Nevin Manimala

New Phytol. 2024 May 12. doi: 10.1111/nph.19806. Online ahead of print.

ABSTRACT

As temperature rises, net carbon uptake in tropical forests decreases, but the underlying mechanisms are not well understood. High temperatures can limit photosynthesis directly, for example by reducing biochemical capacity, or indirectly through rising vapor pressure deficit (VPD) causing stomatal closure. To explore the independent effects of temperature and VPD on photosynthesis we analyzed photosynthesis data from the upper canopies of two tropical forests in Panama with Generalized Additive Models. Stomatal conductance and photosynthesis consistently decreased with increasing VPD, and statistically accounting for VPD increased the optimum temperature of photosynthesis (T_opt) of trees from a VPD-confounded apparent T_opt of c. 30-31°C to a VPD-independent T_opt of c. 33-36°C, while for lianas no VPD-independent T_opt was reached within the measured temperature range. Trees and lianas exhibited similar temperature and VPD responses in both forests, despite 1500 mm difference in mean annual rainfall. Over ecologically relevant temperature ranges, photosynthesis in tropical forests is largely limited by indirect effects of warming, through changes in VPD, not by direct warming effects of photosynthetic biochemistry. Failing to account for VPD when determining T_opt misattributes the underlying causal mechanism and thereby hinders the advancement of mechanistic understanding of global warming effects on tropical forest carbon dynamics.

PMID:38736030 | DOI:10.1111/nph.19806

Pediatr Radiol. 2024 May 13. doi: 10.1007/s00247-024-05946-0. Online ahead of print.

ABSTRACT

BACKGROUND: Magnetic resonance imaging (MRI) findings associated with athletic pubalgia are well documented in the adult literature.

OBJECTIVE: To describe the spectrum of MRI findings in adolescents with pubic symphyseal injuries/athletic pubalgia.

MATERIALS AND METHODS: This is an institutional review board approved, retrospective study of all patients < 18 years who were referred for MRI, over the last 10 years. Two pediatric musculoskeletal radiologists evaluated the MRI in consensus for the following findings: Chronic Salter-Harris (SH)-I equivalent fracture or asymmetric parasymphyseal ossific fraying, non-retractile muscular tear or retraction, and edema of the aponeurosis and arcuate ligament. Radiographs were also reviewed for Risser stage.

RESULTS: Fifteen patients were identified (100% male, median age 17 years, IQR 16-17.6). Most patients (14/15, 93%) had either asymmetric parasymphyseal ossific fraying (4/15, 27%) or chronic SH-1 equivalent fracture (10/15, 67%) of the pubic symphysis, and all patients (15/15, 100%) had aponeurotic and arcuate ligament edema. Few patients had rectus abdominis muscular retraction (2/15, 13%), non-retractile muscular tear of the rectus abdominis (2/15, 13%), and/or adductor muscle (4/15, 27%). Risser stage was as follows: stages 0 (13%), 3 (7%), 4 (47%), and 5 (33%). The injuries in our limited data set were independent of skeletal maturity with no statistically significant association between any of the MRI findings and Risser stage.

CONCLUSION: The MR imaging spectrum of adolescent athletic pubalgia differs from the described findings in adults due to skeletal immaturity. The cleft sign described in adults manifests in adolescents as asymmetric parasymphyseal ossific fraying and chronic SH-1 equivalent fractures.

PMID:38736018 | DOI:10.1007/s00247-024-05946-0

Geroscience. 2024 May 13. doi: 10.1007/s11357-024-01191-3. Online ahead of print.

ABSTRACT

Stochastic epigenetic mutations (SEMs) have been proposed as novel aging biomarkers to capture heterogeneity in age-related DNA methylation changes. SEMs are defined as outlier methylation patterns at cytosine-guanine dinucleotide sites, categorized as hypermethylated (hyperSEM) or hypomethylated (hypoSEM) relative to a reference. Because SEMs are defined by their outlier status, it is critical to differentiate extreme values due to technical noise or data artifacts from those due to real biology. Using technical replicate data, we found SEM detection is not reliable: across 3 datasets, 24 to 39% of hypoSEM and 46 to 67% of hyperSEM are not shared between replicates. We identified factors influencing SEM reliability-including blood cell type composition, probe beta-value statistics, genomic location, and presence of SNPs. We used these factors in a training dataset to build a machine learning-based filter that removes unreliable SEMs, and found this filter enhances reliability in two independent validation datasets. We assessed associations between SEM loads and aging phenotypes in the Framingham Heart Study and discovered that associations with aging outcomes were in large part driven by hypoSEMs at baseline methylated probes and hyperSEMs at baseline unmethylated probes, which are the same subsets that demonstrate highest technical reliability. These aging associations were preserved after filtering out unreliable SEMs and were enhanced after adjusting for blood cell composition. Finally, we utilized these insights to formulate best practices for SEM detection and introduce a novel R package, SEMdetectR, which uses parallel programming for efficient SEM detection with comprehensive options for detection, filtering, and analysis.

PMID:38736015 | DOI:10.1007/s11357-024-01191-3

Sci Rep. 2024 May 13;14(1):10845. doi: 10.1038/s41598-024-61583-5.

ABSTRACT

With growing recognition of the importance of community engagement in addressing public health challenges, its role in promoting healthy behaviors and preventing infectious diseases has gained attention. However, vaccination coverage remains a significant concern in many developing countries. While previous studies have linked community engagement to positive health outcomes, there is a gap in understanding its influence on individual vaccination choices, particularly in the context of developing countries. Utilizing data from the 2021 Chinese General Social Survey (CGSS), this study examines the impact of community engagement on COVID-19 and flu vaccination uptake among 7281 individuals. Community engagement, measured by community vaccination notifications, serves as the key independent variable. The study employs Ordinary Least Squares (OLS) regression and Propensity Score Matching (PSM) methods to analyze the relationship between community engagement and vaccination behavior. The analysis reveals a positive association between community engagement and vaccination rates. Specifically, individuals receiving notifications were more likely to get the COVID-19 vaccine compared to non-recipients (vaccination rates: 100% vs. 53.3%), and flu vaccination rates were also significantly higher among those notified (2.7% vs. 1.9%). Mechanism analysis suggests that individuals receiving community notifications are more aware of the benefits of vaccination, leading to higher vaccination rates among this group. This study underscores the effectiveness of community engagement strategies in promoting positive vaccination behavior among individuals in China. By enhancing awareness and trust in immunization, community engagement initiatives play a crucial role in shaping health behaviors and improving vaccination uptake. These findings emphasize the importance of integrating community engagement approaches into public health interventions to address vaccination challenges.

PMID:38736012 | DOI:10.1038/s41598-024-61583-5

Environ Sci Pollut Res Int. 2024 May 12. doi: 10.1007/s11356-024-33565-7. Online ahead of print.

ABSTRACT

The “dual-carbon” objective presents a huge challenge for China and the world, with profound implications for the advancement of China’s eco-friendly economy. Additionally, informatization development has a significant impact on the level of carbon emissions in both local and neighbouring regions. Therefore, we employ panel data from 30 provinces in China spanning the years 2012 to 2021, and use the Kernel density estimate and Moran’s index to explore informatization level and carbon emissions space agglomeration characteristics. We elucidate the nonlinear relationship and heterogeneity between informatization improvement and carbon emissions based on the spatial Durbin model. The primary findings are as follows. Firstly, we discover a distinct spatial clustering phenomenon which the informatization level is high in coastal areas and low in inland areas, whereas carbon emissions are low in the south and high in the north. Secondly, the effect of the informatization level on carbon emissions is shown as a U-shaped and non-linear correlation, signifying inhibitory and subsequently promoting phases. Thirdly, we reveal the negative influence on carbon emissions caused by spatial lag terms of the informatization level, and find that a higher local informatization level will have an inhibitory effect on carbon emissions in neighbouring areas. Finally, there is a spatial heterogeneity in the impact of the informatization level on carbon emissions, which presents the U-shaped relation between informatization level and carbon emissions varies across the North-South subregion and the three major economic subregion of China.

PMID:38735997 | DOI:10.1007/s11356-024-33565-7

Langenbecks Arch Surg. 2024 May 13;409(1):157. doi: 10.1007/s00423-024-03349-1.

ABSTRACT

PURPOSE: The JCOG (Japan Clinical Oncology Group) 0212 study did not confirm the noninferiority of mesorectal excision (ME) alone to ME with LLND for rectal or anal adenocarcinomas. Furthermore, the significance of LLND for SCCs remains unknown. We evaluated the significance of lateral lymph node dissection (LLND) of squamous cell carcinoma (SCC) of the anal canal.

METHODS: This retrospective cohort study was conducted in 435 patients with SCCs among 1,781 patients with anal canal tumors. In 40 patients who underwent LLND, the 5-year relapse-free survival (5y-RFS) and 5-year overall survival (5y-OS) were compared between groups with positive and negative histopathological findings. In 71 patients with negative lateral lymph node metastasis in the preoperative diagnosis, the 5y-RFS, 5y-OS, and 5-year local recurrence-free survival were compared between patients who did and did not undergo LLND.

RESULTS: The clinical and pathological T stages predicted pathological lateral pelvic lymph node metastasis. There was no statistically significant difference in 5y-RFS and 5y-OS between patients who did and did not undergo LLND. Among patients who underwent LLND, 5y-RFS in those with positive histopathological findings (15.0%) was worse than that in those without (59.2%) (p = 0.002).

CONCLUSIONS: In patients who underwent LLND, 5y-RFS in those with positive histopathological findings than in those without LLND did not contribute to prognosis.

PMID:38735992 | DOI:10.1007/s00423-024-03349-1

Sci Rep. 2024 May 12;14(1):10843. doi: 10.1038/s41598-024-61391-x.

ABSTRACT

The Johns Hopkins Learning Environment Scale (JHLES) was developed by Robert B. Shochet, Jorie M. Colbert and Scott M. Wright of the Johns hopkins university school of medicine and consists of 28 items used to evaluate perception of the academic environment. The objective was to translate and adapt the JHLES to Polish cultural conditions and to validate the Polish version of the tool. The JHLES questionnaire was completed by students of all years (first-fifth) of the faculties of dental medicine at the Medical University of Lublin and the Medical University of Gdańsk. The total surveyed population consisted of 597 students. The overall reliability of the tool was excellent. Confirmatory factor analysis was performed in order to confirm structural consistency with the original JHLES tool. Consequently, all indices had acceptable values (close to 1 or 0, depending on the case), and there was consistency in the results, which shows that the JHLES model is supported by the data. In the present study, the JHLES has been validated in a sample of dental students for the first time in Poland and Europe. Our study provided good evidence for the reliability and validity of the Polish version of the JHLES. In conclusion, the Polish-language version of the JHLES questionnaire is a reliable and valid instrument for analysing the learning environment for students, and its factor structure is supported by the data.

PMID:38735990 | DOI:10.1038/s41598-024-61391-x

Sci Rep. 2024 May 12;14(1):10837. doi: 10.1038/s41598-024-60931-9.

ABSTRACT

Self-medication is a prevalent practice among university students globally and is a significant public health concern. However, previous research has been limited in scope, focusing primarily on adolescents or the general public, leaving a gap in understanding the causal relationships associated with self-medication; thus, this study aimed to investigate the factors influencing self-medication practices among university students in Bangladesh by developing a comprehensive causal model. Data from 417 students across five public universities were collected using the simple random walk technique by a team of 10 members. The study utilized constructs of knowledge, attitude, and convenience related to self-medication as independent variables, while self-medication practice as the dependent variable. One-way ANOVA and structural equation modeling (SEM) were employed to develop a causal model of self-medication practice among university students in Bangladesh. The findings revealed that students with better medication knowledge and adverse drug reactions (ADRs) were more likely to practice self-medication. A positive attitude towards self-medication and ADRs was also significantly associated with higher self-medication practice scores. Additionally, those who perceived self-medication as convenient and prescribed medication as inconvenient had higher self-medication practice scores. The attitude towards self-medication had the most substantial negative effect on self-medication practice, followed by the inconvenience of prescribed medication and the convenience of self-medication. The model explained 87% of the variance in self-medication practice, indicating a good fit for the data. University students in Bangladesh possess intermediate knowledge of medication and primary knowledge of ADRs. They exhibit a positive attitude towards self-medication and ADRs. Physical convenience favors self-medication, while the inconvenience of prescribed medication contributes to its lower preference. Policymakers should focus on evidence-based guidelines to reduce the extent of unnecessary self-medication practice and to enhance the quantity and accessibility of prescribed medications to address the issue effectively.

PMID:38735980 | DOI:10.1038/s41598-024-60931-9

Eur J Med Res. 2024 May 12;29(1):282. doi: 10.1186/s40001-024-01855-y.

ABSTRACT

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was to design dosiomics-based machine learning (ML) models for prediction of AST, to enable creating optimized treatment plans for high-risk individuals.

METHODS: Dosiomics features extracted using Pyradiomics tool (v3.0.1), along with treatment plan-derived dose volume histograms (DVHs), and patient-specific treatment-related (PTR) data of breast cancer patients were used for modeling. Clinical scoring was done using the Common Terminology Criteria for Adverse Events (CTCAE) V4.0 criteria for skin-specific symptoms. The 52 breast cancer patients were grouped into AST 2 + (CTCAE ≥ 2) and AST 2 – (CTCAE < 2) toxicity grades to facilitate AST modeling. They were randomly divided into training (70%) and testing (30%) cohorts. Multiple prediction models were assessed through multivariate analysis, incorporating different combinations of feature groups (dosiomics, DVH, and PTR) individually and collectively. In total, seven unique combinations, along with seven classification algorithms, were considered after feature selection. The performance of each model was evaluated on the test group using the area under the receiver operating characteristic curve (AUC) and f1-score. Accuracy, precision, and recall of each model were also studied. Statistical analysis involved features differences between AST 2 – and AST 2 + groups and cutoff value calculations.

RESULTS: Results showed that 44% of the patients developed AST 2 + after Tomotherapy. The dosiomics (DOS) model, developed using dosiomics features, exhibited a noteworthy improvement in AUC (up to 0.78), when spatial information is preserved in the dose distribution, compared to DVH features (up to 0.71). Furthermore, a baseline ML model created using only PTR features for comparison with DOS models showed the significance of dosiomics in early AST prediction. By employing the Extra Tree (ET) classifiers, the DOS + DVH + PTR model achieved a statistically significant improved performance in terms of AUC (0.83; 95% CI 0.71-0.90), accuracy (0.70), precision (0.74) and sensitivity (0.72) compared to other models.

CONCLUSIONS: This study confirmed the benefit of dosiomics-based ML in the prediction of AST. However, the combination of dosiomics, DVH, and PTR yields significant improvement in AST prediction. The results of this study provide the opportunity for timely interventions to prevent the occurrence of radiation induced AST.

PMID:38735974 | DOI:10.1186/s40001-024-01855-y

Gut Pathog. 2024 May 12;16(1):27. doi: 10.1186/s13099-024-00616-w.

ABSTRACT

BACKGROUND: Enhancing our understanding of the underlying influences of medical interventions on the microbiome, resistome and mycobiome of preterm born infants holds significant potential for advancing infection prevention and treatment strategies. We conducted a prospective quasi-intervention study to better understand how antibiotics, and probiotics, and other medical factors influence the gut development of preterm infants. A controlled neonatal mice model was conducted in parallel, designed to closely reflect and predict exposures. Preterm infants and neonatal mice were stratified into four groups: antibiotics only, probiotics only, antibiotics followed by probiotics, and none of these interventions. Stool samples from both preterm infants and neonatal mice were collected at varying time points and analyzed by 16 S rRNA amplicon sequencing, ITS amplicon sequencing and whole genome shotgun sequencing.

RESULTS: The human infant microbiomes showed an unexpectedly high degree of heterogeneity. Little impact from medical exposure (antibiotics/probiotics) was observed on the strain patterns, however, Bifidobacterium bifidum was found more abundant after exposure to probiotics, regardless of prior antibiotic administration. Twenty-seven antibiotic resistant genes were identified in the resistome. High intra-variability was evident within the different treatment groups. Lastly, we found significant effects of antibiotics and probiotics on the mycobiome but not on the microbiome and resistome of preterm infants.

CONCLUSIONS: Although our analyses showed transient effects, these results provide positive motivation to continue the research on the effects of medical interventions on the microbiome, resistome and mycobiome of preterm infants.

PMID:38735967 | DOI:10.1186/s13099-024-00616-w