Life

Abstract Background: Acute Lymphoblastic Leukemia (ALL) is a highly heterogeneous pediatric malignancy. Despite high survival rates, relapse and the involvement of central nervous system (CNS) remains a significant clinical challenge. Traditional clinical parameters often lack the precision required for early detection and risk stratification. This study utilizes high-throughput proteomics and machine learning to identify molecular signatures in cerebrospinal fluid (CSF) that characterize disease effect and treatment response. Methods: 82 CSF samples from 41 pediatric ALL patients at diagnosis (VD) and remission (VR) were analyzed. Proteomic profiling of 276 proteins was performed using Olink Proximity Extension Assay. Differentially abundant proteins were identified (q-value< 0.05, |Log_2FC| > 0.5) using the Wilcoxon rank-sum test. Three machine-learning algorithms - Random Forest, LASSO, and SVM-RFE - were integrated to select the differentially abundant proteins in VR and VD and between CNS involvement levels. To validate the data Pan-Cancer Atlas analysis was done using two different platforms. Results: In the remission phase, we observed significant alterations in the expression of key proteins compared to diagnosis, with ADGRG1 and KYNU showing a marked increase, while CCL17, CD5, CD27, CXCL9, CXCL11, FASLG, GZMA, and TNFRSF9 were significantly downregulated. Furthermore, our analysis identified distinct protein signatures associated with CNS involvement: CCL4, CTSC, CXCL10, CXCL9, and MMP7 were differentially abundant at the VD stage, whereas CAIX, CASP-8, HAGH, CXCL9, MMP7, MCP-2, and VWC2 at the VR stage. Conclusion: Integrating Olink proteomics with machine learning identified molecular signatures in ALL that have the potential to be further developed to a biomarker panel for monitoring treatment response and guiding personalized therapeutic strategies shifting the focus toward the Precision One Health approaches.

Emerin (EMD), an inner nuclear membrane protein essential for nuclear architecture integrity, gene expression, cellular signaling, and chromatin stability, interacts with the LINC complex and participates in cytoskeleton-nucleoskeleton communication by binding to nuclear actin filaments. EMD is implicated in migration, invasion, and metastasis in some tumors, but its role in glioblastoma (GBM) remains unclear. This study evaluated the effects of EMD knockdown and overexpression in GBM cell lines following genotoxic treatment with cisplatin. In both wild-type p53 (U87-MG) and mutant p53 (U138-MG) GBM cells, EMD expression is high, and cisplatin treatment did not affect these protein levels. EMD knockdown in U87-MG cells significantly increased cisplatin IC50, viability, and proliferation. Conversely, stable overexpression of EMD in U87-MG cells led to reduced cisplatin IC50, viability, proliferation, and migration. EMD knockdown or overexpression did not affect any U138-MG phenotypes, with or without cisplatin treatment. Modulation of EMD levels causes morphological changes in stress fiber cytoskeleton, whereas overexpression of EMD in U87-MG cells promotes an increase and a decrease in nuclear and cytoplasmic actin levels, respectively. These biological responses of U87-MG cells overexpressing EMD were coincidentally associated with alterations in the levels of pH2AX(Ser139), p-p53(Ser15), p53, and p21Kip1 proteins after cisplatin exposure. In sum, modulation of EMD levels affects the viability, migration, and proliferation of wild-type p53 GBM cells treated with cisplatin, suggesting unknown roles in the DNA damage response and repair. This work highlights EMD as a potential regulator of GBM chemoresistance and a target for therapeutic intervention.

Background: Immunochemotherapy (ICT) is considered standard in regards to care for small-cell lung cancer (SCLC) in extensive stages, yet reliable biomarkers for treatment response remain elusive. While previous univariate analyses suggest specific peripheral lymphocyte subsets correlate with survival, the systemic immune response involves complex, multivariate interactions that require advanced analytical approaches. Methods: This paper analysed high-dimensional flow cytometry data from 32 patients with stage IV SCLC treated with carboplatin, etoposide, and atezolizumab. Peripheral blood was analysed at baseline (V0) and longitudinally during treatment. To identify potential early predictive biomarkers and mitigate sample attrition in later cycles, we focused on baseline and measurements after two cycles of ICT (V1). We employed a rigorous machine learning framework utilising nested cross-validation, bootstrapping, and permutation-based statistical testing to evaluate eleven different regression and survival models. Results: Under model-appropriate metrics, regressors did not generalise (R2 <0); conversely, censoring-aware Random Survival Forests (RSF) successfully extracted robust prognostic signatures. Baseline immune profiles (V0) achieved a concordance index (C-index) of 0.66 (p= 0.015), while dynamic changes from V0 to V1 ({triangleup}V) achieved a C-index of 0.65 (p= 0.022). Crucially, absolute values measured after two cycles of ICT (V1) yielded no significant signal (p= 0.445). Feature importance analysis confirmed the prognostic value of Th17 normalisation and identified Naive Regulatory T cells and Memory B cells as candidate components. Conclusion: Machine learning validation confirms a predictive signal in the peripheral immune profile of SCLC patients. Early dynamic shifts in the balance between regulatory and effector immune arms are associated with prognosis, contrasting with the lack of signal in absolute counts after two cycles of ICT. These findings establish a proof of concept for multivariate liquid biopsy immune profiling, warranting confirmation in larger cohorts and highlighting the necessity of integrating systemic and tumour-intrinsic data.

IntroductionTo investigate the effects of chronic hypoxic exposure simulating heavy-industrial environments on the viability, metabolic activity, stemness preservation, and osteogenic differentiation potential of human dental pulp stem cells (hDPSCs). MethodsCommercially available hDPSCs were cultured under controlled oxygen tensions representing surface atmospheric conditions (21% O2), moderate hypoxia (10% O2), deep hypoxia (5% O2), and severe hypoxia (1% O2). Cells were maintained for 1, 3, and 7 days. Cell viability was evaluated using MTT and Live/Dead assays. Reactive oxygen species (ROS) accumulation, mitochondrial membrane potential, and apoptosis were assessed using fluorescent probes and Annexin V/PI staining. Stemness marker expression (SOX2, OCT4, NANOG) and osteogenic markers (RUNX2, ALP, OCN) were analyzed via RT-qPCR. ResultsModerate hypoxia (10% O2) promoted transient increases in stemness marker expression and preserved metabolic activity. Severe hypoxia (1% O2) significantly reduced cell viability, increased ROS accumulation, disrupted mitochondrial integrity, and elevated apoptotic cell populations after prolonged exposure (p < 0.05). Osteogenic differentiation markers were significantly downregulated under severe hypoxic conditions. ConclusionsIndustrial hypoxic environments critically influence pulpal stem cell physiology and regenerative potential. While moderate oxygen reduction may transiently preserve stemness characteristics, chronic severe hypoxia impairs viability and osteogenic functionality. Chronic low-oxygen occupational environments may alter endogenous dental regenerative mechanisms and influence oral tissue healing responses.

BackgroundiPSCs generated from healthy individuals constitute an important control resource for disease modelling applications but existing biobanks are highly skewed towards populations of European ancestry while well characterized control lines from Indian populations remain limited. Given the extensive genetic diversity of the Indian subcontinent, the availability of ethnically relevant healthy control lines is important for developing accurate disease models and reducing population specific confounding effects. MethodologyWe used peripheral blood mononuclear cells (PBMNCs) of a healthy female donor of Eastern Indian origin for the generation a wild type iPSC line using non-integrating episomal reprogramming vectors. Established colonies were expanded and characterized through morphological assessment, expression of pluripotency and trilineage markers, episomal vector clearance analysis, and chromosomal stability evaluation and mycoplasma contamination analysis. ResultsThe line generated exhibited characteristic pluripotent stem cell morphology and also showed strong expression of pluripotency markers, was free from any contamination and free from the reprogramming vectors confirming an integration free system. The cells maintained a normal diploidy number during characterization. Expression of lineage specific markers associated with ectoderm, mesoderm and endoderm confirmed the developed iPSCs functional capacity to undergo trilineage differentiation. ConclusionWe have developed and validated an iPSC line from an underrepresented Indian population. This well characterized, ethnicity specific iPSC line provides a valuable cell line for establishing a high quality, well characterized control baseline, which is a major missing element in South Asian stem cell repositories and thus will provide a solid foundation for future disease specific modelling and screening.

AnnotationMitochondrial heteroplasmy --the coexistence of both wild-type and mutant copies of mitochondrial DNA (mtDNA) within a cell--is a key factor in the pathogenesis of mitochondrial diseases. Classical approaches, which rely solely on the scalar fraction of mutant DNA, fail to fully account for threshold effects, the stochastic nature of heteroplasmy dynamics, and tissue specificity. The aim of the work is to construct a complex stochastic model of heteroplasmy dynamics, which for the first time combines the effects of selection, genetic drift, migration of mitochondrial genomes between tissues and threshold mechanisms of pathology development, for a quantitative assessment of the risk of mitochondrial diseases. In this paper, we propose a complex-phase formalism in which the state of a cells mitochondrial genome is described by a complex number Z = a + ib, where a and b are the absolute numbers of normal and mutant mtDNA copies, respectively. This approach naturally combines information on copy number and heteroplasmy level, and the argument{phi} = arctan (b / a) is interpreted as a phase characterizing the mutant load. Based on this formalism, we developed a stochastic model of tissue dynamics that includes the processes of selection, genetic drift, and intertissue migration of mitochondrial genomes. Using Monte Carlo methods (1000 simulations), we demonstrated that neuronal tissues are characterized by high heteroplasmy variability and a significant probability of reaching a pathological threshold even with a relatively low systemic mutant load. Kaplan-Meier survival analysis demonstrates that the development of pathology is probabilistic and can be described as a time -to-event process . The proposed approach enables quantitative assessment of the individual risk of developing mitochondrial diseases and opens the door to personalized prognosis.

Cancer, one of the worlds leading causes of death, is characterized by a complex metabolic reprogramming that features the Warburg effect as one of its hallmarks. The Warburg effect involves increased glucose and amino acid metabolism, which promotes tumor proliferation and progression. Although cancer has historically been attributed to genetic mutations, recent studies suggest a possible metabolic origin. However, a key characteristic of cancer cells is their greater adaptability than normal cells, as evidenced by their resistance to chemotherapy, which stems from their high mutability. This underscores the need to examine the relationship between metabolic reprogramming and cancer development from both metabolic and evolutionary perspectives. In this context, Saccharomyces cerevisiae snf1{Delta} strain has emerged as an ideal cellular model for studying the Warburg effect. This study aimed to determine whether deletion of the SNF1 gene in S. cerevisiae affects its chronological aging and competitiveness in a glucose and amino acid-dependent manner. Herein, we provide evidence that the snf1{Delta} strain changes the chronological aging depending on nutrimental condition, under low-nutrient levels shortens (0.1% glucose + 0.1x amino acids), and increases under high-nutrient levels (5% glucose + 3x amino acids). Competitiveness of the snf1{Delta} strain in co-cultivation with wild-type was also improved in 5% glucose + 3x amino acids, by approximately 2 Log10. These results indicate that snf1{Delta} strain aging and competitiveness are also sensitive to nutrimental status, as was observed in cancer cells.

We present our Stage-1 Registered Report as a full clinical trial article with all methods in past tense and including mock results, table and figures for the primary analysis. To remind the reader that this Stage-1 article is written before data collection, we highlight in color that these mock results are only for illustrative purposes and will be replaced by the actual results in the Stage-2 Registered Report. Background In patients experiencing out-of-hospital cardiac arrest, optimization of oxygen delivery during cardiopulmonary resuscitation is a critical. Although both positive end-expiratory pressure (PEEP) and zero end-expiratory pressure (ZEEP) are employed during CPR, their respective impacts on clinically relevant outcomes is yet to be clearly established. Methods This investigator-initiated, pragmatic, registry-based, multicenter, triple-blind randomized controlled superiority trial evaluates whether applying 8 cm H2O PEEP during cardiopulmonary resuscitation improves outcomes compared with ZEEP in adults with non-traumatic, non-drowning out-of-hospital cardiac arrest. Pre-randomized CPR kits (1:1 PEEP vs. sham) were used by ambulance sites during manual ventilation throughout the resuscitation process. The primary analysis was conducted in the principal stratum of patients who received either a supraglottic airway or endotracheal tube. The primary outcome was neurological status at hospital discharge measured by a utility-weighted score on the modified Rankin Scale. Secondary outcomes included prehospital return of spontaneous circulation, 30-day survival, and 6-month quality of life. The primary safety outcome was clinically significant pneumothorax.

A key scientific challenge is to develop a universal theory of life that integrates our biological knowledge with fundamental logical principles. We propose that a "five nodes" principle may govern the origin of life and consistently exist hierarchically within living systems. In our investigation, we explored autocatalytic chemical reaction networks (CRNs) as potential origins for methanotrophy and anoxygenic phototrophy, aiming to validate the "five nodes" principle in the emergence of autopoietic systems. Our research revealed the emergence of autocatalytic peptides and weakly reversible realizations within the MSA reaction network (composed of CH4, SO42-/SO32-, and NH4+) as well as in the light-Sammox (sulfurous reduction coupled to anaerobic ammonium oxidation)-driven CRN (composed of HCO3-, SO32-, and NH4+) under hydrothermal conditions. Furthermore, we identified the possible emergence of three main interdependent components essential for life within the two reaction networks: membrane compartments, peptide nucleic acids (PNA) backbones, and catalytic capacities for energy release reactions. Our findings suggest that non-equilibrium synergy of five bioessential elements (NESFBE) can facilitate proto-energy and material metabolism, thereby enabling diverse scenarios for lifes origin. Importantly, our discovery indicates linear constraints present in these CRNs that contributed to lifes inception, which is the mathematical foundation of the "five nodes" principle. Linear constraints determine both the emergence and self-disintegration of autopoietic systems. We infer a period five existence based on hierarchical structures found within autopoietic systems, and "period five indicates autopoiesis" could be one of universal theory of life.

Background: The tumor microenvironment (TME) plays a critical role in cancer progression and treatment response. Stromal components, including cancer-associated fibroblasts (CAFs), extracellular matrix (ECM), and angiogenesis, contribute to tumor aggressiveness. However, a comprehensive stromal activity score integrating multiple stromal dimensions for pan-cancer prognosis prediction is lacking. Methods: We developed a Stromal Activity Score (SAS) integrating five stromal dimensions: CAF signature (12 genes), ECM remodeling (15 genes), TGF-{beta} signaling (13 genes), angiogenesis (12 genes), and complement activation (11 genes). SAS was calculated using single-sample Gene Set Enrichment Analysis (ssGSEA) on TCGA pan-cancer data comprising 1,303 samples across 12 cancer types. Prognostic value was evaluated using Kaplan-Meier analysis and Cox regression. Immunotherapy response prediction was validated in two independent cohorts (IMvigor210, n=88; Liu2019, n=105). Results: Pan-cancer Cox regression demonstrated a significant association between SAS and overall survival (HR = 1.165, 95% CI: 1.065-1.275, P = 0.001). Per-cancer analysis identified BRCA (HR = 1.942, P = 0.022), STAD (HR = 1.684, P = 0.024), and LUSC (HR = 1.552, P = 0.038) as significant, though none survived FDR correction. SAS correlated strongly with ESTIMATE Stromal Score (Spearman {rho} = 0.835) and moderately with Immune Score ({rho} = 0.396). Immunotherapy validation showed consistent trends (IMvigor210: AUC = 0.602; Liu2019: AUC = 0.617). Time-dependent ROC analysis showed 1-year AUC = 0.596, 3-year = 0.579, 5-year = 0.559. Leave-one-out analysis identified angiogenesis removal as enhancing prognostic signal (HR = 3.737, P = 0.0002). Three distinct TME subtypes were identified with differential SAS profiles. Conclusions: SAS is a novel pan-cancer stromal activity score that captures TME biology with strong construct validity. Its clinical utility as a standalone biomarker remains modest, but it may complement existing immunotherapy biomarkers.

ObjectiveIn recent years, the number of cats kept as companion animals has increased, leading to a growing demand for veterinary care. Although some histone deacetylase (HDAC) inhibitors are promising for the treatment of human cancers and neurological diseases, comprehensive systematic research on HDAC inhibitors in domestic cats remains insufficient. Therefore, this study aimed to investigate the effects of HDAC inhibitors on the transcriptome of feline cells. MethodsTwo types of cells derived from domestic cats, Crandell-Rees Feline Kidney (CRFK; kidney-derived) cells and PG-4 cells (astrocyte-derived), were treated with four HDAC inhibitors (panobinostat, trichostatin A, valproic acid, and vorinostat) for 24 h. Transcriptomic changes after treatment were examined using RNA sequencing. ResultsHDAC inhibitor treatment upregulated the expression of intercellular chemical interactions and signal transduction-related genes, similar to observations in human cells. Although HDAC inhibitors did not suppress the expression of cell cycle-related genes in CRFK cells, as observed in human cells, the inhibitors downregulated the expression of organogenesis-related genes. Consistent with observations in human cells, HDAC inhibitors suppressed the expression of cell cycle- and cancer-related genes in PG-4 cells. Importantly, valproic acid, which is thought to be more effective for neurological diseases than for cancer, suppressed the expression of more cancer-related genes in PG-4 cells than the other three HDAC inhibitors. Conclusion and relevanceOur findings revealed that the responses of cells derived from feline organs to various HDAC inhibitors varied considerably depending on the organ of origin and species. Since few studies, including human studies, have comprehensively compared transcriptomic responses to multiple HDAC inhibitor classes across multiple cell types, the results of this study provide a foundation for future research on the treatment and prevention of cancer and neurological diseases in domestic cats and other mammals.

AO_SCPLOWBSTRACTC_SCPLOWCellular automata and graph reaction-diffusion systems encode local spatial interactions in different mathematical forms. We develop a cochain-operator calculus for these two settings. Over a finite field Fq, every local rule on a finite neighborhood has a unique reduced polynomial representative. On an oriented line, the coboundary and endpoint maps recover the left and right shifts. Our main theorem shows that these operators, together with linear operations, constant cochains, and the degree-zero cup product, generate every finite-radius polynomial cellular automaton. Explicit formulas for Rules 30, 110, and 22 show how reflection-invariant linear coupling, directed transport, and nonlinear neighbor interactions enter the calculus. On a general graph, d*d is the unweighted combinatorial Laplacian and enters a graph reaction- diffusion recurrence. Over [R], the term - Dd*d with D [&ge;] 0 admits the usual diffusion interpretation; over Fq, the corresponding expression defines modular coupling without an intrinsic order. In the morphogenetic examples, we therefore distinguish pattern-generating dynamics from finite-state observation and use the Betti numbers of active induced subcomplexes to summarize observed patterns. This yields a common algebraic representation without identifying real-valued diffusion with finite-field dynamics.

Objective: To construct and evaluate, in an exploratory manner, a pathophysiologic rationale link- ing biological pathways derived from the peripheral transcriptome in ischemic stroke (IS) to nursing diagnoses in the NANDA-I 2024-2026 taxonomy, while emphasizing that this association is not di- rect, deterministic, or automatically inferable from textual similarity with large language models (LLMs). Methods: A computational study was conducted using public secondary data from the Gene Ex- pression Omnibus series GSE16561, which includes 63 peripheral blood samples: 39 from indi- viduals with IS and 24 from healthy controls. The pipeline integrated transcriptomic analysis and functional enrichment, semantic mapping through ClinicalBERT embeddings, and mechanistic and clinical-conceptual judgment using Claude Sonnet 4.6 as a judge. The judgment stage was treated as the central interpretive layer, designed to mediate the transcriptome, pathophysiology, functional manifestation, and NANDA-I diagnosis. Results: The analysis identified a bimodal transcriptomic pattern, with activation of pathways re- lated to innate immunity and suppression of pathways related to adaptive immunity. Semantic map- ping generated 158 pathway-diagnosis pairs. The Spearman correlation between cosine similarity and the mechanistic score was negative and statistically significant (rho = -0.243; p = 2.09e-03), but weak in magnitude. This effect size indicates that semantic similarity explained less than 6% of the variance in mechanistic plausibility, reinforcing the insufficiency of embeddings as a stand- alone criterion. Of the 158 pairs, 14 were classified as high concordance, 8 as moderate, and 136 as divergent. Conclusion: The main value of this study lies in demonstrating that translating biological pathways into nursing diagnoses requires pathophysiologic, functional, and clinical-conceptual mediation. The prioritized pairs represent mechanistically plausible hypotheses for future research, without implying causality, direct clinical confirmation, or immediate care recommendations.

Hematopoietic stem cells (HSCs) give rise to all blood cell lineages and possess long-term self-renewal potential. HSCs undergo symmetric division for their expansion and asymmetric division to generate one HSCs and one progenitor cells which contribute to production of mature blood cells. The midbody is a structure which is formed in the center of the intercellular bridge during cytokinesis. However, the midbody is either asymmetrically inherited by one daughter cell or symmetrically released after cell division, whether these distinct patterns of midbody inheritance influence HSC fate remain poorly understood. In this study, we designed a fusion protein hmKO2 and MgcRacGAP which is a component of midbody. We then traced the midbody inheritance during cell division and the future cell fates of HSC daughters after division by time-lapse imaging. As a result, we found that the midbody release correlated with the delay of the time to the next division but not to the lineage potential of HSCs, indicating the possibility that midbody remnant plays some roles in cell cycle progression. HighlightHematopoietic stem cells exhibit a low frequency of midbody inheritance. Midbody inheritance does not affect the lineage potential of daughter cells. Midbody loss is associated with delayed entry into the next cell cycle.

Abstract Familial kidney disease is common in Cyprus. Patients with a glomerular phenotype are most likely to have an autosomal dominant variant in collagen type IV alpha 3 chain (COL4A3) or collagen type IV alpha 4 chain (COL4A4) genes but pathogenic variants are not found in the majority of families. We compare the clinical phenotype between two groups of 10 Turkish Cypriot families who lack a pathogenic variant of COL4A3 or COL4A4 but have either the COL4A4 variant p.G545A or p.G999E. Both groups had identical clinical phenotypes with microscopic haematuria detected at least once in 76% of affected family members; urine protein was less than 1 g/day until glomerular filtration rate (GFR) was <30 ml/min. End-stage kidney disease (ESKD) occurred in 24.1% of those over 50 at a median age of 62.8 (36-86) years. Although the genetic cause of renal injury in this large group is still unknown, these families present with a clinical phenotype best characterised as familial hypertensive nephropathy. We propose that this condition accounts for the great excess of renal failure in the Eastern Mediterranean in those over 65 years of age.

Nutritional status and immune function have a significant impact on the prognosis of patients undergoing maintenance hemodialysis (MHD). Previous studies have shown that the Geriatric Nutritional Risk Index (GNRI) and the Prognostic Nutritional Index (PNI) at the initiation of dialysis can be used to assess the prognosis of MHD. However, as the physical status of patients are usually unstable in the early stage of dialysis, we hypothesized that the nutritional status and immune function after a certain period of stable dialysis might be more closely related to the prognosis. This study conducted a retrospective analysis of patients who started MHD between January 1, 2019 and December 31, 2021. A total of 200 patients were included, with 66 patients succumbing during follow-up. Both initial PNI and initial GNRI exhibited a negative correlation with all-cause mortality (p=0.019 and p=0.046, respectively). After three months of MHD, both PNI and GNRI increased in most patients; however, only the PNI measured after three months was significantly associated with prognosis and higher PNI was associated with a better prognosis (p<0.001). Multivariate Cox regression analyses indicated that only PNI after three months of MHD was linked to prognosis (p=0.004). Kaplan-Meier curves demonstrated patients experiencing a decrease in PNI following three months of MHD had poorer prognoses compared to those whose PNI increased (p=0.004). Furthermore, the predictive value of PNI after three months of MHD was evident in both younger (<60 years old; p=0.024) and older (>60 years old; p=0.022) patient groups. Both the PNI and GNRI showed a downward trend before death, but only PNI had a significant decline (p=0.03, compared with PNI after three months of MHD). In conclusion, for patients undergoing MHD, the correlation between PNI and prognosis is closer than that of GNRI, and the PNI after three months of MHD is a statistically significant but moderate predictor of long-term outcomes.

Predicting the long-term kidney function decline is critical for timely intervention but remains challenging. While the urinary protein-to-creatinine ratio (uPCR) is a potential surrogate endpoint, its short-term reduction's link to long-term nephroprotection requires investigation. This study aimed to develop a probabilistic neural network model to capture both the estimated glomerular filtration rate (eGFR) slope and its uncertainty based on baseline clinical characteristics. Using a retrospective dataset, we designed a neural network to output a predictive distribution (mean and standard deviation {sigma}) for the eGFR slope. SHAP (SHapley Additive exPlanations) was used for model interpretation, and a simulation study quantified the impact of uPCR reduction. In the validation set, the model achieved a Pearson's correlation coefficient of 0.56 and an RMSE of 2.81 ml/min/1.73m^2/year between predicted and actual slopes. SHAP analysis identified uPCR as the most potent predictor, with higher baseline levels associated with a more rapid eGFR decline. Furthermore, a simulated 62% uPCR reduction demonstrated a significant improvement in the predicted eGFR slope, an effect most pronounced in patients with high baseline uPCR. This proof-of-concept study reinforces the critical role of uPCR in predicting eGFR slope and suggests its reduction may contribute to long-term kidney function preservation, warranting validation in larger, diverse real-world datasets.

Valproic acid/sodium valproate (VPA) is a widely prescribed anticonvulsant and has also been used against certain tumor cells. It is a potent modulator of gene expression. Its ability to induce apoptosis has been well documented in HeLa cells. However, another form of cell death - mitotic catastrophe - has not yet been explored in VPA-treated HeLa cells. Here, we investigated the effects of VPA treatment on mitotic catastrophe characteristics, including morphological features and their frequencies, fluorescence intensity signals of caspase-2 and p53, and the expression and abundance of DNMT1 and DNMT3B. An increased frequency of mitotic catastrophe was observed not only morphologically, but also through enhanced induction of caspase-2, involvement of p53, at least under more drastic VPA treatment, but without a decrease in DNMT1 or DNMT3B levels. Additionally, enhancement of mitotic catastrophe coincided with a reduction in mitotic chromosome abnormalities. Increased DNMT3B expression following VPA action, may be favored by previously reported chromatin decondensation induced by this drug. Enhanced CpG methylation of specific DNA sites could thus be promoted. In conclusion, VPA was shown to trigger metabolic pathways linked to different forms of cell death in HeLa cells, supporting its oncosuppressive potential.

Dung beetles can use a variety of orientation cues to maintain a consistent bearing during ball-rolling. Where several cues are available, they appear to learn the spatial relationship between them, providing redundancy if some cues are removed. Mounting evidence indicates that such a learning process is implemented in the insect head direction circuit; specifically, in the plastic substrate between sensory input neurons and compass neurons in the central complex. This plasticity appears to be driven by rotational movements, providing a clear link with observed beetle 'dance' behaviour. Here, we extend our functional model of this circuit and use it on a robot platform, to test it in the same behavioural assay as was used for the beetles. The robot was able to replicate the beetle's ability to substitute a directional wind cue for a point source light cue in guiding straight-line movement. However, it also revealed significant biasing coupled to dance direction. This biasing appears to be caused by inherent conflict between recurrent and instantaneous inputs to the compass circuit. We predict that the real insect should experience similar issues unless it has evolved a neural mechanism to compensate.

Microtubule-destabilizing agents (MDAs) and microtubule-stabilizing agents (MSAs) are commonly used chemotherapeutic agents due to its activity to induce cell death by compromising the dynamics of spindles during mitosis. Ewing sarcoma, the second most common pediatric bone cancer, is known to selectively respond to MDAs as a first-line treatment, but not to MSAs. Ewing sarcoma cells carry an aberrant EWSR1-FLI1 fusion gene and only one wildtype EWSR1 allele. To investigate the origin of this MDA sensitivity, we used an (AID-EWSR1/wt: EWSR1-FLI1-mCherry/wt) cell line that enables conditional induction of EWSR1-FLI1 expression (Tet-On system) and EWSR1 knockdown derived from one EWSR1 allele (auxin-degron system). A combination of EWSR1-FLI1 expression and EWSR1 knockdown induces apoptosis upon nocodazole treatment, a type of MDA. Our study revealed that the mitotic spindles of Ewing sarcoma cells (A673, RD-ES and SK-ES1) contain elevated levels of tubulin damage, visualized with GTP-tubulin, compared to mesenchymal stem cells (MSC). Consistently, the combination of EWSR1-FLI1 expression and EWSR1 knockdown in (AID-EWSR1/wt: EWSR1-FLI1-mCherry/wt) cell line also leads to an increased incidence of damage in mitotic spindles. Together, we propose that the sensitivity of Ewing sarcoma cells is derived from the increased levels of damage to mitotic spindles caused by EWSR1-FLI1 expression and EWSR1 knockdown.