Reliable mortality data are important for evaluating the impact of health interventions. However, data on mortality patterns among populations living in urban informal settlements are limited.To examine the mortality patterns and trends in an urban informal settlement in Kibera, Nairobi, Kenya,Using data from a population-based surveillance platform we estimated overall and cause-specific mortality rates for all age groups using person-year-observation (pyo) denominators and using Poisson regression tested for trends in mortality rates over time. We compared associated mortality rates across groups using incidence rate ratios (IRR). Assignment of probable cause(s) of death was done using the InterVA-4 model.p = 0.004). Similarly, death due to pulmonary tuberculosis among persons 5 years and above significantly declined .We registered 1134 deaths from 2009 to 2018, yielding a crude mortality rate of 4.4  per 1,000 pyo. Males had higher overall mortality rates than females . The highest mortality rate was observed among children aged < 12 months . All-cause mortality rates among children < 12 months were higher than that of children aged 1–4 years . The overall mortality rate significantly declined over the period, from 6.7 per 1,000 pyo  in 2009 to 2.7  per 1,000 pyo in 2018. The most common cause of death was acute respiratory infections (ARI)/pneumonia (18.1%). Among children < 5 years, the ARI/pneumonia deaths rate declined significantly over the study period (5.06 per 1,000 pyo in 2009 to 0.61 per 1,000 pyo in 2018; Overall and some cause-specific mortality rates declined over time, representing important public health successes among this population. Reliable and timely mortality data are important for health services planning, prioritisation and evaluating the impact of health interventions . MonitorGlobally more than half of the world’s population live in urban areas, and the urban population is growing most rapidly in Asia and Africa . In sub-Hemophilus influenzae type B, Streptococcus pneumoniae and rotavirus were introduced in the routine childhood immunisation programme in Kenya in 2001, 2011 and 2014 respectively. In addition, a cross-sectional study conducted among residents of Kibera who delivered in 2014–2015 reported that 97% had delivered in a health facility. Individuals residing in a defined catchment area within Kibera for at least 4 months are eligible for participation in PBIDS. Infants born to PBIDS participants are also eligible, regardless of the duration of residence. A person stops being a resident if reported to be away for more than 4 months. During the study period, the population under surveillance ranged from approximately 22,000 to 28,000. PBIDS participants receive free health care for acute infectious illnesses at a centrally located clinic where facility-based surveillance for infectious diseases is also conducted.The Kenya Medical Research Institute (KEMRI) in collaboration with the US Centers for Disease Control and Prevention (CDC) has implemented the Population-Based Infectious Disease Surveillance (PBIDS) platform since 2006 in Kibera, a large urban informal settlement in Nairobi, Kenya. The surveillance methods have been described elsewhere ,17. KibeSurveillance is conducted at the household level, with regular visits by trained study personnel using standardised questionnaires to collect demographic data, including births, deaths, and migrations of household members. Starting in January 2006, home visits were conducted every 2 weeks; in October 2009, the frequency was increased to weekly, and then returned to biweekly in May 2011. In April 2015, the frequency of household visits decreased to every 6 months. The key demographic data gathered within a household did not change over the surveillance period. Since decreasing the frequency of household visits in 2015, household data collection has been supplemented by a network of community reporters; residents of the study area who provide continuous reports of pregnancies, births and deaths as they occur.Verbal autopsy (VA) is attempted for all reported deaths within a month after death by specially trained field workers who interview the deceased’s next of kin, or health workers who cared for the person at home or are familiar with the circumstances of the death. VA interviews are conducted using standard questionnaires based on tools from the World Health Organization (WHO), with updates to new versions in 2013 (2012 WHO VA questionnaire) and 2018 (2016 WHO VA questionnaire) .Data management and analyses were performed in STATA Version 13.1 software  and R for Windows version 3.6.1. We analysed all deaths occurring among PBIDS participants of all ages between January 2009 and December 2018. Assigning of probable cause(s) of death was done using a Bayesian probabilistic model, the InterVA-4 model version 4.02, setting HIV prevalence to high and malaria prevalence to low. The causes of death generated by InterVA-4 are compatible with the International Classification of Diseases version 10 (ICD-10) and are categorised into 62 groups, as defined in the WHO VA instrument . The speResults are presented as annualised mortality rates and fractions. All-cause, cause-specific, communicable, and non-communicable disease mortality rates were expressed as the number of deaths per 1,000 person-years of observation (pyo), calculated based on each PBIDS participant’s residency status during the study period. Cause-specific and grouped cause-specific mortality rates were adjusted for the proportion of deaths missing VA by dividing the number of deaths due to a particular cause by the proportion of all deaths with VA conducted to obtain an adjusted number of cause-specific deaths; adjustments were made stratified by sex, age groups and year. Deaths classified as indeterminate were excluded from cause- and group-specific rates.e (person – time) as offset and categorical year as the exposure variable. A statistically significant change was set at p < 0.05.Assuming a Poisson distribution, mortality rates with 95% CI were estimated and compared across groups using incidence rate ratios (IRR). We used Poisson regression to model for trends in mortality rates over time using logp < 0.001). The overall mortality rate in males  was higher than in females 3.6  per 1,000 pyo.A total of 1134 deaths were registered from January 2009 to December 2018 of which 774 (68.2%) had complete VA conducted. Causes of death were available for 735 (95.0%) of the completed deaths with VA. Of those without cause of death 16 (41.0%) were female and 23 (58.9%) were male. There were 256,445 pyo during the study period . The ovep < 0.001)  and males . Overall, male had higher mortality rates than females .The overall mortality rate decreased from 6.7 per 1,000 pyo  in 2009 to 2.7  per 1,000 pyo in 2018. Significant declines were observed among children aged <5 years, with mortality falling from 16.8 (95% CI 13.3–20.8) per 1,000 pyo in 2009 to 6.1  per 1,000 pyo in 2018 (< 0.001) ). AlthouAmong 774 deaths with VA, the most common cause of death was acute respiratory infections/pneumonia (18.1%), followed by HIV/AIDS related deaths (12.8%), pulmonary tuberculosis (6.9%) and malaria (5.9%); of note, 11.6% had an indeterminate cause . In chilp = 0.004). The rates of malaria, diarrhoea, HIV/AIDS and neonatal pneumonia deaths in children aged <5 years did not significantly change over time. Among persons aged ≥5 years, HIV/AIDS related deaths remained the highest cause-specific rate throughout most years of the study period. HIV/AIDS mortality rate was highest in 2009  and lowest in 2015 ; however, there was not a statistically significant decline over the study period. The rate of death due to pulmonary tuberculosis among persons aged ≥5 years declined significantly .Cause-specific mortality rates over time for the leading causes of death are presented in p < .001) and those aged ≥5 years . Mortality due to other grouped causes of death  did not significantly change over time.Trends in group-specific mortality  are shown in Over a 10-year period, the overall mortality rate declined significantly in Kibera, with a decrease of ~64% in children aged <5 and ~50% among older children and adults. The observed reduction was driven primarily by declines in deaths due to infectious causes, including acute respiratory infection (ARI)/pneumonia in children aged <5 years and tuberculosis (TB) in persons aged ≥5 years. Despite this progress, we observed a persistent burden of deaths due to infectious diseases such as HIV/AIDS and pneumonia in adults, and malaria, diarrhoea and HIV/AIDS in young children. We also observed a substantial variability in risk of death across demographic groups, highlighting the importance of mortality data for guiding public health interventions.We found ARI/pneumonia to be the predominant cause of death among children aged <5 years and a leading cause of mortality among older children and adults. Several studies have similarly highlighted respiratory infections as a leading cause of morbidity and mortality in informal settlements ,25. FactMalaria stood out as an important cause of death among children aged <5 years despite Nairobi being considered a low-risk area for malaria transmission . A study2.5) in similar settings in Kenya [Injuries and other non-communicable diseases were major contributors to mortality among persons aged >5 years, with no significant change over time. This is contrary to other studies which have reported increases in deaths due to injuries and non-communicable diseases among adults living in informal settlements . Even wiin Kenya ,41. EffoThis study had several limitations. It is important to note that misclassification errors do occur in all forms of cause-of-death assignment, including the use of InterVA-4 modelling and that InterVA-4 provides only a single cause of death per individual. Furthermore, 32% of reported deaths in our study had no VA interviews conducted primary due to lack of appropriate respondent, refusal to participate in the VA interviews and migration of family members of the deceased. Since we lack information on the causes of death in this particular group with missing VA there is a risk of underestimation of the disease burden in this population. To try and mitigate this bias we adjusted for missing VA in calculating cause-specific mortality rates. Of note, PBIDS participants receive health care for acute illnesses free of charge at the surveillance clinic, and this access to care might have impacted mortality rates over time.Despite these limitations, we emphasise the important role of verbal autopsy data in filling the gap created by inadequate vital registration systems in this setting. VA can be used to monitor population-level cause of death over time. We found that overall all-cause mortality rates and deaths due to specific infectious causes declined over time in Kibera, representing important public health successes among this underserved urban population. However, communicable diseases persist as leading causes of death, despite the availability of preventive interventions. In addition, rates of death due to injuries and non-communicable diseases have remained stable over time, and therefore responsible for an increasing proportion of death, particularly among persons aged ≥5 years. Current preventive strategies for infectious diseases and non-communicable diseases may need to be tailored to the informal settlement setting to maximise impact on mortality.Click here for additional data file.


Aortic aneurysms (AA) are prevalent worldwide with a notable absence of drug therapies. Thus, identifying potential drug targets is of utmost importance. AA often presents in the elderly, coupled with consistently raised serum inflammatory markers. Given that ageing and inflammation are pivotal processes linked to the evolution of AA, we have identified key genes involved in the inflammaging process of AA development through various bioinformatics methods, thereby providing potential molecular targets for further investigation.The transcriptome data of AA was procured from the datasets GSE140947, GSE7084, and GSE47472, sourced from the NCBI GEO database, whilst gene data of ageing and inflammation were obtained from the GeneCards Database. To identify key genes, differentially expressed analysis using the “Limma” package and WGCNA were implemented. Protein-protein intersection (PPI) analysis and machine learning (ML) algorithms were employed for the screening of potential biomarkers, followed by an assessment of the diagnostic value. Following the acquisition of the hub inflammaging and AA-related differentially expressed genes (IADEGs), the TFs-mRNAs-miRNAs regulatory network was established. The CIBERSORT algorithm was utilized to investigate immune cell infiltration in AA. The correlation of hub IADEGs with infiltrating immunocytes was also evaluated. Lastly, wet laboratory experiments were carried out to confirm the expression of hub IADEGs.342 and 715 AA-related DEGs (ADEGs) recognized from GSE140947 and GSE7084 datasets were procured by intersecting the results of “Limma” and WGCNA analyses. After 83 IADEGs were obtained, PPI analysis and ML algorithms pinpointed 7 and 5 hub IADEGs candidates respectively, and 6 of them demonstrated a high diagnostic value. Immune cell infiltration outcomes unveiled immune dysregulation in AA. In the wet laboratory experiments, 3 hub IADEGs, including BLNK, HLA-DRA, and HLA-DQB1, finally exhibited an expression trend in line with the bioinformatics analysis result.Our research identified three genes - BLNK, HLA-DRA, and HLA-DQB1- that play a significant role in promoting the development of AA through inflammaging, providing novel insights into the future understanding and therapeutic intervention of AA. Approximately 13% of men and 6% of women aged over 65 have been diagnosed with abdominal aortic aneurysm (AAA) in the United States, with around 2 million new cases arising each year  , and ageInterestingly, a growing body of evidence has shown that the ageing process is linked to chronic inflammation, characterized by elevated plasma inflammatory markers , 15, resBioinformatics is considered an effective method for identifying key molecules and investigating the potential molecular mechanisms of diseases by comparing differences between patients and healthy individuals using a variety of algorithms. In this context, we investigated the role of inflammaging-related genes in the development of AA and sought potential key genes involved in the related processes for further therapeutic targets.22.1http://www.ncbi.nlm.nih.gov/geo)   using “a2.2Significant differentially expressed genes (DEGs) from GSE140947 and GSE7084 were obtained using the R package “limma” respectively, with p-values < 0.05 and |log2 fold change (FC)| ≥ 1, where log FC > 1 represented upregulated genes and log FC < -1 represented downregulated genes. The heatmap and volcano plot of DEGs were generated using the R packages “pheatmap” and “ggplot2”.2.3Weighted gene co-expression network analysis (WGCNA) was utilized to identify modules of highly correlated genes and their associations with disease phenotypes, in order to discover potential candidate biomarkers or therapeutic targets . All subhttps://jvenn.toulouse.inrae.fr/app/example.html) (AA-related DEGs (ADEGs), identified by both WCGNA and the “limma” package, were obtained using the Jvenn online tool (le.html)  by inter2.4https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). The results were visualized using the R packages “ggplot2”  , Gene Onggplot2” , “GOplotggplot2” , and “en2.5https://www.genecards.org/), was utilized to obtain inflammation and ageing-related genes by searching for the keywords “inflammation” and “ageing”. In order to obtain a reasonable number of genes, those with relevance scores above the median were selected. This resulted in 4416 genes associated with inflammation and 4302 genes related to ageing    was empldb.org/) . Cluster2.7ML was employed as another method to screen the hub IADEGs. Three ML algorithms – least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF) analysis – were adopted, and the overlapping genes among them were treated as potential hub IADEGs for further study. LASSO logistic regression analysis assigns a value of zero to the coefficients of variables one by one in order to identify highly important genes. SVM framework based on binary classification is a supervised ML technique that identifies the optimal model by maximizing the classification margin without overfitting and not depending on the number of samples. RF analysis is a type of ensemble learning based on decision trees, focusing on the score of each variable. SVM and RF were the two best ML methods before the invention of deep learning. The R package “glmnet”  was used2.8The clinical value of potential hub IADEGs was assessed using the area under the curve (AUC) and 95% confidence interval (CI) across three datasets, including two datasets for internal validation (GSE140947 and GSE7084) and one dataset for external validation (GSE47472). The R package “pROC” was employed to perform receiver operating characteristic (ROC) analysis and generate the AUC plots. A diagnostic value was considered when the AUC was above 0.75. The R package “rma” was utilised for the creation of a nomogram.2.9https://www.targetscan.org/vert_72/), and miRTarBase  and miRNAs were predicted. Three bioinformatics databases – starBase , TargetSRTarBase  – were eRTarBase  with a p2.10GSE7084 was utilized for immune infiltration analysis. The CIBERSORT algorithm  was empl2.11Full-thickness aortic wall tissue was collected from patients undergoing aortic replacement operations due to AA (n=5) at Wuhan Union Hospital, Wuhan, China. AA specimens were gathered from the aneurysmal region of the aorta, whilst the normal samples were procured from the aorta of the recipient undergoing a heart transplant due to heart failure caused by ischemic cardiomyopathy or valvular disease. The clinical characteristics of the patients are listed in 2.12(-ΔΔCt) method.Total RNA was extracted from human aorta tissue using the RNA-easy Isolation Reagent , followed by quantitative polymerase chain reaction (qPCR) using HiScript III RT SuperMix for qPCR . Primers used in qPCR are listed in 2.13Total protein was isolated from human aorta tissue using RIPA lysis buffer and boiled in loading buffer for fifteen minutes. After separation on a 10% SDS-PAGE gel, the proteins were transferred to PVDF membranes and subsequently incubated with primary antibodies overnight at 4°C. The primary antibodies used in the study are listed in 2.14The primary antibodies used for IHC were listed in 2.15Statistical analysis was carried out to analyze the results of wet laboratory experiment and the differences in baseline data of the included patients. All data included were presented as the mean ± standard deviation (SD) of the independent experiments. The differences were analyzed by Student’s T-test using SPSS 26.0. The expression level of genes in qPCR was calculated by Student’s T−test using GraphPad Prism 9.0. P<0.05 was considered to be statistically significant.2.16https://openai.com/blog/chatgpt), developed by OpenAI, to refine the language of our article  proteins, based on a study of 164,610 UK individuals aged 60 to 70 years . HLAs arBLNK is required to promote B cell maturation and is a necessary component of BCR signaling pathways . MutatioJPH2 is one of the four JPH isoforms expressed in excitable cells, including muscle cells and neurons, and plays a crucial role in cellular excitability by impacting ion channel function related to calcium on the plasma membrane and sarcoplasmic reticulum . Reducedin vivo and in vitro, which we will focus on in our subsequent studies. Third, our research is grounded in GEO datasets with a rather small sample size, which could impact the generalizability of ML models and make it challenging to draw extrapolative conclusions. In tasks with a small sample size and high dimensionality, the model trained using limited samples is prone to overfitting and underfitting the target tasks. Consequently, the performance gap between the actual trained model and the optimal model trained using existing features and algorithms cannot be effectively reduced through training and hyperparameter adjustment, leading to subpar overall model performance. To minimize the impact of this limitation, we employed a simpler model, SVM framework based on binary classification (In our study, the interaction between inflammaging and AA was explored through bioinformatics analysis. To the best of our knowledge, we obtained key genes of AA related to inflammaging processes and provided potential molecular targets for further study. We conducted a rigorous bioinformatics analysis. Three GEO datasets and two complementary methods of hub gene screening, PPI network and ML, were utilized in our study to avoid sampling and methodological bias. However, there are also several limitations. First, the hub genes have only been validated in human tissue, leading to a conclusion lacking the support of animal models and studies without homologous genes. Second, further experiments were not conducted to elucidate the molecular regulation mechanism of these genes and their specific roles in AA development and rupture fication , 88, to 5In summary, following an extensive bioinformatics analysis, 3 genes that play a crucial role in the pathological process of AA through inflammaging were identified and validated, including BLNK, HLA-DRA, and HLA-DQB1. Further research is required to elucidate the mechanisms of these genes in the pathological process of AA and to establish their clinical significance.https://github.com/wangshilin2000/Source-code-for-figure-2-6-1260688-.The original codes used for the analyses presented in the study are publicly available. This data can be found here: The studies involving humans were approved by Ethics Committee of Union Hospital Affiliated to Tongji Medical College, Huazhong University of Science and Technology. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.SW: Conceptualization, Data curation, Validation, Writing – original draft. HL: Data curation, Formal Analysis, Methodology, Validation, Writing – original draft. PY: Data curation, Formal Analysis, Validation, Writing – original draft. ZW: Data curation, Formal Analysis, Validation, Writing – original draft. PY: Supervision, Writing – review & editing. JX: Supervision, Writing – review & editing. SC: Conceptualization, Supervision, Writing – review & editing.


The connection between vitamin D to non-alcoholic fatty liver disease (NAFLD) is still unclear. Herein, the relationship of vitamin D with NAFLD and liver fibrosis (LF) detected by vibration controlled transient elastography was investigated in US adults.The National Health and Nutrition Examination Survey of 2017–2018 was employed for our analysis. Participants were categorized as having either vitamin D deficiency (<50 nmol/L) or vitamin D sufficiency (≥50 nmol/L). A controlled attenuation parameter score of ≥ 263 dB/m was employed to define NAFLD. Significant LF was identified by the liver stiffness measurement value of ≥ 7.9 kPa. Multivariate logistic regression was adopted to explore the relationships.p = 0.21). Using multivariate logistic regression analysis, no obvious connection of vitamin D status to NAFLD  was discovered. However, among NAFLD participants, the sufficiency of vitamin D represents a lower LF risk . When evaluated in quartiles, in comparison to the lowest quartile, high vitamin D represents low LF risk in a dose-dependent manner .Among the 3407 participants, the prevalence of NAFLD and LF was 49.63% and 15.93% respectively. Compared to participants without NAFLD, no significant difference in serum vitamin D was observed in NALFD participants (74.26 vs. 72.24 nmol/L; Our study found no relationship between vitamin D and CAP-defined NAFLD in US adults.High serum vitamin D was inversely associated with liver fibrosis in a dose-dependent manner among NAFLD participants.No relationship was found between vitamin D and CAP-defined NAFLD. However, a positive connection of the high serum vitamin D to the reduced LF risk was found among NAFLD subjects. As a most frequently identified liver disorder worldwide, non-alcoholic fatty liver disease (NAFLD) affects about a quarter of the whole population . ConsideVitamin D is a sterol hormone synthesized in the skin through a chemical reaction dependent on ultraviolet radiation and is later activated by hydroxylation in liver and kidneys. Except its classical functions in regulating calcium homeostasis and the bone metabolism , vitaminTherefore, according to the 2017–2018 National Health and Nutrition Examination Survey (NHANES), we conducted this cross-sectional study to examine the connection of serum vitamin D to NAFLD and liver fibrosis (LF) detected by VCTE, providing novel ideal for liver steatosis and fibrosis diagnosis at an early stage.As a survey program based on national population, NHANES is performed every 2 years and used to evaluate the nutritional and health status of the non-institutionalized US civilian general population. Herein, we employed the NHANES of the 2017–2018 cycle for our analysis because of the data of VCTE was specifically included.A total of 9254 participants were enrolled in this cycle. Among them, 5494 participants had elastography exam with complete status. We excluded 272 participants with missing vitamin D data and 895 participants aged below 20 years. For NAFLD, 404 participants with significant alcohol intake  were excluded . We alsoThe original NHANES study protocol was approved by the Ethics Review Board of the National Center for Health Statistics Research. The signed written informed consents were provided by all the enrolled individuals.In our present study, the total 25(OH)D in serum was set as the concentration of 25(OH)D2 plus 25(OH)D3. For measuring the 25(OH)D concentrations, the high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was conducted by the National Center for Environmental Health. According to the 25(OH)D concentrations in serum, we separated the participants to two groups: the vitamin D deficiency group, whose participants had less than 50 nmol/L vitamin D in serum and the vitamin D sufficiency group, whose participants had no less than 50 nmol/L vitamin D in serum ,18. In aThe examination of transient elastography was carried out to record the data and diagnose NAFLD and LF. A XL or M probe equipped FibroScan® model 502 V2 Touch  was employed to conduct the elastography exam in the NHANES Mobile Examination Center. For each participant, no less than 10 measurements were obtained, and the values of median CAP and LSM were calculated by the device along with the interquartile range. Exams were considered complete if participants fasted at least 3 h before the exam, there were 10 or more complete liver stiffness measures, and the interquartile range/median of the LSM was < 30%. In this study, CAP value of 263 dB/m or higher was used to define NAFLD ,20 and w2, overweight: 25–30 kg/m2, and under/normal weight: < 25 kg/m2), smoking status , education level (> high school or ≤ high school), race/ethnicity , sex, and age, were included. Dietary vitamin D intake and supplemental vitamin D intake were also adjusted to account for the potential impact of dietary factors. We computed eGFR using the Chronic Kidney Disease Epidemiology Collaborative equation [Based on the previous report , the NAFequation . Diabeteequation .t-test and chi-square test were carried out for comparing the continuous and categorical variables between groups, respectively. For exploring the connections of vitamin D to NAFLD and LF, we conducted the multivariate logistic regression analyses. Three different logistic models, such as non-adjusted model 1, ethnicity-, sex-, and age-adjusted model 2, and TC-, HLD-C-, eGFR-, diabetes-, hypertension-, BMI group-, dietary vitamin D intake-, supplemental vitamin D intake-, smoking status-, education level-, and model 2 covariates-adjusted model 3, were employed in our present study. As suggested by NHANES, sample weights used for accounting for unequal selection probabilities and nonresponse were utilized in all analyses. Statistical analysis was conducted with R 4.2.0 software and the value of p less than 0.05 was considered statistically significant.Continuous variables were expressed as mean ± SE and categorical variables were expressed as number and percentage. The two sample According to the exclusion criteria, we enrolled 3407 participants in this analysis. The mean age of our study population was 48.54 ± 0.79 years, and 47.78% of the participants were male. The weighted prevalence was 49.63% for NAFLD, and the weighted prevalence of significant fibrosis among NAFLD participants was 15.93%. Mean serum vitamin D level was 73.25 ± 1.66 nmol/L, with 21.25% of participants below 50 nmol/L. Mean dietary vitamin D intake and supplemental vitamin D intake were 4.24 ± 0.12 mcg/day and 21.82 ± 2.81 mcg/day, respectively. Based on the status of vitamin D, p = 0.21). After adjusting for TC, HDL-C, eGFR, diabetes, hypertension, BMI group, dietary vitamin D intake, supplemental vitamin D intake, smoking status, education level, race/ethnicity, sex, and age, no significant associations of vitamin D status or quartiles with NAFLD were observed in the multivariate logistic regression analysis. Among the enrolled 3407 subjects, 48.42% of the participants were MAFLD. Additionally, the correlation of vitamin D with MAFLD were similar to that of vitamin D with NAFLD . For evaluating the adjusted connection of vitamin D level to LF, the multivariate logistic regression analysis was conducted. In the unadjusted model, vitamin D status (sufficiency vs. deficiency) was inversely correlated to LF . And this inverse association was also present in adjusted model 2  and 3 . When we evaluated vitamin D levels in quartiles, a dose-dependent relationship between LF and higher vitamin D levels was observed in comparison to those with lowest quartile after adjusting multiple confounding factors   .Using a large general US population, our study found that serum vitamin D is not connected to the CAP-defined NAFLD, however, among NAFLD participants, low vitamin D represents high risk of developing significant LF.PPARγ and up-regulating carnitine palmitoyltrans 2, the major enzyme for fatty acid β-oxidation [The contradictory conclusions of the correlation between NAFLD and vitamin D have been obtained from several studies ,25–29. Axidation .As a hallmark characteristic of liver injury, the advanced LF can comprise severe risks for development of hepatocellular carcinoma and hepatic failure. In consistent with our current conclusion, the negative correlation of vitamin D with LF determined by NAFLD fibrosis score was observed by other researchers ,31. In tCurrently, why vitamin D could effectively suppress the LF in NAFLD patients remains unclear. During the development of LF, hepatic stellate cell activation plays important effect. Activated hepatic stellate cells can effectively induce cell growth and transformation from a quiescent vitamin A-storing cell into an activated myofibroblast-like cell, increasing the production of extracellular matrix and tissue inhibitors of metalloproteinases . ThroughNo effective treatment strategies for hepatic fibrosis are available so far. Based on previous research, we believe that the supplementation of vitamin D may be used as new widely available and cost-effective treatment for LF prevention and therapy. A randomized double-blind placebo-controlled trial, including 311 NAFLD patients, found that 12-month usage of vitamin D (1000 IU/day) can significantly attenuate the transient elastography indices of liver steatosis and fibrosis . AnotherThe strength of this study is that a nationally representative data is included. Using this dataset, we could analyse the data from healthy individuals and are not restricted to certain kinds of patients such as diabetes. However, there are also some limitations present in our study. First, due to the cross-sectional design, the verification of causality was limited, and the impact of vitamin D over time was not evaluated. Second, there are no consensual cut-offs for CAP and LSM. Third, the vitamin D seasonal variations, as well as the usage of supplement containing calcium were not investigated in this study.In summary, based on a large general US population, this study demonstrated that the CAP-defined NAFLD is not associated with the deficiency of vitamin D. On the other hand, low serum vitamin D was closely connected to increased LF risk among NAFLD participants. Thus, the role of vitamin D in prevention and treatment of NAFLD warrants further research.


Bursaphelenchus xylophilus is a forestry quarantine pest and causes an extremely dangerous forest disease that is spreading worldwide. Due to the complex pathogenic factors of pine wood nematode disease, the pathogenesis is still unknown. B. xylophilus ultimately invades a host and causes death. However, little is known about the defence-regulating process of host pine after infection by B. xylophilus at the molecular level. Therefore, we wanted to understand how Pinus massoniana regulates its response to invasion by B. xylophilus. P. massoniana were artificially inoculated with B. xylophilus solution, while those without B. xylophilus solution were used as controls. P. massoniana inoculated with B. xylophilus solution for 0 h, 6 h, 24 h, and 120 h was subjected to high-throughput sequencing to obtain transcriptome data. At various time points , gene transcription was measured in P. massoniana inoculated with PWN. At different time points, P. massoniana gene transcription differed significantly, with a response to early invasion by PWN. According to Gene Ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, P. massoniana response to PWN invasion involves a wide range of genes, including plant hormone signal transformation, flavonoid biosynthesis, amino sugar and nucleoside sugar metabolism, and MAPK signalling pathways. Among them, inoculation for 120 hours had the greatest impact on differential genes. Subsequently, weighted gene coexpression network analysis (WGCNA) was used to analyse transcriptional regulation of P. massoniana after PWN infection. The results showed that the core gene module of P. massoniana responding to PWN was “MEmagenta”, enriched in oxidative phosphorylation, amino sugar and nucleotide sugar metabolism, and the MAPK signalling pathway. MYB family transcription factors with the highest number of changes between infected and healthy pine trees accounted for 20.4% of the total differentially expressed transcription factors. To conclude, this study contributes to our understanding of the molecular mechanism of initial PWN infection of P. massoniana. Moreover, it provides some important background information on PWN pathogenic mechanisms.The pinewood nematode (PWN) The online version contains supplementary material available at 10.1007/s44154-023-00131-z. Bursaphelenchus xylophilus is listed as the only national first-class forest pest. Pinus provides us with many resources with ornamental, industrial and medicinal value. For pine trees, PWD is a devastating disease that is difficult to control. At present, there is no effective control method. Because most pine species in North America are resistant to pinewood nematode (PWN) B. xylophilus, infection due to geographical environment and other factors, PWN has little impact on pine trees  is one of the greatest threats to pine trees and is spreading worldwide. In China, the PWD pathogen Pinus massoniana is a significant conifer that produces oleoresin and lumber. The most commonly affected tree species in China by pine wilt is P. massoniana. The State Forestry Administration of China stated in 2022 that from the disease’s initial detection in Nanjing, China, in 1982, it had spread to 19 administrative provinces and resulted in significant economic and ecological damage  is a key insect vector of the destructive forest pest PWN, which has caused widespread and destructive PWD throughout Asia and Europe  of a pine sawyer beetle confer resistance to entomopathogenic Beauveria bassiana via fungal growth inhibition  transcription factor family is a class of transcription factors containing the MYB domain and is widely present in plants. When plants are subjected to external biological or abiotic stress, MYB family members recognize and bind to specific gene promoter motifs to activate transcription, improving plant stress resistance. For example, the MYB promoter conserved binding motif (A/C) ACC (A/T) A (A/C) C, AtMyb1 motif (A/C) TCC (A/T) ACC, AtMyb2 motif TAAC (G/C) GTT, AtMyb3 motif TAACTAAC, AtMyb4 motif A (A/C) C (A/T) A (A/C) C  was used to study the complex relationship between genes and phenotypes, the core genes at different stages were screened by constructing protein–protein interaction network analysis, and their role in pathogenesis was determined. The findings will be helpful for research on the early diagnosis of PWN and provide important reference data for research on the pathogenesis of PWN.High-throughput sequencing is a powerful tool to identify differential transcription of the whole genome under different conditions. Considering the importance of p < 0.05. Genes with differential expression were identified in the four samples T0h, T6h, T24h, and T120h, and they were compared in pairs. The number of differentially expressed genes between the groups is shown in the Wayne plot in Fig. Differential expression of genes was analysed by DESeq to determine how transcriptome data changed during the early invasion of pine wood nematodes into host pine trees. During the screening procedure, the following conditions were needed: expression difference multiple log2-fold change > 1 and significant P. massoniana-pine wood nematode interactions. After 6 hours of interaction, we found significant enrichment (p < 0.05) in several categories, including 622 upregulated genes and 444 downregulated genes in cellular component (CC), 686 upregulated genes and 389 downregulated genes in response to stimulation (BP), 1238 upregulated genes and 801 downregulated genes in metabolic process (BP), and 10 upregulated genes in cell killing (BP)  members (CC), including 573 upregulated genes and 541 downregulated genes; response to stimulation (BP), with 680 upregulated genes and 480 downregulated genes; cell killing (BP), with 13 upregulated genes and 0 downregulated genes; cellular anatomical entity (CC), with 982 upregulated genes and 915 downregulated genes; and multiorganizational process (BP), with 230 upregulated genes and 116 downregulated genes  in the extracellular region (CC), with 245 upregulated genes and 240 downregulated genes; cell killing (BP), with 23 upregulated genes and 1 downregulated gene; response to stimulation (BP), with 682 upregulated genes and 654 downregulated genes; membership (CC), with 562 upregulated genes and 677 downregulated genes; immune system process (BP), with 111 upregulated genes and 49 downregulated genes; multiorganizational process (BP), with 229 upregulated genes and 183 downregulated genes; and cationic activity (MF), with 974 upregulated genes and 1118 downregulated genes  in P. massoniana. By comparison with the T0h sample, the top 5 pathways with the highest abundance were found to be “plant hormone signal transduction”, “flavonoid biosynthesis”, “flavonoid and flavonol biosynthesis”, “amino sugar and nucleoside sugar metabolism”, and “cysteine and methionine metabolism” when pine wood nematodes invaded the host for 6 hours , gene interaction networks can be constructed to identify gene modules and their core genes. By analysing RNA-seq data, we identified key genes and modules involved in the response of P. massoniana was unclear. Pinus sylvestris core gene screening is therefore critical for the early diagnosis of pine nematode disease and the development of control strategies, and we constructed a protein interaction network (PPI) to further mine the core module genes at each time point  and correlated significantly with the 0 h, 6 h, 24 h, and 120 h samples Fig.  A. Regarint Fig.  B. Gene int Fig.  A, the gP. massoniana response play a linkage and defence function.GO enrichment and KEGG enrichment methods were used to annotate and enrich the core genes in these four modules. The genes of the MEturquoise module were mainly enriched in flavonoid biosynthesis, stilbenes, diarylheptanes, gingerol biosynthesis, and zeatin biosynthesis Fig. A, E. TheP. massoniana transcription , activating its transcription. MYB10 binds to the specific motif R6 (ACTGGTAG (T) C (T) TAT (A) T) in other gene-mutated apple strains, leading to stronger activation signals and increased anthocyanin accumulation  was injected into the hole with a pipette, and the hole was quickly wrapped with a sealing film to ensure no evaporation. The negative control of the experiment was drilled seedlings that were not inoculated with pine wood nematodes. After inoculation with pine wood nematode solution for 0, 6, 24, and 120 hours, the stem tissues at 3 cm above and below the inoculation point were taken as experimental samples, with three biological replicates for each treatment. Approximately 1 g of cut slices was transferred to a 1.5 mL tube for storage. All samples were stored at − 80 °C and later sent to Shanghai Parsono Biotechnology Co., Ltd. for eukaryotic transcriptome sequencing.Total RNA quality detection: Concentration and purity were detected using a NanoDrop spectrophotometer (Thermo Scientific NanoDrop 2000). Integrity was assessed using RNA-specific agarose electrophoresis or a 2100 assay .Total RNA with a total amount of ≥1 μg was selected, and the NEBNext Ultra II RNA Library Prep Kit for Illumina kit (strand-specific library building kit NEBNext Ultra Direct RNA Library Prep Kit for Illumina) was used. mRNA with polyA tails was enriched using oligo (dT) magnetic beads and then randomly disrupted using divalent cations. cDNA was synthesized using fragmented mRNA as a template and random oligonucleotides as primers. Purification of double-stranded cDNA followed by double-terminal repair and introduction of the ‘A’ base at the 3 ‘end and connection to sequencing connectors. AMPure XP beans were used to screen cDNA of approximately 400–500 bp, and PCR amplification was performed. The PCR product was purified again using AMPure XP beans, ultimately obtaining a library. An Agilent 2100 Bioanalyzer  and Agilent High Sensitivity DNA Kit  were used for library quality testing. By using Pico Green to detect the total concentration of the library , quantitative detection of effective library concentration < Thermo Scientific StepOnePlus Real Time PCR Systems> was performed by qPCR. After homogenization of multiple DNA libraries and equal volume mixing, the mixed library was diluted and quantified before performing PE150 mode sequencing using an Illumina sequencer.p < 0.05.Differential expression analysis between two comparative combinations was performed using DESeq software (1.20.0). Differential analysis of gene expression was conducted using DESeq, and the screening conditions for differentially expressed genes were as follows: expression difference multiple | log2FoldChange | > 1, significance p < 0.05) to determine the GO terms of significant enrichment for differential genes to determine their main biological functions. ClusterProfiler (3.4.4) software was used for KEGG pathway enrichment analysis, focusing on significantly enriched pathways with p < 0.05.GO enrichment analysis was carried out with the top GO, and P was calculated by the hypergeometric distribution method (the standard of significant enrichment was https://string-db.org/), protein interaction analysis was performed to reveal the interaction relationship between target genes. When the PPI information of the species is input, PPI pairs with differential genes and score > 0.95 are directly screened based on the results of gene differential expression analysis. When the network is too large or too small, the score value can be adjusted. When there is no PPI information for a species in the STRING database, similar species are selected to compare their protein sequences and then obtain interrelationships between their proteins. For transcriptome sequencing projects without a reference genome, similar species are selected to compare the unigene sequences of the species.According to the STRING database (https://horvath.genetics.ucla.edu/html/CoexpressionNetwork) was used to explore the complex relationship between genes and phenotypes(Langfelder and Horvath Weighted Gene Coexpression Network Analysis (-∆∆Ct(Schmittgen and Livak Randomly select genes from 10 core modules and calculate gene expression using 2Additional file 1.Additional file 2.Additional file 3.Additional file 4.


The resulting shoot and root growth and seed yield and quality were compared to a control (C). Both NPK + Hae + micro and PK + An treatments enhanced root growth in the top 20 cm soil layer at the ten-leaf stage: root dry biomass increased by 80 and 24%, respectively, and the volumetric root length density by 61 and 17%. The two treatments also allowed for a larger number of commercial seeds to be produced (on average +16 bags per gross hectare vs. C) owing to a better seed caliber, which consequently reduced rates of seed disposal  and, in the case of NPK + Hae + micro, due to an increment in the number of kernels per ear (+5% vs. C). These effects were not associated with any significant changes in shoot growth, height, or leaf net CO2 assimilation. In this preliminary trial, peak commercial benefit was obtained with the use of hydrolyzed epithelium together with macro- and micronutrients. Further investigation into application timing and dose, and the means by which these products alleviate the effects of low vigor and stress conditions observed particularly under mechanical emasculation is, however, necessary for their full exploitation in the production of hybrid maize seeds.Plants of inbred maize lines are characterized by low vigor due to their high rates of homozygosity and may, therefore, benefit from additional nutrients and biostimulants supplied via foliar spraying. The present study innovatively investigated the effects of foliar treatment with three commercial organic-mineral fertilizers/biostimulants on a male-sterile inbred line of maize at the five-leaf stage. The three fertilizers were characterized by their following content: ( The foliar supply of nutrients is recognized as one of the most efficient agronomic practices to alleviate nutritional deficiencies in plants caused by insufficient soil availability . The benFoliar application of nutrients allows small quantities of target elements, tailored to the specific requirements of the particular crop species at different growth stages, to be supplied directly to the plant. Adequate concentrations of nutrients can improve plant nutritional status, stimulate root growth, and enhance mineral absorption from the soil solution . Macro-nTrichoderma) are the most commonly used. These are also associated with the greatest beneficial effects [The application of plant biostimulants (PBs) represents another promising tool to enhance plant nutrition. When applied to plants, seeds, or soil, they have the ability to enhance flowering, plant growth, fruit set, crop productivity, and nutrient use efficiency (NUE). What is more, PBs have also been shown to improve tolerance against a wide range of abiotic stressors . PBs con effects ,10. When effects .Trichoderma spp., are now increasingly administered worldwide under both conventional and organic farming. Such fungi enhance the availability of different nutrients, including N, P, and micronutrients, and have also occasionally been observed to promote plant productivity [Initially implemented in horticulture due to the high commercial value of vegetables and fruits, foliar application of nutrients and biostimulants has been implemented at increasing rates in cereal crops such as wheat and rice in more recent years. For instance, late-season foliar N fertilization is steadily being adopted as a recommended farmer practice worldwide due to the resulting improvements in grain protein content and quality in common wheat flour and durum wheat semolina ,12. Amonuctivity .To date, foliar supply of nutrients and biostimulants has been little explored in maize, often focusing on low input management systems in developing countries ,14,15,16A further specialized application of foliar treatment with nutrients and biostimulants concerns inbred maize lines used for hybrid seed production. Here, the practice could counteract the low plant vigor associated with elevated homozygosity and improve seed production. In a previous study on inbred maize lines, foliar fertilization with N-P-K + Mg together with microelements and amino acids prevented phytotoxicity caused by post-emergence herbicides applied at the 5–6 leaf stage (V5–V6) . Accordii) NPK + hydrolyzed animal epithelium + micronutrients (named ‘NPK + Hae + micro’), (ii) NK + humified peat (named ‘NK + Hp’), and (iii) PK + Ascophyllum nodosum extracts (named ‘PK + An’). Foliar spraying was conducted at the five-leaf stage (V5). The main objectives of the research were to verify (i) the physiological response by measuring the leaf chlorophyll content across the season and net CO2 assimilation rate one month after treatment; (ii) the morphological response in terms of root growth and aboveground plant biomass; and (iii) whether possible plant improvements translate into higher hybrid seed yields and quality in terms of kernel caliber and germinability.Given such a background, the present study aimed to innovatively investigate the morpho-physiological effects of three commercial formulations of mixed mineral fertilizers and organic biostimulants in a non-emasculated male-sterile inbred maize line characterized by elevated homozygosity. The three products were characterized by their following content: (p ≤ 0.05) (2 net assimilation in the youngest leaf on July 17 at 31 days after treatment (DAT) (V10 stage), which was unaffected by the foliar treatment, although a slight but statistically insignificant increase in assimilation was observed with NK + Hp (+2% vs. C) and a slight and insignificant decrease with PK + An  ;  ≤ 0.05) . From miC; n.s.) .−1 of Control; 29 DAT), there were no statistically significant variations among treatments. Plant height was not affected by the treatments either .Even though above-ground biomass increased by 23% with the NK + Hp treatment (26.5 vs. 21.6 g dry weight (DW) plantp ≤ 0.1); in these plants, root biomass and length density increased by 23 and 17% vs. Control, respectively. On the contrary, the NK + Hp treatment reduced root expansion in both soil layers  and 48% in root dry biomass . This rol layers , althougp ≤ 0.05) and particularly ‘soil layer’ , were statistically significant in explaining RLD and RAD as well as root dry biomass. Their interaction (T × SL) was significant (p ≤ 0.05) for root dry weight and surface area due to the negative impact of NK + Hp  taken in parallel with soil corings (29 DAT) corroborated the positive effect of PK + An treatment on root growth, although with a lower and not significant variation (+13% vs. C) as compared with the morphological root measurements. NPK + Hae + micro and NK + Hp treatments allowed for a slight, albeit not significant, improvement in root electrical capacitance, i.e., up to +8% vs. C, in contrast to the results from the soil corings of NK + Hp treated plants .−1; p ≥ 0.05), whereas no differences were associated with the NK + Hp treatment (p ≥ 0.05)  per Gha showed slight but not significant improvements with the NPK + Hae + micro and PK + An treatments, i.e., +11 and +4% vs. C (5246 Kg of dry kernels Ghareatment . The eff ≥ 0.05) .p ≥ 0.05)  and the number of kernels per spike  were not affected by foliar treatments, although the NPK + Hae + micro and NK + Hp treatments increased the number of kernels per spike  .p ≥ 0.05).Regarding the commercial caliber of kernels, the percentage of L and M kernels did not vary significantly among treatments . Howeverp ≤ 0.05)  .As expected, the germination rate of kernels was generally higher in warm than in cold temperatures (99% vs. 95% in C). It was not a trait that was significantly affected by treatment, and rates were always >90% for both temperatures regardless of the treatment or lack thereof .The present study innovatively investigated the effects of early foliar application of three mixed mineral fertilizers and organic biostimulants on selected physiological and productive parameters in a male-sterile inbred line of maize. The aim was to verify their potential biostimulant properties and benefits on plant morpho-physiology and performance in order to better counteract the low vigor typical for inbred maize lines, while simultaneously ensuring high kernel quality within commercial standards.Ascophillum nodosum algae and animal epithelium, respectively. Contrary to expectation, no differences or even slight reductions of root expansion in comparison to the Control were observed with the use of NK + Hp, which contained humified peat. Humified peat contains humic and fulvic acids [The biostimulant properties of PK + An and NPK + Hae + micro were clearly evident at root level. These two fertilizers contained organic carbon from ic acids ,22, bothic acids . As a soic acids .Ascophyllum nodosum alga extract (PK + An) demonstrated the greatest root biostimulating effect, which was greater than that observed with the use of just P and K, also present in the two other commercial fertilizers/biostimulants. The beneficial effects of algae extracts on root growth of maize have previously been observed by Jeannin et al. [A. nodosum seaweed cream at different concentrations as a foliar applicant in potted maize plants. The said authors demonstrated an enhancement of root dry biomass with A. nodosum foliar application, and this was associated with a stronger sink capacity of the root apparatus. Increased root elongation, particularly of the finest roots, and greater root surface area together improved nutrient uptake, increased esterase activity, and elevated sugar content, as recently documented by Ertani et al. [2 assimilation, is documented here. Accordingly, no evident changes in shoot height or biomass were recorded in treated plants.The product containing n et al.  and Shukn et al. . Jeanninn et al.  used A. i et al. , who supi et al. , which wHowever, positive root responses with PK + An and NPK + Hae + micro treatments were associated with a moderate increase in the number of commercial seed bags per Gha. This was due to a slight increment in the number of kernels per spike under NPK + Hae + micro treatment, possibly related to its higher K content and micronutrients, such as zinc, which is recognized to be involved in phytohormone activity, seed production, carbohydrate metabolism, and protein synthesis . The amoAscophyllum nodosum in maize at different time points between the V8 (eight-leaf) and R1 (silking) stages reported a lack of evident improvement in plant performance [The choice of application timing is one of the main factors influencing foliar treatment efficacy. Fertilizer application at the V5 stage was not associated with a relevant increase in yield, even though Brankov et al. (2020) had previously identified this stage as the optimal one for maximizing biomass, leaf area index, and kernel productivity in comparison to later application timing at 11–12 leaves . Brankovformance . Maize cformance ,34. OptiNitrogen nutrition has a specific role in floret differentiation. An appropriate N rate can both increase N metabolism-related enzymatic activity and increase the glutamine and asparagine contents of leaves . This, iAnimal epithelium and animal waste in general represent a rich source of biodegradable C, N, H, O, and S. As opposed to utilizing the direct proteinaceous by-product associated with the livestock and poultry industries, enzymatic, chemical, and chemical-enzymatic hydrolysis of these, as was done for the epithelium content of the NPK + Hae + micro treatment in the current study, provides peptides of varying lengths as well as free amino acids . Indeed,The trial was carried out in 2020 on a male-sterile maize inbred line used as a seedbearing line for hybrid seed production (FAO class 700) at the “Ca’ Corniani” farm located at Caorle . The site was characterized by silty-clay-loamy soil, with the main characteristics described in Beyond low vigor, the studied seedbearing inbred line also suffers from leaf firing, which is responsible for early necrosis of leaf margins and consequent loss of photosynthetic capacity .−1 P2O5 and 55 kg ha−1 K2O were incorporated into the soil prior to sowing via harrowing. Sowing took place at the beginning of May at intervals of 22 cm along rows 75 cm apart, resulting in roughly 60,000 plants ha−2. The plots were dress-fertilized in mid-June with 230 kg N ha−1 in the form of urea, which was incorporated into the soil by means of interrow tillage. The a.i. Chlorantraniliprole and Lambda-Cyhalothrin were sprayed in mid-July to protect against the European corn seed borer  and later  with Indoxacarb to deter the Western corn rootworm (Diabrotica virgifera). Weed control was ensured by spraying the a.i. Mesotrione, S-Metolachlor, and Terbutilazina as a pre-emergence treatment just after sowing, and the a.i. Mesotrione and Nicosulfuron as a post-emergence treatment at the beginning of June.Following local recommendations, 85 kg hai) NPK + Hae + micro, (ii) NK + Hp, and (iii) PK + An, were applied to the male-sterile inbred line at the V5 stage by means of foliar spraying , resulting in a total of 16 plots. Each plot/replica measured 4.5 m across (6 rows of seedbearing maize plants) and 10 m along, for a total area of 45 m−2. Between each column/replicate plot, there were two rows of male maize line plants spaced 0.5 m apart.Three commercial mixed mineral fertilizers and organic biostimulants, here named  revealed lower temperatures (−1.3 °C) and abundant rainfall (229 mm vs. 78 mm), compared with the historical 10-year means . ConversThe leaf chlorophyll content was indirectly quantified as SPAD units, measured weekly on the last fully expanded leaf of five tagged plants randomly chosen in each plot/replicate, starting from one week after foliar application (V5 stage) until leaf senescence. This was done using a Soil Plant Analysis Development (SPAD)-502 chlorophyll meter  . Three m2 assimilation (A) was measured 31 DAT (17 July), on the last fully expanded leaf by means of an infrared gas analyzer LI-6800 . The measurement was undertaken on one plant per replicate per treatment. In order to fully evaluate the potential of photosystem II (PSII), the instrument was set with a pulsed actinic far-red light at 8000 µmol m−2 s−1 which ensured full excitation of photosystem I (PSI), thus allowing for complete discharge of electrons from PSII, thereby avoiding the initial dark adaptation of the leaf. The temperature of the leaf chamber was set at 27 °C, the relative humidity at 51%, and the air flow at 500 µmol s−1. The reference CO2 level was set at 400 μmol mol−1 and the photosynthetic photon flux density (PPFD) at 1500 µmol m−2 s−1 . Net CO2 assimilation (A) was determined following Murchie et al. [Net COe et al. .Plant height was measured weekly on the same five plants per plot (replicate) chosen for SPAD measurements. Plant height was taken from the soil surface until the latest visible leaf collar. Shoot dry biomass was determined at 29 DAT on 15 July, i.e., at the V10 stage, on one plant (cut at crown level) per plot (n = 4), after oven-drying at 105 °C for 48 h.The dynamics of root growth were monitored from the time of foliar treatment until the end of July by non-destructive measurement of the root electrical capacitance. Data were acquired weekly by a handheld digital electrical capacitance meter , following the methods described in Romdhane et al. . Electriv/v) before analysis [To investigate the main root parameters, one soil core  was collected at 29 DAT on July 15 (V10 stage) per plot. The soil cores were collected using a core sampler at a distance of 5 cm from the crown of a maize plant in the inter-row. Each soil core was split into 20 cm deep sub-samples  in order to effectively describe the rooting profile. Roots were separated from the soil particles by flotation with a hydraulic centrifugation device and collected in a 500 μm mesh sieve to be stored at 4 °C in an ethanol solution , and the number of kernels per unit seed weight (1 kg) were determined. The number of seed bags per Gha, each containing 80,000 kernels, was also determined for every sample considering the number of kernels per ear, the plant density (6 plants m−2), the surface area occupied by female plants (8400 m−2 ha−1), and the percentage of discarded kernels .Hybrid seed yield was measured on September 18 by collecting the ears over an area of 2.5 mFor each sample, the kernels were subdivided into two classes according to their caliber: large kernels (L), i.e., with a caliber between 8.0 and 9.4 mm, and medium-large kernels (M), i.e., with a caliber between 6.5 and 8.0 mm. The procedure was carried out by means of sieves with different mesh sizes according to the above thresholds. The kernels fitting neither the L nor M classes, that is, with a caliber <6.5 mm or >9.4 mm, were discarded as non-marketable kernels, and the percentage of discard kernels was calculated for each sample.For each treatment, the germination rate was determined for both caliber classes on 4 replicates consisting of 100 kernels each. Kernels were sown in a substrate of sterilized siliceous sand with a particle diameter of 0.05 to 0.08 mm, and a pH between 6.5 and 7.5 and kept in growth chambers. Germination was tested at two different temperatures, i.e., at a high temperature (25 °C) and a low temperature (12 °C). The first count of germinated kernels was carried out at 4 days after sowing (DAS), and the second and final counts were carried out at 7 DAS following the ISTA  protocol.p ≤ 0.05 with the Student–Newman–Keuls test.The data from all the assessed parameters were subjected to ANOVA with covariance analysis using Costat software . Separation of means was set at Foliar spraying represents a method with great potential for improving seed yield and quality in hybrid seed production in maize. The present study demonstrated that male-sterile inbred lines of maize could benefit from early foliar application of mixed mineral fertilizers and organic biostimulants, which partly reached the soil at the five-leaf stage of the plants. Products containing P, as well as K and/or algae extracts, exert a highly evident biostimulating effect in the roots of the shallow soil layers. This biostimulant effect can be translated into greater kernel numbers and, therefore, improved kernel productivity and a lower fraction of discharged kernels. However, optimal improvements in terms of the number of commercial seeds can be obtained when nutrients are combined with hydrolyzed animal epithelium, as in the fertilizer NPK + Hae + micro. Among nutrients, mineral N should be further included in fertilizer/biostimulant formulations, together with P and K and possibly some micronutrients such as Zn, to reach optimal effects. Nonetheless, root amelioration itself might be a premise for better counteracting the low vigor of inbred lines. However, much remains to be elucidated to enhance the application protocol for foliar application of these products. Confirmation of results in other growing seasons, as well as investigations into different formulations and doses, the number of applications, and the application timing within a longer experimental timespan containing later growth stages, is crucial. Such investigations are also necessary to ascertain the effects of foliar treatments under mechanical emasculation of male-fertile seedbearing inbred maize lines, with expected greater effects.


Breast cancer (BC) is the most prevalent tumor in women. Improvements in treatment led to declined mortality, resulting in more survivors living with cancer- or therapy-induced comorbidities. In this study, we investigated the impact of neoplasia and chemotherapy on resting energy expenditure (REE) and body composition, in relation to cancer-related fatigue. Inflammatory parameters were checked as possible explanation for changes in REE.T-test. The paired-samples T-test investigated the effects of chemotherapy from T0 to T1. A Pearson correlation analysis was conducted between REE, body composition, and fatigue and between REE, body composition, and inflammatory parameters. A linear regression analysis was fitted to estimate the contribution of the significantly correlated parameters. The measured REE at T0 and T1 was compared to the predicted REE to analyze the clinical use of the latter.Fifty-six women participated: 20 women with BC and 36 healthy controls. Patients were assessed at baseline (T0) and follow-up (T1) after 12 weeks of chemotherapy. Controls were measured once. REE was assessed with indirect calorimetry: body composition  by air plethysmography. The multidimensional fatigue index (MFI-20) was used to analyze fatigue. Baseline measurements of patients were compared to results of the healthy controls with the independent-samples At baseline, patients with BC had significantly higher REE in the absence of differences in body composition. From baseline to T1, REE and body weight did not change. In contrast, fat-free mass declined significantly with concordant increase in fat mass. Fatigue deteriorated significantly. C-reactive protein at baseline predicted the change in energy expenditure. Predicted REE significantly underestimated measured REE.Women with BC have higher REE in the tumor-bearing state compared to healthy controls. Chemotherapy does not affect REE but alters body composition. Predictive equations are invalid in the BC population. Results of our study can be used to implement personalized nutritional interventions to support energy expenditure and body composition and minimize long-term comorbidities. Globally, breast cancer (BC) is the most prevalent neoplasm in women , 2. DespWomen with BC who receive adjuvant chemotherapy (CT) are metabolically compromised. This altered metabolic profile in combination with drugs and lifestyle changes may lead to alterations in resting energy expenditure (REE) , 5. SeveEq) is often applied. The HBEq estimates REE based on anthropometric and demographic factors such as body height (BH), body weight (BW), sex, and age [Eq [Different methods have been developed to determine REE, amongst them numerous equations that predict REE (pREE) . In clin and age . Only in age [Eq . AlthougOne of the major challenges in cancer patients is to differentiate between tumor-induced changes in REE or and/or chemotherapy-induced changes in REE . This isTo investigate the energy expenditure and possible coinciding effects on cancer-related fatigue (CRF) and quality of life (QoL), we conducted a longitudinal prospective cohort study on women with BC, all receiving CT, and investigated absolute and relative levels of energy expenditure, body composition , and patient-reported CRF. We also examined inflammatory parameters, as possible explanations for metabolic changes. A better understanding of the potential side effects of CT may provide clinicians with more insight and help to counteract the possible debilitant effects of CT.2RUN) of Movant Research Group (University of Antwerp) in cooperation with the Multidisciplinary Breast Clinic of the University Hospital of Antwerp (Belgium).This approved study (Belgian registration: B300201837317) was conducted at the Multidisciplinary Metabolic Research Unit (MEq to predict REE (pREE) in the BC population before and after the treatment. Finally, the effects of a 12-week CT on CRF, and of blood parameters ; total lymphocyte count tTLC), neutrophile-to-lymphocyte ratio (NEU/LYM), C-reactive protein (CRP)), or tumor size at T0 on the outcome parameters related to energy expenditure and body composition were investigated.This prospective cohort study investigated the effects of a 12-week treatment period with paclitaxel chemotherapy  on energy expenditure, body composition, and fatigue. More specifically, we investigated absolute resting energy expenditure (mREE), mREE in relation to fat-free mass , metabolic state , anWomen diagnosed with primary BC were recruited from the Multidisciplinary Breast Clinic of the University Hospital of Antwerp (October 2020-September 2022). Participants were included when they were > 18 years of age, diagnosed with BC, and registered for neoadjuvant treatment with paclitaxel chemotherapy  with no prior treatment . Since the presence of the tumor in BC patients might influence our primary outcome parameters, a healthy control group was recruited for comparison at the start of the study. The healthy controls were recruited after advertising on social platforms . Eligible subjects were contacted by telephone and provided with baseline appointment at the laboratory. In- and exclusion criteria of both the patient and healthy control group can be found in Table All patients with BC were invited twice to the research facility. A baseline assessment at T0 of REE, body composition, and fatigue was executed before the first administration of CT, while the follow-up measurement (T1) was planned after 12 weeks of CT program.As a comparison, healthy volunteers were assessed only once at T0, to determine whether or not patients with BC had a tumor-induced difference in REE and scored differently in the domains of MFI-20. Indirect calorimetry (IC) was used to measure mREE, while air displacement plethysmography (BOD POD) was used for analyzing body composition . Fatigue was assessed by the multidimensional fatigue inventory (MFI-20).All assessments were executed in the morning (7h00am–11h30am). Participants were asked to be in fasted state (minimum 8 h without eating). Drinking water was allowed ad libitum until 2 h prior to the measurement. All subjects were asked to refrain from heavy exercise 24 h before the measurement. Each appointment lasted 1.5 h. Written informed consent was provided by each participant.The following data were collected or calculated from measurements in the laboratory, the patient’s medical record, or from an anamnesis : age (years); BW (kg); BH (cm); body mass index (BMI); weight status was determined according to the following reference values: underweight: BMI < 18.5, normal weight: BMI = 18.5–24.9, and overweight/obese: BMI ≥ 25.0; pREE . Calibration of the device was performed automatically every 30 min with span gas (18% O2 and 0.8% CO2) and nitrogen gas (100%). Validation of the system by methanol combustion was performed weekly [All IC measurements were done with an open-circuit diluted flow calorimeter (d weekly .3). Participants were instructed to lay in a semi-inclined position while staying awake. Minimal activity  was allowed. The room served as reservoir collecting 2 and 2. The measurement lasted 60 min, and data were provided every minute. Results of the last 50 min were used. 2 and 2 were converted to REE values . Data were collected as kcal/min and recalculated to kcal/24 h (absolute mREE) to determine relative mREE. Results on 2 and 2 can be found as supplementary material  [FM and FFM were assessed by air-displacement plethysmography  , 15. TheThe MFI is a 20-item self-report instrument to measure five dimensions of fatigue: General fatigue, physical fatigue, mental fatigue, reduced motivation, and reduced activity. Each dimension is covered by 4 items (questions). Participants were asked to score the items on a 5-point Likert scale. Each dimension received a score on 20, with higher scores indicating more fatigue on that specific domain. The grading system was analyzed with the validated scoring tool .Quantitative variables are expressed as mean ± SD. All data were checked for normality . Demographic characteristics include the following: age, BH, BW, obesity status (according to BMI), and metabolic state . Blood- or tumor-related parameters include the following: tNC, tLC, NEU/LYM, CRP, and tumor size. Metabolic parameters include the following: absolute mREE, relative mREE, and mREE/pREE; parameters related to body composition include the following: FM, FFM, and BW; and domains of fatigue include the following: general fatigue, physical fatigue, mental fatigue, reduced motivation, and reduced activity.T-test analyzed the difference in means of the demographic variables between BC and healthy controls at T0. The difference in means of measures of energy expenditure and body composition from T0 to T1 in patients with BC was analyzed by the paired samples T-test. The independent samples T-test analyzed the difference between the metabolic parameters and body composition parameters of BC and controls at T0. The paired samples T-test investigated the difference in means between absolute mREE and pREE, as calculated by the HBeq, to determine its validity in patients with BC at T0 and T1. The paired samples T-test was also used to analyze the difference in the five domains of fatigue in patients with BC from T0 to T1. In addition, the independent samples T-test was used to determine the difference in fatigue between patients with BC and healthy controls at baseline.The independent samples R2 change. All statistical tests are executed two-sided (significance: α < 0.05). Statistical analyses were performed with SPSS software .The correlation between the metabolic parameters, body composition, and fatigue, at T0 and T1, is expressed by the Pearson correlation coefficient (r). In addition, the correlation between the change from T0 to T1 (delta) of the metabolic parameters and body composition, blood parameters, and tumor size is also examined by the Pearson correlation coefficient. Next, a linear hierarchical regression model was fitted to estimate the contribution of the significantly correlated parameters to the change in aspects of energy metabolism and body composition. The individual contribution is expressed by the Fifty-six women participated in the study: 20 women diagnosed with BC, and 36 healthy women were enrolled in the control group. Six women with BC were lost in follow-up: two due to aggravation of their medical condition, and four were unable to attend the measurements at follow-up due to time constraints, leaving a total of 14 BC patients in the study.BC: 16.4 ± 12.3 vs. controls: 2.5 ± 7.0; p < 0.001).Characteristics of the study population and comparison of means between groups can be found in Table BC: 1596.8 ± 212.1 vs. controls: 1421.9 + 153.1; p < 0.001). The same was true for relative mREE (mREE/FFM) (± 10%) . The ratio between mREE and pREE also differed significantly . No significant differences in body composition parameters  were found between patients and controls at T0.At T0, absolute mREE was significantly higher (± 11%) in patients with BC compared to controls  and FFM%  were significantly lower in BC at T1 compared to T0, while FM%  was significantly higher at T1 . At T1, pREE underestimated mREE with ± 8.4% in patients  . Higher levels of general fatigue, physical fatigue, decreased motivation, and mental fatigue were also seen in patients, although differences were not significant  and mental fatigue  and report significantly decreased motivation  during chemotherapy treatment  and correlated low with FFMkg . Nonsignificant low correlations were found between absolute mREE and all other parameters of body composition. Furthermore, relative mREE displayed a significantly negative moderate correlation with FFMkg  but a significant strong positive correlation with mREE/pREE . The ratio mREE-pREE was strongly and significantly correlated with absolute and relative mREE, while the correlation with all other parameters was low and non-significant. General fatigue, physical fatigue, decreased motivation, and mental fatigue were not significantly correlated with body composition, absolute mREE, relative mREE, or mREE/pREE. For decreased activity, a significant low-positive correlation was found with FFMkg  and a moderate negative correlation with relative mREE . All other parameters were low but nonsignificantly correlated . Strong significant correlations were also seen between relative mREE and FMkg , absolute mREE , and mREE/pREE . BW correlated moderately with relative mREE . A significant negative correlation was found between relative mREE and FFM% . A strong significant positive correlation was seen for mREE/pREE with FMkg . FFM% was significantly moderate but negatively correlated with mREE/pREE , while BW correlated moderate and positively with mREE/pREE .At T1, absolute mREE, relative mREE, mREE/pREE, and FM%  and between decreased motivation and FMkg . All other parameters correlated low to moderately, but non-significantly, within the domains of fatigue  as did NEU/LYM at T0 . A moderate negative correlation was found for CRP at T0 and the change in absolute mREE , relative mREE , and mREE/pREE . A moderate negative correlation was found between tumor size at T0 and the change in absolute mREE , relative mREE , and mREE/pREE   = 8.311, p = 0.015). For relative mREE, the R2 was 0.733 with an R2 change of 0.537 (F(1.11) = 12.739, p = 0.004). For mREE/pREE, the R2 was 0.708 with an R2 change of 0.501 (F(1.11) = 11.027, p = 0.007) tNC at T0 which significantly predicted the change in BW with R2 was 0.768 and R2 change of 0.590 (F(1.12) = 17.240, p = 0.001) . The main and novel findings of this study are that patients with BC have a significantly higher resting energy expenditure prior the start of treatment with paclitaxel compared to healthy controls, and that treatment with paclitaxel had no additional effects on resting energy expenditure. We also found that the metabolic aberrations at baseline were present in the absence of significant differences in body composition between patients and controls. Furthermore, we found differences in body composition, e.g., body weight increased nonsignificantly, but FFMCRP: 9.09 ± 19.6 mg/L), we hypothesize that the higher REE is induced by inflammatory pathways as well, as previously shown by Madzima et al. [At present, we have no decisive explanation for the significant higher REE at baseline in comparison with healthy controls. However, tumor burden, determined by a.o. tumor location and size, affects energy metabolism subsequently . Our resa et al.  in similAn important aspect that needs to be addressed is that our patient population was significantly less active at baseline in comparison to the control group, while all other fatigue levels of the MFI-20 subdomains were higher in the BC group, although nonsignificantly. We have no clear explanation for the findings of a decreased level of physical activity without concomitant increases in any of the fatigue subdomains of the MFI-20 at baseline. However, although not further investigated in current study, we can hypothesize that mental fatigue negatively influences the level of physical activity as it affects exercise decision-making . Moreovekg: − 1.5 kg; FFM%: − 3.2%) and significant gain in FM% , without a concomitant altered BW (+ 1.6 kg), could be observed. Our findings on BW confirm the result of a meta-analysis by van de Berg et al. [After 12 weeks of treatment, a nonsignificant decrease − 73 kcal/day) in resting energy expenditure was seen in BC patients. This is in line with the findings of Harvie et al.  who obse kcal/dayg et al. , who repg et al. .In healthy adults, the contribution of FFM to REE is fivefold greater than the contribution of FM to REE . ConsideMuscle atrophy during CT is associated with an increase in inflammatory cytokines, such as CRP, and related higher energy expenditure . AlthougEq significantly underestimated REE measured by indirect calorimetry, confirming previous results [In clinical practice, measures of BW and body composition are useful outcomes to interpret results on REE at a single time point, but cannot detect inflammation and tumor burden which seem to affect energy expenditure as well . This mi results . Our finThis study has limitations worth discussing. First of all, the relatively small patient sample might have influenced our clinical results. Although the strength of our study is the measurement of REE in the tumor-bearing state before the start of chemotherapy, the short timespan between diagnosis and first administration impeded patient inclusion. More, patients were not screened on cancer-related cachexia before entering the study. With our inclusion criteria, however, we hope to have limited the risk of including cachectic patients, already metabolically compromised. Also, analysis of specific inflammatory cytokines (such as interleukins) could have provided more information to support our findings on inflammation. Additionally, we did not control for dietary intake. Consequentially, the results of the respiratory exchange ratio  could not be used, as it is highly influenced by nutrient intake on the previous days. Future studies should include RER as well, as it provides important information on the impact of chemotherapeutic agents on nutrient utilization, which will improve patient-tailored dietary advice. Furthermore, it is possible that repeated measurements (> 2) of energy expenditure during treatment unravels a dynamic pattern which is currently outbalanced. Finally, we included only patients that received neoadjuvant paclitaxel chemotherapy; other chemotherapeutic drugs and treatment regimens might have different outcomes.kg,% and concurrent increase in FM%. We hypothesize that tumor burden and inflammation mask the effects of diminished FFM on energy expenditure, and results in elevated REE levels. We promote the importance of precise assessment of REE by indirect calorimetry when adapting nutritional strategies, as the HBEq significantly underestimates the true energy needs in patients. Furthermore, a decrease in the level of activity was present in patients compared to the control group, with no difference in FFM. All other domains of fatigue were higher in the patient group and deteriorated significantly after 12 weeks of chemotherapy. Our results can found the basis for implementing supportive exercise and dietary rehabilitation during treatment with CT as it will promote the conservation/amelioration of body composition profiles, positively influencing both prognosis and cancer related QoL.Our study concludes that patients with breast cancer have significantly higher energy expenditure compared to healthy controls, and that a 12-week treatment regimen with paclitaxel chemotherapy did not alter energy expenditure, however, it had an impact on body composition. A non-significant increase in BW was seen alongside a significant decline in FFM


Small for gestational age (SGA) neonates are often born to mothers with pregnancy-induced hypertension (PIH). Here, we aimed to explore the morphometric characteristics of the placenta during the perinatal period associated with SGA risk in mothers with PIH and identify the risk factors related to SGA.The medical records of 134 neonates born between 28- and 32-weeks’ gestation to PIH mothers were retrospectively analyzed. Placental morphology and umbilical cord (UC) length were compared between the SGA and appropriate for gestational age (AGA) groups.z = −6.04, p < 0.01) and minor placenta axes , lower weight , smaller volume , and smaller area  than the AGA group. The UC was significantly shorter . Short placental major axis  and low placental weight  were independent risk factors for SGA in premature newborns of PIH mothers.The placenta of the SGA group had a shorter major (15.00 vs. 18.00 cm; A major axis shorter than 15.5 cm or placental weight lower than 347.50 g at birth was related to a greater risk of SGA infants born to PIH mothers. As a predictor in prenatal ultrasound, the major axis is more helpful for precise prenatal pre-evaluation of vulnerable SGA preterm neonates with PIH mothers. SmalPregnancy-induced hypertension (PIH) is a common and serious perinatal complication often leading to the birth of premature SGA neonates , 9. PIH The placenta supports intrauterine life and fetal development through its nutritional, immunologic, and endocrine functions . Existin2.2.1.This preliminary retrospective case-control research was performed in the neonatal department of a level 3 hospital in Beijing from January 2018 to December 2020. Ethical clearance (2021-KY-106-01) was obtained from the institutional ethical committee. Preterm SGA neonates with a gestational age (GA) of 28–32 weeks, born to mothers with PIH, were enrolled in the SGA group. Preterm AGA infants without intrauterine growth retardation, also born to mothers with PIH, were consecutively enrolled in the control group till two groups showed an even distribution for GA at birth. The exclusion criteria included (a) multiple pregnancies; (b) family history of inherited metabolic diseases; (c) abnormal test results in non-invasive detection of fetal chromosomal aneuploidy in maternal blood; (d) chromosomal or metabolic gene abnormalities diagnosed by chorionic villus sampling; (e) abnormality in deafness gene and hearing screening; (f) congenital malformation in the newborn; and (g) incomplete clinical records.SGA is defined when a newborn's birth weight is less than two standard deviations or below the 10th percentile of the mean for GA based on defined standards  for males and females –14. Pret2.2.Neonatal gender, length, weight, GA at birth; placental weight, length (major axis), width (minor axis), thickness, and length of the umbilical cord (UC); and mother's age at birth, mode of delivery, number of pregnancies and deliveries, perinatal complications  were obtained from the patients’ medical records. Methods of these measurements were referenced to the description by Barker et al. . Briefly2.3.a priori sample size was calculated and all the eligible participants during the study period were included.No 2.4.U test was used to compare non-normally distributed continuous variables  between SGA and AGA groups. Dichotomous data was compared between the two groups using the Chi-square or Fischer's exact test. Correlations between neonatal birth weight and the placental major axis, minor axis, area, volume, weight, and UC length were detected using Spearman rank correlation analysis. Potential risks and independent risk factors for growth retardation in preterm neonates with mothers of PIH were detected by univariate and multivariate logistic regression analyses, separately. The predictive accuracy of placental weight or major axis to estimate SGA preterm neonate birth to a mother with PIH was determined using receiver operating characteristic (ROC) curve analysis. Data was analyzed using SPSS Statistics for Windows, Version 21.0 . A two-sided p-value of <0.05 was considered statistically significant.Median (interquartile range) was used to show quantitative data. Absolute frequency (percentage) was used to show dichotomous data. Mann − Whitney 3.3.1.Between January 2018 and December 2020, 2,143 premature infants were hospitalized in the neonatal department of our hospital. Eighty-nine preterm neonates born between 28- and 32-weeks’ gestation to mothers with PIH were diagnosed with SGA. Sixty-five premature SGA infants were included in the SGA group according to the exclusion criteria. Sixty-nine premature AGA infants with matched GA, born to mothers with PIH were enrolled into the AGA (control) group, until GA of neonates in each group was evenly distributed. Hospitalization records of 134 premature Chinese infants and their mothers were complete for retrieval.p > 0.05). The neonatal birth length and weight in the SGA group were significantly lesser than in the AGA group . The rate of fetal distress was higher in the SGA preterm neonates than in the control neonates . The natural childbirth rate in the SGA group was significantly lower than in the AGA group . Other data regarding maternal information, such as age, gravidity, parity, primiparity, composition of subtype hypertension, gestational complications , and occurrence of abnormal amniotic fluid, showed no marked difference between both groups.z = −7.21, p < 0.01), smaller volume , smaller area , shorter major axis , shorter minor axis , and shorter UC length   and perimeter  showed no statistical difference between the SGA and control groups  . Placentl groups .3.2.ρ = 0.52, p < 0.01) and minor axes , area , volume , weight , and UC length .Spearman’s test  showed tp < 0.01; odds ratio (OR) = 1.84; 95% confidence interval (CI): 1.65 − 2.09), minor axis , weight , and UC length  were risk factors for growth retardation in premature infants of mothers with PIH. Multivariate regression analysis showed that short major axis  and low placental weight  were independent risk factors for SGA in premature newborns of PIH mothers . The median birth weight increased from 1,020 g for a placental weight of 200 to 2,047.80 g for a placental weight of 810 g. R2 = 0.303, p < 0.01). The median birth length increases with advancing placental weight from 37.15 cm at a placental weight of 200 g to 49.35 cm at a placental weight of 810 g. R2 = 0.278, p < 0.01). The median birth weight increased from 969.10 g for a placental major axis of 10 cm to 2071.30 g for a placental major axis of 30 cm. PIH mothers with shorter placental major axis at birth have a higher risk of giving birth to newborns with lower birth weight. R2 = 0.201, p < 0.01). The median birth length increases with the advancing placental major axis from 36.05 cm at the placental major axis of 10 to 45.45 cm at the placental major axis of 30 cm. PIH mothers with shorter placental major axis at birth have a higher risk of giving birth to newborns with shorter birth length.3.3.p < 0.01). With the optimal cut-off of 15.50 cm for the placental major axis, a sensitivity of 88.40% and specificity of 61.50% were achieved in the detection of SGA risk for preterm neonates born to PIH mothers. According to the cut-off value, we divided the subjects into two groups . The short placental major axis group tended to have a higher prevalence of SGA [83.33% (40/48) vs. 29.07% (25/86)] and a low percentage of AGA [16.67% (8/48) vs. 70.93% (61/86)] compared to the long placental major axis group.ROC curves were used to quantify marker  performance  in the pp < 0.01). The optimal cut-off value of placental weight for predicting the presence of SGA was 347.50 g, with a sensitivity of 84.10% and specificity of 76.90%. According to the cut-off value, we divided the subjects into the two groups . The light placental weight group tended to have higher prevalence of SGA [81.97% (50/61) vs. 20.55% (15/73)] and low percentage of AGA [18.03% (11/61) vs.79.45% (58/73)] compared to the heavy placental weight group.Areas under the ROC curve (AUC) indicated a good discriminatory power of placental weight , not the minor axis, was an independent risk factor for SGA in premature newborns of mothers with PIH in this study. These differences may be attributed to the placenta collected in these studies, which were from hypertension-complicated pregnancies in our study and from pregnancies without comorbidities in the above two studies .Furthermore, the surface area is also a critical placental parameter for fetal development because it determines nutrient transport and oxygen diffusion . In thisPlacental thickness is a controversial placental morphological parameter that has been widely investigated in many studies for its correlation with neonatal birth weight. An examination of 561 normal singleton pregnancies throughout pregnancy demonstrated that thick placentas are related to light birth weight and poor perinatal and infant outcomes . HoweverAmong the above parameters, short placental major axis and low placental weight were independent risk factors for SGA in premature newborns of mothers with PIH, which were associated with higher SGA delivery risks by 2.16 times and 2.68 times, respectively. As a diagnostic capability, the placental major axis for the prediction of SGA neonates has a sensitivity of 88.40% and specificity of 61.50%, while the placental weight for the prediction of SGA neonates is 84.10% and 76.90% for sensitivity and specificity, respectively. A placental weight lower than 347.50 g or a placental major axis shorter than 15.5 cm at birth was related with a greater risk of delivery of SGA premature infants to mothers with PIH. Our data showed that the placental major axis and low placental weight were reliable clinical indicators for SGA prediction. SGA neonates are more likely to experience adverse outcomes after delivery and even upon reaching adulthood . Early rThe UC is an important link between the fetus and the placenta. Compared with AGA term newborns, thinner (maximum diameter <0.8 cm) UCs were noted in SGA term newborns . Other UIn this study, we demonstrated the detailed morphometric characteristics of the placenta in a study of SGA preterm neonates of mothers with PIH. Furthermore, we revealed that lower placental weight and shorter major axis length were independent risk factors for SGA in premature newborns of mothers with PIH. The predictive value of these two parameters in predicting PIH-related SGA risk was also preliminarily explored. Since the length of the major axis is an easily obtainable ultrasonographic parameter and shows its potential to improve the prediction of the risk of SGA delivery, this research could be useful for monitoring the women with PIH. Furthermore, it could be helpful for the earliest possible intervention and management, not only during pregnancy but also after childbirth, and could prevent adverse neonatal outcomes as much as possible.Despite its potential clinical importance, this study has several limitations. The results were based on medical records obtained from one institution, and all neonates were Chinese. Due to the limited sample size, a classification study on the placental morphological characteristics of different subtypes of PIH-related SAG was not conducted. Furthermore, owing to the retrospective nature of this study, placental morphological parameters at different pregnancy stages were not collected. This research could be regarded as a preliminary exploration. Prospective multi-center larger cohort studies including neonates of various races should be conducted globally. The findings of this study should also be validated in larger cohorts. Further studies could also precisely determine when placental size and shape start to get affected during pregnancy in mothers with PIH who deliver SGA preterm neonates.