lower in the cirrhosis-HCC subgroup compared to the cirrhosis-only subgroup (p< 0.001). While AFP remains an independent predictor of HCC among cirrhosis patients, ccfDNA fragment size did not prove to be an independent predictor in this cohort. However, AUROC (Area Under the Receiver Operating Characteristic Curve) analysis revealed that a combined model of AFP and ccfDNA fragment size showed modest additional discriminatory value between the two groups, compared to either ccfDNA peak size or AFP alone. Conclusions: ccfDNA fragment size may provide modest complementary value within multimarker panels. However, the marker needs further validation in a larger cohort, and adequate assessment of potential confounders such as severity of liver dysfunction and age.