TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analyses
Cytokines play a crucial role in immune system regulation, mediating responses from pathogen defense to tissue-damaging inflammation. Excessive cytokine production is implicated in severe conditions such as cancer progression, hemophagocytic lymphohistiocytosis, and severe cases of Coronavirus disease-2019 (COVID-19). Studies have shown that cytokine expression profiles serve as biomarkers for disease severity and mortality prediction, with machine learning (ML) methods increasingly employed for predictive analysis. To improve patient outcome predictions, treatment adaptation, and survival rates, longitudinal analysis of cytokine profiles is essential. Time-series cytokine profiling has been linked to tumor response, overall survival in various cancers, and acute encephalopathy. Similarly, COVID-19 severity and patient outcomes correlate with cytokine expression dynamics over time. However, challenges remain due to the limited availability of time-series cytokine data, restricting broader experimental applications and robust predictive modeling. Recent advancements indicate that cytokine expression can be computationally inferred using gene expression data and transcription factor interactions. Inferring cytokine levels from existing gene expression datasets could enhance early disease detection and treatment response predictions while reducing profiling costs. This work proposes TSCytoPred, a deep learning-based model trained on time-series gene expression data to infer cytokine expression trajectories. TSCytoPred identifies genes relevant for predicting target cytokines through interaction relationships and high correlation. These identified genes are subsequently utilized in a neural network incorporating an interpolation block to estimate cytokine expression trajectories between observed time points. Performance evaluations using a COVID-19 dataset demonstrate that TSCytoPred significantly outperforms baseline regression methods, achieving the highest coefficient of determinataion (R2) and the lowest mean absolute error (MAE). Furthermore, cytokine data inferred by TSCytoPred enhances COVID-19 patient severity risk predictions, demonstrating the model’s clinical utility. TSCytoPred can be effectively applied to datasets with limited time points and accommodates longitudinal datasets containing irregular temporal gaps, thereby enhancing disease outcome analysis such as in COVID-19 cases and expanding the applicability of multi-omics datasets in rare disease contexts with missing multi-omics samples. TSCytoPred is publicly available at https://github.com/joungmin-choi/TSCytoPred.
Choi et al. (2025) TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analyses. PeerJ 13:e20270 https://doi.org/10.7717/peerj.20270
Assessment of distinct effects of Parinari curatellifolia Planch.ex Benth Ethanolic leaf extract on glucose transport in different cell types
Extracts of Parinari curatellifolia Planch.ex Benth have been used as a traditional medicine in Sub-Saharan Africa for the management of various ailments including diabetes and has been shown to reduce plasma glucose levels in rat models of diabetes. Treatment of a range of mammalian cell lines with P. curatellifolia ethanolic leaf extract (PCE) for 24–48 h, typically between 0 and 100 µg/mL, revealed different actions: in 3T3-L1 adipocytes, PCE markedly inhibited insulin-stimulated glucose transport (50% inhibition at 100 µg/mL), whereas by contrast PCE-treatment of Caco-2 cells, a model of the intestinal epithelia at the same concentration, increased glucose transport ∼2-fold. This effect was accompanied by increased glucose transporter-1 (GLUT1) levels but is independent of changes in the level of Akt, Adenosine monophosphate-activated protein kinase (AMPK) or p38. Our data suggest that the antidiabetic effects of extracts of P. curatellifolia may arise by increased absorption of glucose from the gut and thus distribution to other cells/tissues. Our data further highlight the importance of screening metabolic actions of plant extracts against multiple cell lines, as these can often exhibit distinct cell-type-specific responses, and further suggest that relatively low doses of PCE (up to 100 µg/mL) could warrant investigation in in vivo models of disease.
Omale et al. (2025) Assessment of distinct effects of Parinari curatellifolia Planch.ex Benth Ethanolic leaf extract on glucose transport in different cell types. PeerJ 13:e20269 https://doi.org/10.7717/peerj.20269
Impact of insular landscape features on the population genetics of a threatened climbing palm, Korthalsia rogersii Becc., endemic to the Andaman Islands
Despite the critical structural and functional roles of palms in tropical forest ecosystems and their importance in the local economy and livelihood, palms face significant threats from habitat loss and economic exploitation. Many endemic palms on tropical islands warrant conservation strategies aimed at augmenting the existing gene pool to support effective management and long-term protection of genetic diversity. This study investigated the genetic diversity and structure of Korthalsia rogersii, a threatened climbing palm (rattan) endemic to the Andaman Islands in the Bay of Bengal, across seven known populations (including recently identified ones) using microsatellite markers. The aim was to formulate informed conservation strategies by understanding how the island landscape influences the population genetic divergence of the species. Although heterozygosity and bottleneck analyses did not reveal significant genetic diversity loss, a positive correlation between population size and the number of observed alleles points to a potential ongoing decline. Moderate to high genetic differentiation was observed between populations, with geographical isolation contributing to divergence, particularly in the Interview island population. Notably, the South Andaman population (Chidiya Tapu) harbours the highest number of private alleles, despite exhibiting low overall genetic divergence, indicating it may serve as a reservoir of lost genetic diversity. Further, the Bakultala population shows significant within-population relatedness and reduced allelic diversity, indicative of genetic isolation and demographic decline. These findings provide preliminary insights into the role of the island landscapes in the Andaman archipelago in shaping population genetic divergence among plant taxa. Effective conservation strategies should target gene diversity, genetic structure and hotspots of unique alleles identified in the study, prioritising both population size enhancement and genetic augmentation to ensure the long-term survival of K. rogersii.
Paremmal et al. (2025) Impact of insular landscape features on the population genetics of a threatened climbing palm, Korthalsia rogersii Becc., endemic to the Andaman Islands. PeerJ 13:e20265 https://doi.org/10.7717/peerj.20265
Multimodal system for recording individual-level behaviors in songbird groups
The implicit goal of longitudinal observations of animal groups is to identify individuals and to reliably detect their behaviors, including their vocalizations. Yet, to segment fast behaviors and to extract individual vocalizations from sound mixtures remain challenging problems. Promising approaches are systems that record behaviors with multiple cameras, microphones, and animal-borne wireless sensors. Good systems extract from such multimodal signals perfectly synchronized data streams. In this vein, we designed a modular system (BirdPark) for simultaneously recording small animals wearing custom low-power frequency-modulated radio transmitters. Our custom software-defined radio receiver makes use of a multi-antenna demodulation technique that eliminates data losses due to radio signal fading and that increases the signal-to-noise ratio of the received radio signals by 6.5 dB compared to demodulation from the best single-antenna. Digital acquisition of all data streams relies on a single clock, which offers accurate cross-modal redundancies that can be used to dissect rapid behaviors on time scales well below the video frame period. We demonstrate this feat by reconstructing the wing-stroke phases of free-flying songbirds and by separating the vocalizations among up to eight vocally interacting birds. In conclusion, our work paves the way for automatically dissecting complex social behaviors.
Rüttimann et al. (2025) Multimodal system for recording individual-level behaviors in songbird groups. PeerJ 13:e20203 https://doi.org/10.7717/peerj.20203
Risk factors of diastasis recti abdominis, and relationship with surface electromyography characteristics of pelvic floor muscles in early postpartum: a retrospective study
Objective This study aimed to identify the factors associated with diastasis recti abdominis (DRA) in early postpartum women and investigate any relationship with surface electromyography (sEMG) characteristics of pelvic floor muscles (PFM). Methods A total of 478 participants who visited Fujian Maternity and Child Health Hospital for postpartum re-examination between January and March 2023 were divided into two groups: DRA and Non-DRA. Basic demographic data were collected via self-reported questionnaires. Additionally, inter-recti distance (IRD) was measured using ultrasound imaging, and pelvic floor muscle activity was assessed using surface electromyography according to the Glazer protocols. Results There were no significant differences between the non-DRA and DRA groups in terms of weight gain during pregnancy, physical activity, number of fetuses, delivery mode, gestational diabetes, or urinary incontinence during pregnancy or postpartum. However, the DRA group was older and had a significantly lower level of education. Both pre-pregnancy and postpartum body mass index (BMI) were higher in the DRA group. The proportion of first-time mothers was greater in the non-DRA group, and fetal weight was lower in the non-DRA group compared to the DRA group. Multivariate logistic regression analysis revealed that older maternal age, lower education level, and a high number of deliveries were independently associated with an increased risk of DRA. No significant differences were observed in sEMG parameters between the two groups at the pre-baseline, flick contraction, tonic contraction, endurance contraction, and post-baseline stages. Conclusion Older maternal age, lower educational attainment, and higher parity were significantly associated with an increased risk of diastasis recti abdominis in early postpartum. No correlation was found between the sEMG characteristics of pelvic floor muscles and diastasis recti abdominis in the early postpartum period.
He et al. (2025) Risk factors of diastasis recti abdominis, and relationship with surface electromyography characteristics of pelvic floor muscles in early postpartum: a retrospective study. PeerJ 13:e20299 https://doi.org/10.7717/peerj.20299
Screening frost-tolerant sunflower hybrids: integrating physiological traits and electrolyte leakage analysis
Background Frost is an important environmental stress factor that adversely affects plant growth and development and can even threaten plant survival. Methods This study aimed to identify frost-tolerant sunflower hybrids by analyzing the changes in physiological characteristics after exposure to frost at two early growth stages. Fourteen sunflower hybrids were exposed to frost stress at −4 °C for 4 hours at developmental stages of V2 and V4. Chlorophyll content (SPAD), relative leaf water content, leaf temperature, and electrolyte leakage were measured. Additionally, the percentage of damaged and dead plants following frost stress was recorded. Principal component analysis was performed for classification of sunflower hybrids. Results Significant differences were observed among the sunflower hybrids for all parameters investigated. All parameters were significantly affected by genotype and frost treatment. Increased electrolyte leakage and decreased relative water content were identified in frost- stressed plants. Electrolyte leakage was found to be significantly correlated with the percentage of damaged and dead plants at the V4 stage. Frost susceptibility increased with the advancing growth stage, with a higher percentage of damaged and dead plants at the four-leaf stage. The dead plant rate increased from 4.1% at the V2 stage to 19.4% at the V4 stage. SY Roseta, P63LE113, P64LE121, and Sanbro MR had the lowest percentage of damaged and dead plants at the two-leaf stage, while Sanbro MR, LG 50.585, and LG 59.580 were at the V4 stage. Conclusions The study highlighted the crucial influence of the growth stage on frost tolerance, with earlier stages showing greater resilience. Sunflower hybrids P63LE113, SY Gibraltar, and P63MM54 appeared more tolerant to frost damage. At the V4 stage, chlorophyll content and electrolyte leakage can be employed as potential selection criteria for frost-tolerant genetic resources and hybrids.
Kaya et al. (2025) Screening frost-tolerant sunflower hybrids: integrating physiological traits and electrolyte leakage analysis. PeerJ 13:e20282 https://doi.org/10.7717/peerj.20282
Serum cystatin-C and all-cause mortality in patients with hypertrophic cardiomyopathy: a retrospective cohort study
Background Numerous studies across various populations have revealed that elevated cystatin-C levels are associated with an excessive risk of mortality. However, the prognostic value of cystatin-C remains unidentified in hypertrophic cardiomyopathy (HCM) patients. The objective of this study was to investigate whether serum cystatin-C could predict all-cause mortality independently in HCM patients. Methods Data from 456 HCM patients treated at West China Hospital were collected and stratified into two groups based on the median baseline serum cystatin-C level. All-cause mortality was the primary outcome. Cox regression models were used to analyze the association between cystatin-C levels and mortality risk. Results A total of 90 deaths were recorded over a median follow-up period of 4.67 years. Patients with higher cystatin-C levels had an increased risk of all-cause mortality (adjusted hazard ratio (HR): 2.11, 95% CI [1.30–3.42], p = 0.003) compared to those with lower levels. Time-dependent area under the curves (AUC) of cystatin-C in different time points, ranging from initial measurement to follow-up, showed a relatively stable fluctuation between 0.70 and 0.80. In comparison, the commonly used renal function markers, estimated glomerular filtration rate (eGFR) and serum creatinine, yielded lower AUC values. Restricted cubic spline curves showed that with median value of cystatin-C (1.01 mg/L) as reference, there was a gradual rise in risk of all-cause mortality with cystatin-C increasing. Subgroup analyses in female, in the patients ≥ 58 years old, and in the patients with eGFR ≥ 60 mL/min/1.73 m2 consistently confirmed robustness of the main findings. Conclusion Elevated serum cystatin-C levels are associated with a higher risk of all-cause mortality in HCM patients, providing valuable prognostic information beyond traditional renal function markers such as eGFR and serum creatinine.
Liu et al. (2025) Serum cystatin-C and all-cause mortality in patients with hypertrophic cardiomyopathy: a retrospective cohort study. PeerJ 13:e19631 https://doi.org/10.7717/peerj.19631
Prognostic implications of microRNA-107 in esophageal cancer: a retrospective cohort study
Background Esophageal squamous cell carcinoma (ESCC) imposes a heavy disease burden in China, accounting for over 50% of global cases and approximately 301,000 annual deaths. Current prognostic markers inadequately predict recurrence in early-stage patients. This study investigates microRNA-107 (miR-107) as a novel prognostic biomarker for ESCC. Methods Tumor tissues (n = 66) and adjacent normal tissues (n = 28) were collected from ESCC patients undergoing radical surgery (2010–2012). miR-107 expression was quantified via reverse transcription quantitative polymerase chain reaction (RT-qPCR) (normalized to U6 snRNA). Clinicopathological correlations and survival outcomes were analyzed using χ2 tests, Kaplan–Meier/log-rank tests, and Cox regression. Comparative analysis of miR-107 levels was performed in human esophageal squamous cell carcinoma line 109 (EC109) cancer cells versus human esophageal epithelial cell (HEEC) normal epithelial cells. Results miR-107 expression was significantly lower in esophageal cancer tissues (0.801 ± 0.737) compared to adjacent non-cancerous tissues (1.390 ± 1.346), p = 0.006. Low miR-107 expression (cutoff = median) correlated with advanced tumor, node, metastasis stage (TNM stage) (I vs. V: 100% vs. 21.4%, P < 0.001), lymph node metastasis (73.1% vs. 35%, P < 0.001), and larger tumor size (70% vs. 33.3%, P < 0.001). Patients with low miR-107 had shorter median overall survival (10 vs. 59 months; Hazard Ratio (HR) = 0.475, 95% Confidence Interval (CI) [0.247–0.915]; P < 0.001). Multivariate Cox analysis confirmed miR-107 as an independent prognostic factor alongside TNM stage (HR = 3.586, 95% CI [2.253–5.708]; P < 0.001). Consistently, EC109 cells exhibited 59% lower miR-107 levels than HEEC (P = 0.029). Conclusions miR-107 downregulation is a robust predictor of aggressive ESCC phenotypes and poor survival. It holds promise as a clinical biomarker for risk stratification and personalized therapy. Future studies should validate these findings in multicenter cohorts and elucidate miR-107’s functional mechanisms.
Sun et al. (2025) Prognostic implications of microRNA-107 in esophageal cancer: a retrospective cohort study. PeerJ 13:e20327 https://doi.org/10.7717/peerj.20327
Effect of short-term exposure to air pollution on ischemic stroke incidence and mortality: a five-year time-series study in Jining, China
Background Short-term exposure to air pollutants is associated with an increased risk of ischemic stroke incidence and mortality. However, there is a lack of research based on data from disease surveillance systems. This study used disease surveillance system data to quantitatively analyze the association between air pollution and ischemic stroke incidence and mortality in Jining, China. Methods The stroke registration system of the Jining City Center for Disease Control and Prevention (CDC) includes information on confirmed stroke cases reported by all medical institutions in the jurisdiction, covering a population of 8.9 million. Generalized linear regression models combined with distributed lag nonlinear models (DLNM) were used to determine the association between air pollutants and ischemic stroke incidence and mortality. Stratified analyses by sex, age, and season were also conducted. Results During the study period (January 1, 2018, to December 31, 2022), there were 209,949 ischemic stroke incidence cases and 23,565 ischemic stroke-related deaths. There were more ischemic stroke incidence and death cases in males compared to females. The number of incidence cases was higher in the warm season (52.6%) than in the cold season (47.4%), while this pattern was reversed for the number of deaths, with a higher number of deaths in the cold season (55.9%) than in the warm season (44.1%). This study showed that exposure to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and carbon monoxide (CO) was associated with ischemic stroke incidence, and exposure to PM2.5, PM10, sulfur dioxide (SO2), and CO was associated with ischemic stroke mortality. The relative risks (RRs, with 95% CIs) for ischemic stroke incidence at the maximum single-lag effect day for each interquartile range (IQR) increment for PM2.5, PM10, NO2, and CO were 1.007 (1.001–1.014), 1.004 (1.000–1.008); 1.031 (1.011–1.051), and 1.008 (1.001–1.015), respectively. The RRs (with 95% CIs) for mortality for PM2.5, PM10, SO2, and CO were 1.049 (1.025–1.073), 1.031 (1.014–1.048), 1.021 (1.001–1.041), and 1.044 (1.017–1.071), respectively. Furthermore, the association between air pollution and ischemic stroke incidence risk was modified by age and season. Individuals aged >75 years were more vulnerable to SO2-induced ischemic stroke incidence risk, and PM2.5 and CO were more harmful in the cold season. Conclusion These findings suggest that short-term exposure to PM2.5, PM10, SO2, NO2, and CO leads to increased ischemic stroke morbidity and mortality. The elderly population, as well as the general population, should be better protected during the cold season.
Kong et al. (2025) Effect of short-term exposure to air pollution on ischemic stroke incidence and mortality: a five-year time-series study in Jining, China. PeerJ 13:e20298 https://doi.org/10.7717/peerj.20298
Are caves enough to represent karst groundwater biodiversity? Insights from geospatial analyses applied to European obligate groundwater-dwelling copepods
Caves are recognized as biodiversity hotspots for groundwater fauna, including obligate groundwater-dwelling copepods (Crustacea: Copepoda), exhibiting high species richness, endemism, and phylogenetic rarity. However, the extent to which caves alone provide a representative estimate of copepod species richness in karst areas remains uncertain. Taking advantage of the recently published EGCop dataset, the first expert-validated, Europe-wide occurrence dataset for obligate groundwater-dwelling copepods (hereinafter, GW copepods), this study investigates the distribution of GW copepods into karst areas, comparing species richness in caves versus other karst groundwater habitats (e.g., springs, karst streams, artificial wells), within and among the European karst units. The main aims are: (i) identifying karst areas which represent hotpots of GW copepod species richness; (ii) assessing to which extent caves, as open windows to the subterranean environments, contribute to define hotspots of GW copepods’ species richness into karst areas across Europe. EGCop comprises 6,986 records from 588 copepod species/subspecies distributed among four orders: Cyclopoida (3,664 records, 184 species), Harpacticoida (3,288 records, 395 species), Calanoida (32 records, seven species), and Gelyelloida (two records, two species). To perform geospatial analyses, we filtered the dataset by: (i) selecting only the records with spatial uncertainty in the associated coordinates lower than 10 km; (ii) searching for those records falling within, or very close to, the polygons representing European karst areas. Species richness hotspots were then estimated through geospatial analyses in geographic information system (GIS) environment. Within the selected records, those specifically referring to karst habitats (2,526 records, 369 species) are primarily represented by Harpacticoida (1,199 records, 228 species) and Cyclopoida (1,293 records, 132 species). Among species collected from karst habitats, records from caves (1,867, 73.9%) belong to 318 species (Harpacticoida = 189, Cyclopoida = 122, Calanoida = 7), representing 86.1% of the total species richness of karst habitats. Geospatial analyses reveal that the European hotspots of GW copepods’ species richness recorded exclusively in caves reflect the spatial arrangement of postglacial refugia in southern karst regions, though representing a subset of the broader diversity found across all karst groundwater habitats. Our findings highlight that the contribution of cave systems in groundwater biodiversity assessments and related conservation planning may vary depending on the evolution and morphologies of the target karst regions—often pointing to a high representativeness of caves for subterranean biodiversity, sometimes revealing their lower explanatory power within the broader karst systems.
Galmarini et al. (2025) Are caves enough to represent karst groundwater biodiversity? Insights from geospatial analyses applied to European obligate groundwater-dwelling copepods. PeerJ 13:e20285 https://doi.org/10.7717/peerj.20285