Helicobacter Pylori infection and change in lifestyle habits such as smoking, food storage and preservation (Gastric cancer (GC) represents the most prevalent malignancy in the globe with second highest mortality . GC to oervation . GC patiervation . On treaervation . In GC wervation . The proGastric cancer diagnosis is based on invasion extent of primary tumor (T-stage), lymph node status (N-stage), and distant spread (M-stage), also known as TNM system . HoweverWu et al, Ren et al., Zhang et al., Liu et al., Bao et al., Hongkun et al., Jeon et al., Yue et al.),. Among these reports, Ren et al describes the retrospective study to use of immunoscores to distinguish the outcomes in stage II and III colorectal cancer. Zhang et al. proposes to use the Lymph node metastasis (LNM) based staging system to predict prognosis in ampullary carcinoma (AC) cases where as Wu et al., note that the overall survival was comparable in N0 stage with N1 stage when less than 8 lymph nodes were present and therefore proposes to give emphasis in stage II colon cancer with less than 8 lymph nodes. Jeon et al., compares the surgical outcomes in surgical and pathological stages of colon cancer patients and infers that there is significant difference exists between surgical T4 and T3 in pathologic stage IIA.A total of 09 articles published on refinement of staging system ,. The published studies propose to use expression pattern of uniquely expressed genes to understand the clinicopathological features and accurately predict the survival. For instance, Wang et al., observed that USP22 expression in gastric cancer tissues is associated with lymph node and distant metastasis and TNM grade. Zheng et al., Lu et al. perform data analysis from the TCGA database to identify OAS1 to be overexpressed in pancreatic cancer tissue and associated with poor survival. Authors also conform the OAS1 expression in pathological tissues and note that apoptosis, Notch signaling and p53 pathways were associated with OAS1 expression. On similar note, Li et al. examines the expression of SOX30 in 195 CRC and adjacent tissues and observe that its expression was decreased in CRC tissue and negatively associated with tumor size and lymph node metastasis. This collection also features 04 review and systematic review of meta analysis articles ,. Kinami et al. summarizes the importance of determining lymph node metastasis in diagnosis of gastric cancer. Xi Jiang et al. reviews the anti-tumor effects of berberine (BBR) in CRC. Authors note that BBR exerts antitumor effect in CRC by regulating microbiota and mucosal barrier function and attest to use this drug for chemotherapy. In addition, Zhang et al., attempts to develop prediction model using vascular endothelial growth factor receptor 2 (VEGFR2) immunohistochemistry in 206 HCC patients. Authors also uses contrast-enhanced MRI parameters in predicting VEGFR2 expression. In another interesting study, Gao et al., uses bioinformatics approaches to examine the DNA methylation, copy number variation and regulated miRNAs of Gamma-aminobutyric acid transaminase (ABAT) in HCC. Author’s infer that ABAT expression was lower in HCC and miR-135a-5p may be the upstream regulatory miRNA for ABAT. Immunotherapy is well recognized treatment for HCC and know to improve therapeutic response. Presently, one of the attractive strategy is to use tyrosine kinase inhibitors synergizing with immune checkpoint inhibitors including anti-PD-1/PD-L1 (Zheng et al., screens 880 drugs to identify Anlotinib downregulates PD-L1 expression and may benefit with anti PD-1 inhibitor in clinical setting for GC.Prognosis in gastric cancer patients with identical TNM stage and receiving the similar treatment is observed to be different , present-1/PD-L1 . Zheng eTogether, the brief overview of the articles presented here provide the glimpse of updates on use of prognostic and clinicopathological factors in affecting the gastric cancer staging and eventually the treatment course.The author confirms being the sole contributor of this work and has approved it for publication.


Insomnia and short/long sleep duration increase the risk of AMI, but their interaction with each other or with chronotype is not well known. We investigated the prospective joint associations of any two of these sleep traits on risk of AMI. We included 302 456 and 31 091 participants without past AMI episodes from UK Biobank  and the Trøndelag Health Study , respectively. A total of 6 833 and 2 540 incident AMIs were identified during an average 11.7 and 21.0 years follow-up, in UKBB and HUNT2, respectively. Compared to those who reported normal sleep duration (7–8 h) without insomnia symptoms, the Cox proportional hazard ratios (HRs) for incident AMI in UKBB among participants who reported normal, short and long sleep duration with insomnia symptoms were 1.07 , 1.16  and 1.40 , respectively. The corresponding HRs in HUNT2 were 1.09 , 1.17  and 1.02 . The HRs for incident AMI in UKBB among evening chronotypes were 1.19  for those who had insomnia symptoms, 1.18  for those with short sleep duration, and 1.21  for those with long sleep duration, compared to morning chronotypes without another sleep symptom. The relative excess risk for incident AMI in UKBB due to interaction between insomnia symptoms and long sleep duration was 0.25 . Insomnia symptoms with long sleep duration may contribute more than just an additive effect of these sleep traits on the risk of AMI.The online version contains supplementary material available at 10.1007/s10654-023-00981-x. Globally, more than 8.9 million people die of coronary heart disease (CHD) each year . Some weIt is estimated that 33% of the population suffer from one or more insomnia symptoms, i.e. trouble falling asleep, frequent awakenings during night, or too early awakening , 12, andAlthough these sleep traits  are interrelated –24, mostGiven the complex relationship between insomnia symptoms, sleep duration and chronotype and the scarce amount of research on the joint associations of these risk factors on AMI, we prospectively investigated the joint associations of any two self-reported sleep traits together  on subsequent risk of incident AMI in two large population-based cohorts – the UK Biobank and the HUNT2. We also investigated the associations of these sleep traits individually on the risk of incident AMI in the same study samples.UKBB is a population-based prospective study of middle-aged adults (ranging from 40 to 69 years) recruited during March 2006–July 2010 and living within 25 miles of one of the 22 study assessment centres located throughout England, Scotland and Wales.More than 9.2 million individuals were invited and 502 460 participated. The participants signed an electronic consent and completed a touchscreen questionnaire along with a brief computer-assisted interview. They provided detailed information about their lifestyle, physical measures and had blood, urine and saliva samples collected and stored for future analysis, as described elsewhere .UKBB received ethical approval from the National Health Service (NHS) Research Ethics Service (reference number 11/NW/0382). The UKBB database was formed in accordance with the Declaration of Helsinki.All inhabitants aged 20 years or older were invited to participate during a four-phase population-based health survey (the HUNT Study) in the Trøndelag County of Norway, first in 1984–86 (HUNT1), then in 1995–97 (HUNT2), and 2006–08 (HUNT3), and last in 2017–19 (HUNT4). This study is based on data from HUNT2.In total, 94 187 individuals were invited during 1995–97 and 65 228 (69.3%) participated . The invThe HUNT Study was approved by the Data Inspectorate of Norway and recommended by the Regional Committee for Ethics in Medical Research . The ethical approval for conducting this study was also obtained from the Regional Committee for Ethics in Medical Research . The HUNT Study was conducted in accordance with the Declaration of Helsinki.In both UKBB and HUNT2, insomnia symptoms were defined as difficulty falling asleep, difficulty maintaining sleep or waking up too early without any related daytime impairment. Thus, our definition of insomnia is not aligned with established frameworks for classification of insomnia .In the UKBB, the participants were asked: “Do you have trouble falling asleep at night or do you wake up in the middle of the night?” with response options “Never/rarely”, “Sometimes”, “Usually” or “Prefer not to answer”, and 500 956 participants (99.7%) answered this insomnia symptoms question. Participants were classified as having insomnia symptoms if they answered “Usually”, otherwise they were classified as having no insomnia symptoms.In HUNT2, insomnia symptoms were assessed by the following two questions: “Have you had difficulty falling asleep in the last month?” and “During the last month, have you woken too early and not been able to get back to sleep?” with response options “Never”, “Sometimes”, “Often” or “Almost every night”, and 54 322 participants (83.3%) answered one or both of these insomnia symptom questions. Participants who responded “Often” or “Almost every night” to at least one of these questions were classified as having insomnia symptoms. For the participants in HUNT2 answering only one of the insomnia symptom questions, we did the following: (1) if they answered “Often” or “Almost every night” to one of the questions, but did not answer the other, they were classified as having insomnia symptoms, and (2) if they answered “Never” or “Sometimes” to one of the questions, but did not answer the other, they were excluded to avoid possible misclassification.In UKBB, participants were asked about sleep duration the last four weeks: “About how many hours sleep do you get in every 24 h? (please include naps)”. In HUNT2, participants were asked about sleep duration: “How many hours do you usually spend lying down (i.e. sleeping and/or napping) during a 24-h period?”. In UKBB and HUNT2, 498 245 (99.2%) and 53 203 (81.6%) participants reported their sleep duration, respectively. A three-level categorical variable was created defining sleep duration as “Short” (6 h or less), “Normal” (7–8 h) or “Long” (9 h or more) as per recommendations from the National Sleep Foundation . ExtremeIn UKBB, 496 281 (98.8%) participants reported chronotype . Chronotype was not reported in HUNT2. Chronotype was dichotomized categorizing the alternatives “Definitely a ‘morning’ person” or “More a ‘morning’ than ‘evening’ person” as “Morning” chronotype; and “More an ‘evening’ than a ‘morning’ person” or “Definitely an ‘evening’ person” as “Evening” chronotype. The alternatives “Do not know” or “Prefer not to answer” were excluded.In UKBB, follow-up for AMI incidence was conducted via linkage to the Hospital Episode Statistics (HES) for England, Scottish Morbidity Record (SMR) and Patient Episode Database for Wales (PEDW) where health-related outcomes had been defined by International Classification of Diseases (ICD)-9 and ICD-10 codes . Mortality information was obtained from NHS Digital for participants in England and Wales and from the NHS Central Register  for participants in Scotland where cause of death had been defined by ICD-10 codes (Field IDs: 40001 and 40000).In HUNT2, the participants were followed up for incident AMI, either identified at hospitals or by the National Cause of Death Registry. Hospitalizations for AMI were identified through a linkage with medical records from the three hospitals  of Trøndelag County in which health-related outcomes had been defined by ICD-9 and ICD-10 codes. Death records were identified by a linkage with the National Cause of Death Registry where cause of death had been defined by ICD-10 codes.Incident AMI was defined as the first occurrence of either hospitalization or death due to AMI between date of participation and end of follow-up. All participants with any episode(s) of AMI before their date of participation were excluded. We used ICD-9 code 410 and ICD-10 codes I21 and I22 to identify hospitalizations and deaths due to AMI before and after baseline. A flow chart of participant selection process for our analyses is summarized in Fig. Information on socio-demographic , education and employment status) and lifestyle factors ) was collected by means of a self-administered questionnaire. A clinical examination was conducted by trained staff where measurements on weight, height, and blood pressure were recorded and blood samples were collected.For UKBB, marital status was categorized as “Married” or “Unmarried”, while for HUNT2 it was categorized as “Married”, “Unmarried” or “Separated/Divorced/Widowed”. The information on alcohol intake frequency was categorized for “Never”, “Monthly”, “Weekly” or “Daily” alcohol intake. Smoking status of the participants were categorized as “Never”, “Previous” or “Current” smoker. Body mass index (BMI) was computed by dividing weight (in kgs) by the squared value of height (in metres) and was analysed as a continuous variable. The information on physical activity was categorized as “Low/inactive”, “Moderate” or “High” level of physical activity based on International Physical Activity Questionnaire (IPAQ) grouping. Education attainment was categorized as “Primary” (10 years or less), “Secondary” (11–13 years) or “Tertiary” (14 years or more) level of education. Information on shift work/night shifts was analysed as a dichotomous “Yes” or “No” variable. Employment status was categorized as “Employed” or “Not employed”. For UKBB, ethnic background was categorized as “White”, “Mixed”, “Asian/Asian British”, “Black/Black British”, “Chinese” or “Other” ethnic groups, to account for ethnic heterogeneity. We did not adjust for ethnicity in HUNT2, since the population of Nord-Trøndelag is mostly white (less than 3% non-Caucasians) . For UKBFurther details on how the covariates were handled are provided in the supplementary material.We analysed UKBB and HUNT2 separately. We used Cox proportional hazard models to examine the prospective associations of self-reported insomnia symptoms, sleep duration and chronotype individually on the subsequent risk of incident AMI. We then assessed the joint associations of two sleep traits together i.e., insomnia symptoms and sleep duration; insomnia symptoms and chronotype; and chronotype and sleep duration on the risk of incident AMI. Each participant was followed until either first incident AMI, death, loss to follow-up or until end of follow-up . We calculated the number of incident AMI events, person-years at risk and hazard ratios (HRs) with 95% confidence intervals (CIs) using different models adjusting for potential confounding factors.We reviewed the literature and created Directed Acyclic Graphs (DAGs) to select covariates that could cause both sleep disturbances and AMI. First, we adjusted for age and gender (Model 1). In our main model (Model 2), we further adjusted for marital status, alcohol intake, smoking status, BMI, physical activity, education, shift work/night shifts and employment status. We also adjusted for TDI and ethnicity in Model 2 for our analyses on UKBB. Lastly in Model 3, we additionally included systolic blood pressure, blood cholesterol levels, blood glucose levels, use of sleep medication(s), depression, and anxiety which may be both confounders and/or mediators for the associations under study. Because blood samples were non-fasting, blood laboratory investigations especially for cholesterol and glucose levels could be influenced by time between last meal and venepuncture, so we also adjusted for time since last meal in Model 3.We tested the proportionality of hazards using log-log curves and Schoenfeld residuals test. The joint associations of any two sleep traits together on the subsequent risk of incident AMI were assessed by using the relative excess risk due to interaction (RERI) with 95% CIs . In brieWe did formal tests for interaction between each sleep trait and their combinations with age (above and below 65 years) and gender. After reviewer comments, we also examined interaction due to shift work, depression (HADS-Depression score above and below 8 in HUNT2) and anxiety (HADS-Anxiety score above and below 8 in HUNT2). In addition, analyses stratified by age, gender, shift work, depression and anxiety were conducted.We performed several sensitivity analyses to assess the robustness of our findings. To reduce the possibility of reverse causality as an explanation for the observed associations, we repeated the analyses after excluding the first two years of follow-up. In another sensitivity analyses, we adjusted for any self-reported chronic disorders in Models 2 and 3, as sleep disturbances co-exist with certain illnesses and chronic pain . We repeThe statistical analyses were conducted using R version 4.1.1 for Mac OS .Baseline characteristics of the study population according to insomnia symptoms status are displayed in Table Among 302 456 UKBB participants without previous AMI, a total of 6 833 incident AMIs were observed during a mean (SD) follow-up period of 11.7 (1.9) years. Among 31 091 HUNT2 participants without previous AMI, a total of 2 540 incident AMIs were identified during a mean (SD) follow-up of 21.0 (6.5) years.The age- and gender-adjusted HRs and multivariable adjusted HRs with 95% CIs for incident AMI in relation to self-reported insomnia symptoms, sleep duration and chronotype are presented in Table Table HRs with 95% CIs for incident AMI in relation to the joint association of self-reported insomnia symptoms and chronotype within UKBB are presented in Table Table We found no strong statistical evidence of interaction by age for any individual sleep traits in both cohorts (Table S3). However, for the combination of insomnia and chronotype, we found that young or middle-aged adults (< 65 years), who were evening chronotypes without insomnia symptoms or morning chronotypes with insomnia symptoms had an increased risk of AMI compared to morning chronotypes without insomnia symptoms. We did not find the same increased risk of AMI in these phenotypes among the older participants (≥ 65 years). Additionally, we found no statistical evidence of interaction by gender, shift work, depression or anxiety (Tables S4–S7).When excluding the first two years of follow-up, a total of 6 089 and 2 390 AMI events were reported within UKBB and HUNT2, respectively, and the estimated associations remained fairly unchanged, but were less precise (Tables S8–S11). When adjusting for the presence of any chronic disorders, the effect estimates remained essentially unchanged, but were less precise (Tables S12–S15). When restricting the analyses to “White British” participants in UKBB (n = 269 375), similar findings were reported (Tables S16–S19). A total of 1 144 AMI events were reported in HUNT2 until December 31, 2008  follow-up period of 11.6 (2.5) years), and the estimated associations remained fairly unchanged, but were less precise compared to the complete follow-up period of 21.0 years (Tables S20–S21).This is a population-based study of self-reported insomnia symptoms, sleep duration, and chronotype involving two large European cohorts. In UKBB, we found that those who had insomnia symptoms, short/long sleep duration, or evening chronotype had an increased risk for incident AMI, compared to those who had no insomnia symptoms, normal sleep duration or morning chronotype, respectively. Although participants with the combinations of two sleep traits  had the greatest risk of incident AMI in UKBB, we found a synergistic association only for insomnia symptoms with long sleep duration. In HUNT2, we observed similar trends for incident AMI among those who had insomnia symptoms, short sleep duration or their combination, with less precise effect estimates possibly due to lack of power. We found no evidence of synergistic association due to the interaction between these sleep traits in HUNT2.Our findings for insomnia symptoms and risk of incident AMI are in line with that of a prior study on HUNT2 participants with an average of 11.4 years of follow-up, where individual insomnia symptom(s) and cumulative number of insomnia symptoms were associated with increased risk of incident AMI . CompareOur findings that short and long sleep duration moderately increased the risk of incident AMI, compared to normal sleep duration in UKBB, are consistent with findings from a prior study on UKBB with median 7.0 years of follow-up . We haveOur findings for evening chronotype and increased risk of incident AMI are consistent with evidence by Fan et al. , that foOur findings for the joint association of insomnia symptoms with short sleep duration and moderately increased risk of incident AMI are consistent with evidence from a cross-sectional study by Kalmbach et al. involving 3 911 subjects from Evolution of Pathways to Insomnia Cohort (EPIC) study . They foOur findings showing a synergistic association of insomnia symptoms with long sleep duration and increased risk of incident AMI in UKBB are consistent with a prospective study on this phenotype and incident CHD. Sands-Lincoln et al. followed 86 329 postmenopausal women aged 50–79 years from Women’s Health Initiative (WHI) Observational Study for a mean of 10.3 years. They found that women at high risk of insomnia symptoms, defined as WHI Insomnia Rating Scale (WHIIRS) ≥ 9, with 10 h or more sleep duration had 93% increased risk of incident CHD , compared to those at low risk of insomnia symptoms, defined as WHIIRS < 9, with 7–8 h of sleep duration . Since tTo the best of our knowledge, this is the first study to investigate the joint associations of chronotype with insomnia symptoms or short/long sleep duration on the risk of incident AMI and to investigate the statistical evidence for biological interaction beyond additivity due to the conjunct presence of these sleep traits. The conjunct presence of insomnia symptoms with long sleep duration may be a vulnerable phenotype contributing to a greater risk of AMI, than simply an additive effect of insomnia symptoms and long sleep duration.Sleep debt, which occurs through insomnia and short sleep duration, may result in glucose intolerance, decreased thyrotropin secretion, increased cortisol concentration, increased sympathetic nervous activity , and eleThe strengths of the current study include the use of two large cohorts with information on self-reported insomnia symptoms, sleep duration and chronotype, making it possible to examine the joint association of these traits on the risk of AMI. Incident AMIs were ascertained using linkages of the cohorts through hospital records and death certificates which minimizes the chance of misclassification. Moreover, we had rich information on possible confounders .The current study has several limitations. Sleep traits were not assessed objectively using validated measures such as actigraphy or polysomnography, which may have caused some measurement error. It remains therefore uncertain whether self-reported sleep duration in the present study represents time in bed or actual sleep time. However, sleep duration tends to be overestimated by actigraphy , and polOur study suggests that individual sleep traits i.e., insomnia symptoms, sleep duration and chronotype alone are important phenotypes associated with an increased risk of AMI, and we found evidence of an excess risk due to interaction for insomnia symptoms with long sleep duration. Insomnia symptoms with long sleep duration may be a vulnerable phenotype that needs to be further explored. Thus, subsequent studies investigating sleep problems on the risk of CHD/CVD should consider interaction between insomnia symptoms and long sleep duration, as investigating only one element may provide a partial recognition of clinically relevant sleep phenotype leading to their out of sight health consequences. We would also suggest further studies to apply a Mendelian randomization design using genetic variants as instrument variables for the sleep traits. Such studies could rule out limitations due to residual confounding and reverse causation. Also, studies aimed at exploring potential vascular and metabolic mechanisms behind insomnia, short/long sleep duration and chronotype are warranted to better understand association underlying AMI risk.Below is the link to the electronic supplementary material.Supplementary Material (DOCX 160 kb)


Tomato is an important vegetable crop and fluctuating available soil phosphate (Pi) level elicits several morpho-physiological responses driven by underlying molecular responses. Therefore, understanding these molecular responses at the gene and isoform levels has become critical in the quest for developing crops with improved Pi use efficiency. A quantitative time-series RNA-seq analysis was performed to decipher the global transcriptomic changes that accompany Pi starvation in tomato. Apart from changes in the expression levels of genes, there were also alterations in the expression of alternatively-spliced transcripts. Physiological responses such as anthocyanin accumulation, reactive oxygen species generation and cell death are obvious 7 days after Pi deprivation accompanied with the maximum amount of transcriptional change in the genome making it an important stage for in-depth study while studying Pi stress responses (PSR). Our study demonstrates that transcriptomic changes under Pi deficiency are dynamic and complex in tomato. Overall, our study dwells on the dynamism of the transcriptome in eliciting a response to adapt to low Pi stress and lays it bare. Findings from this study will prove to be an invaluable resource for researchers using tomato as a model for understanding nutrient deficiency.The online version contains supplementary material available at 10.1007/s44154-022-00035-4. Availability of phosphorus (P), an essential macronutrient, is one of the major limiting factors in crop productivity. Soil P exists in both the inorganic (Pi) and organic forms, and conversion to the Pi form is essential for absorption by plants , a Myb-like transcription factor, plays a central role in PSR -old seedlings were grown in hydroponic medium with (P+) or without (P-) supplemental Pi and grown for 1, 3, 7 and 9 d . If the scale-free topology fit index fails to reach values above 0.8 for reasonable powers  and the mean connectivity remains relatively high (in the hundreds or above), chances are the data exhibit a string driver that makes a subset of the samples globally different from the rest. The difference causes high correlation among large groups of genes which invalidates the assumption of the scale-free topology approximation. A higher scale-free topology of R2 greater than 0.9 was not achieved, and therefore 0.8 was set as the score for determining it. Co-expressed genes identified by this analysis are presented as modules, which can be further analyzed. For the analysis, we used all genes that had a total of 10 counts in all samples put together . In the root samples, the genes clustered into 65 different modules of which 20 are shown in Fig. The R package WGCNA  was used to find modules comprising genes of high correlation in root and shoot samples separately. For this analysis, all expressed genes from all samples were taken for the analysis. A Pearson correlation matrix was used to create a signed network with the TOMsimilarityFromExpr function. A signed network was created to ensure only positive correlations were taken into consideration. A soft threshold power of 7 was used as it resulted in a scale-free topology  and brown (2554 genes) modules show the genes with expression at basal levels 1 and 3 DAT and highly upregulated 7 and 9 DAT. The GO enrichment for the blue module contained the following terms, “water soluble vitamin metabolic process”, “kinase activity”, “protein phosphorylation” and “transferase activity”. In the brown module the terms “RNA metabolic process” and “senescence” were enriched. After resupply, eigengene expression in the blue and brown modules falls to levels similar to the eigengene level under Pi-replete condition at 9 d. These genes are those that are activated on long-term starvation. In the cyan module (281 genes), the eigengene expression is the highest at 1 and 3 DAT, and reduces at 7 and 9 d. A few enriched GO terms are “response to nitric oxide”, “lipid biosynthetic process” and “cellular response to reactive oxygen species”. The eigengene expression is reduced below basal level after resupply. In the greenyellow module (454 genes), the eigengene expression reduces in the first and third days, increases significantly at 7 d and falls at 9 d. After resupply the expression of the eigengene is reduced to near basal level. Some top GO terms enriched in this module are “magnesium ion transport”, “RNA interference”, and “response to wounding”. In the pink module (595 genes), the eigengene expression is activated after 7 and 9 d under Pi-replete condition. Under Pi-depleted condition, it is deregulated significantly at 7 and 9 d. The most enriched term in this module is “response to wounding” and other enriched terms are “response to biotic stimulus” and “immune system process”. It has been previously shown that Pi starvation can lead to suppression of the immune system which results in enhanced plant-microbe interactions  and 2482 and 2989 genes were downregulated (log2FC < − 1) in root and shoot, respectively. In the root, of all the genes that were upregulated at 9 d between Pi-starved and Pi-replete conditions (log2FC > 1) only three  were observed to be upregulated between Pi-starved and following resupply, while 974 were downregulated. GO analysis of the downregulated genes showed that most of the terms that were enriched under Pi starvation such as “response to starvation”, “transmembrane transport”, “cellular lipid metabolic process” among others, were enriched. The expression level of the rest of the genes (811) were considered to be deregulated to their basal levels. Some of the GO terms that were enriched among these genes were those that were related to “redox homeostasis” and “transcription factor activity”. On the other hand, while 73 genes stayed downregulated in resupply condition, 1153 genes were upregulated (log2FC > 1) in the genes that were downregulated between Pi-starved and Pi-replete conditions. The upregulated genes were enriched for terms such as “cell cycle” and “DNA replication” and other terms that were related to the functioning of the cell machinery. The expression of 1256 genes were reduced to their basal levels. The most enriched term in this set of genes was “response to stimulus”. A similar analysis in the shoot revealed that there were four genes that remained upregulated , 2082 were downregulated and 862 genes were brought back to their basal levels of expression. The genes that were downregulated were enriched for terms such as “response to stress”, “defense response” and “hydrogen peroxide metabolic process”, while some of the GO terms that were enriched for the genes that returned to basal level of expression were “oxidation-reduction process”, “defense response” and “response to stress”. Among the downregulated genes between the Pi-depleted and Pi-replete conditions in shoot, 20 remain downregulated in the resupply plants, while 1304 and 716 genes were either upregulated or restored back to their basal levels of expression, respectively. The most enriched term for the upregulated genes was “translation” and that for the genes that returned to basal level of expression was “glucuronate metabolic process” and “oxoacid metabolic process”.A total of 91 and 123 genes involved in ROS production and scavenging and MAP kinases, respectively, were identified from the tomato genome. The number of ROS related genes and MAP kinases that were reported to be differentially expressed by DESeq2 analysis is 45 and 41, respectively, in 7 d shoot samples. Of these, 25 and 14 ROS and MAP kinase genes, respectively, were expressed at levels higher or lower than two-fold. The number of genes that were upregulated more than two-fold was 12/9 (ROS/MAP kinases). Six ROS-related genes viz., Solyc03g117980.2, Solyc08g080940.2, Solyc11g072800.1, Solyc08g075540.2, Solyc01g067740.2 and Solyc09g091840.2, and five MAP kinase genes, Solyc12g088940.1, Solyc04g007320.1, Solyc12g009340.1, Solyc03g097920.1 and Solyc02g090970.1 are upregulated in shoot particularly at 3, 7 and 9 DAT . The leaf samples that were taken from seedlings subjected to Pi starvation displayed brownish coloration while the control samples showed no such accumulation , one MYB (Solyc10g086270.1) and the other a BHLH TF (Solyc09g065100.1), which are both probable positive regulators of the anthocyanin biosynthetic pathway. Some of the other important genes that were upregulated include ACC oxidase (Solyc01g067620.2), glutathione S-transferase (Solyc02g081340.2), 4-coumarate CoA ligase (Solyc03g117870.2), chalcone synthase (Solyc05g053550.2) and anthocyanidin synthase (Solyc08g080040.2). The MYB TF, Solyc10g086270.1, was upregulated in 3, 7 and 9 d Pi-starved shoot. Other genes that showed higher expression levels in these three time points were a UDP-glucuronosyltransferase family 1 protein (Solyc09g092500.1) and a cytochrome P450 (Solyc10g078220.1). The higher expression levels of several of these anthocyanin biosynthetic pathway genes corroborates with the increase in the anthocyanin content in the shoot.The alternative splicing landscape was also analyzed, particularly differential alternative splicing (DAS). This was done with rMATS and estimated five different AS events such as exon skipping, mutually exclusive exons, alternative acceptor, alternative donor and retained introns. The number of significant AS events (FDR < 0.05) is only marginally higher under Pi deficient condition than sufficient condition in both root and shoot tissue. The total number of AS events that were identified from 9128 genes was 81,500 from both root and shoot from an overall total of 25,658 intron containing genes Fig. . Of thesP value < 0.05). The number of genes that were upregulated in root and shoot was 3253 and 4789, respectively, and the number of genes downregulated was 3982 and 4620, respectively. There was a total of 6942 and 7795 genes differentially expressed in root and shoot, respectively. Taking into consideration both root and shoot tissues, 12,145 out of 35,358 (34.35%) genes were differentially expressed during the period of treatment. When comparing the DEGs with the DAS genes in root tissue, 1145 genes were identified in both data sets. A GO ontology analysis of these overlapping genes revealed that the most enriched terms were related to DNA repair. Some of the other enriched terms included those related to the lipid metabolic process, “response to stress”, “response to starvation” and “cellular response to stimulus”. These terms indicate that differences in the response to stress not only arises due to changes in differences in expression but also due to alternative splicing. A similar analysis with DEGs and DAS genes from the shoot tissue was also indicative of this fact. There was an overlap of 1346 genes and in this set of genes “organonitrogen compound metabolic process” was the most enriched. Interestingly, apart from the “lipid metabolic/biosynthetic process”, the GO term “superoxide metabolic process” was also enriched. So, here again it is clear that genes that are involved in stress response, are not only differentially expressed but also differentially alternatively spliced. Once the common genes that are both DE and DAS were analyzed for their role in low Pi stress related processes, the genes that were common among these common sets of genes from root and shoot tissue were also analyzed. There were 364 genes that were both DE and DAS that were found to be common in both root and shoot of tomato under Pi starvation.All the genes that were differentially expressed in the root and shoot tissues were identified , and the isoforms by their inherent difference in functional potential can have a major biological impact , which has been implicated in oxidation-reduction process including negative regulation of programmed cell death and iron-deficiency stress  terms in both root and shoot tissue. Although ROS accumulation is a consequence of several environmental stresses, the final response is fundamentally different and the activation of MAP kinases could be through multiple ROS pathways  is the only species that can traverse the plant membranes and therefore has the potential to function as a signaling molecule  (Solyc02g070020.1), one of the upregulated genes under Pi starvation, was also found to be one of the driver genes in the pink module. Ectopic expression of UGTs have been shown to increase anthocyanin accumulation and they have also been implicated in enhancing antioxidant activity thereby helping plants to cope with abiotic stresses , another gene upregulated in the shoot under Pi starvation and it has been reported that GSTs are required for the transport of anthocyanin  Solyc0g070020.1AtPHR1 mutation and could bind to the P1BS motif and was shown to interact with the promoters of SlPht1;2 and SlPht1;8  is being used increasingly for the creation of correlation networks for gene expression data generated by RNA sequencing. WGCNA can be used for the identification of modules of genes with high correlation and for eventually the summarization of such modules with the help of the module eigengene or the intramodular hub gene , one of the first genes characterized in tomato under Pi deficiency condition  and sulfoquinovosyl transferase genes, involved in lipid biosynthesis pathway, and the In addition to DEGs, genes that are DAS too are an integral part of the stress-response mechanism of a plant. This is consistent with a recent study showing that changes in transcript structure contribute to the transcriptome complexity in Arabidopsis plants under nutrient stress  accession Heinz1706 was used in this experiment. The seeds were disinfected with 20% bleach followed by thorough washing five times with distilled water before germination. The seeds were pre-germinated for 1 week before transferring to hydroponic solution containing: 2.5 mM Ca (NO3)2.4H2O, 1.25 mM K2SO4, 1 mM MgSO4.7H2O, 12.5 μM H3BO3, 2.25 μM MnSO4.H2O, 1.9 ZnSO4.7H2O, 0.25 μM CuSO4.5H2O, 0.1 μM Na2MoO4.2H2O, 0.13 μM KCl and (Fe-stock) 8 μM Fe (III)-EDTA with 250 μM KH2PO4 for Pi-sufficient condition and with 125 μM K2SO4 for Pi-deficient condition (i.e. 0 Pi). The germinated seeds were transferred to hydroponic medium with 250 μM Pi for 1 day. The following day, half of the seedlings were transferred to a medium with no Pi (0 μM Pi) for a period of 7 days. After 7 d, half of the seedlings from the Pi-deficient medium was transferred into medium containing 250 μM KH2PO4 for 2 d. Throughout the hydroponic experiment, the pH of the medium was adjusted to 5.7 and was renewed once every 3 days. The plants were grown in a growth chamber under controlled conditions at a temperature of 28/19 °C (16/8 h) day/night cycle and a relative humidity of 60–65%. Root and shoot tissues were collected from the plants separately 1, 3, 7 and 9 d after treatment. Samples from the resupply experiment were collected 2 d after treatment  in 50 mM Tris-acetate buffer, pH 5.0. Samples were incubated for 24 h at room temperature in the dark before transferring to 80% ethanol. Once chlorophyll was completely removed, the ethanol was replaced with 25% glycerol and the leaves were visually scored for color intensity. For trypan blue staining, the leaf samples were immersed in 0.4% trypan blue solution at room temperature for 8 h. The samples were decolorized by boiling them in a fixing solution (1 lactic acid: 1 glycerol: 4 ethanol) before image documentation.From root and shoot of tomato, total RNA was isolated using the RNAprep Pure Plant Kit (Tiangen). To eliminate genomic DNA contamination, DNAse was added during isolation of RNA. The quantity of RNA was ascertained using a NanoDrop 2000c Spectrophotometer (Thermo Fisher Scientific). For mRNA sequencing, three biological replicates were taken and each biological replicate included three plants. The samples were frozen in liquid nitrogen immediately after collection and stored at − 80 deg C until further processing. The NEBNext Ultra II Directional RNA library Prep Kit for Illumina (New England Biolabs) was used for generating the sequencing libraries with a starting material of 4 μg of RNA. Paired-end (150 bp) sequencing was performed using Illumina reagents at the Genomics Core Facility at the Shanghai Center for Plant Stress Biology following the manufacturer’s instructions.https://sourceforge.net/projects/bbmap/files/) with the following parameters: ktrim = r k = 23 mink = 11 hdist = 1 tpe tbo for adapter trimming followed by quality trimming with qtrim = rl trimq = 20 minlen = 25. Clean reads were mapped to the tomato genome build SL2.50 and the associated annotation (ITAG2.4) GTF file obtained from EnsemblPlants (http://plants.ensembl.org/Solanum_lycopersicum/Info/Index) using STAR version 2.5.3a . Only the gene-level read count information thus generated for the genes annotated (ITAG2.4) was used for differential gene expression analysis with DESeq2, an R/Bioconductor package   WGCNA package (v1.51) . Module detection was performed with default settings (mergeCutHeight of 0.15 and enabled PAMstage). The minimal module size was set to 30 genes. For each module, the expression profile of the module eigengene was calculated, which is defined as the first principal component of the module’s expression data. For each gene, the intramodular connectivity (kME) was calculated, which represents Pearson correlation of the individual gene with the respective module eigengenes.For the unsupervised WGCNA, only genes that have at least for one time point over all three replicates a DESeq2-normalized read count of at least 10 were considered. A total of 26,350 genes passed these filtering criteria. DESeq2-normalised counts then served as input for the network analysis. We used the function blockwiseModules, implemented in the R (https://plants.ensembl.org/index.html) using HMMER3.0 with default settings  sequences were identified from the tomato, rice, Arabidopsis and maize protein sequences downloaded from EnsemblPlants  . The cDNA was synthesized from 1 μg of total RNA using the Bio-Rad iScript reverse transcription kit, according to the manufacturer’s instructions. Real time RT-qPCR assay of the transcript levels was performed using the CFX Connect™ Real Time System (Bio-RAD). The Additional file 1.Additional file 2.Additional file 3.Additional file 4. Supplementary Fig. 1 Non-differentially expressed, alternatively-spliced genes showing isoform switching. The ROS-related gene Solyc06g068680 (A) and the MAP kinase gene Solyc02g093410 are alternatively-spliced and show IS, but are not differentially expressed.


The greatest absolute increase occurs for the Antarctic Peninsula with respective acceleration amplitude and energy trends ( ± 3σ) of 0.037 ± 0.008 nm s−2y−1 (0.36 ± 0.08% y−1) and 4.16 ± 1.07 nm2 s−2y−1 (0.58 ± 0.15% y−1), where percentage trends are relative to historical medians. The inferred global mean near-coastal ocean wave energy increase rate is 0.27 ± 0.03% y−1 for all data and is 0.35 ± 0.04% y−1 since 1 January 2000. Strongly correlated seismic amplitude station histories occur to beyond 50∘ of separation and show regional-to-global associations with El Niño and La Niña events.Ocean waves excite continuous globally observable seismic signals. We use data from 52 globally distributed seismographs to analyze the vertical component primary microseism wavefield at 14–20 s period between the late 1980s and August 2022. This signal is principally composed of Rayleigh waves generated by ocean wave seafloor tractions at less than several hundred meters depth, and is thus a proxy for near-coastal swell activity. Here we show that increasing seismic amplitudes at 3 Ocean waves induce geographically extensive seafloor forces that excite a continuous and globally detectable seismic wavefield. This study infers global near-coastal average wave energy intensification at a rate of 0.27% per year since the late 1980’s, and 0.35% per year since January 2000. Mid-20th century studies established phenomenological understanding of the distinct ocean wave to solid Earth source coupling processes responsible for the primary (≈14–20 s) and secondary (≈6–12 s) microseism period bands. Microseism signals occur at much longer periods than typical anthropogenic seismic noise2 and thus constitute an ocean-state proxy that is well recorded by seismographs essentially everywhere on Earth.Earth’s seismic wavefield was revealed by the late 19th century to be incessantly excited at periods between ~8 and 30 s. It was well established by the 1960s that seafloor forces due to wind-driven ocean gravity waves are the principal source of seismic waves in this period range in the absence of earthquakes or other large transient events, and that this microseismic wavefield is primarily composed of seismic surface waves5. Ocean waves in this period range have wavelengths λ in the range of 300–600 m, and their dynamic pressure field decays exponentially with depth at a rate determined by the wavenumber-depth product. The primary microseism spectrum6 matches the swell spectrum of partially to fully developed seas excited by worldwide storm systems, and microseism amplitudes reflect near-coastal seafloor tractions influenced by swell amplitude, propagation direction, and/or wave period. The distinct and more energetic secondary microseism between ~6 and 12 s, not analyzed in this study, has been investigated more thoroughly than the primary mechanism. It arises from wave period-shifted pressure perturbations on the ocean floor generated by generalized standing (clapotic) components of the ocean wavefield resulting from swell interference. These standing wave components may be generated by wave interactions occurring within a single translating storm system, between swell arising at multiple storm centers, or between incident and reflected waves due to coasts7. Notable efforts in the theory and numerical modeling of seismic ocean source processes in recent years have sought to more thoroughly incorporate necessary elements of seafloor bathymetry, physical oceanography, and seismology11 to refine the understanding of the ocean swell wavefield responsible for the secondary microseism and the influences of water depth, wave propagation direction, seafloor slope, and general bathymetry on primary and secondary microseism generation13.Global microseism signals are generated by two distinct source processes. The primary microseism between ~14 and 20 s is excited by normal and shear tractions due to dynamic pressure variations of ocean swell on the near-coastal seafloor∘ and 80∘ S15. Relevant factors vary geographically over multi-decade timescales under the influence of troposphere and ocean warming21 with14 estimating that global wave power has on average increased by 1.087 × 103 kW m−1 y−1 and correlates strongly with sea surface temperature for 1948–2008. The microseism wavefield arises from geographically distributed forces applied to the seafloor by wind-driven ocean wave activity and is thus a proxy for the ocean wave state that complements surface and remote measurements6. This indicates that secular and other trends in ocean waves state are expected to be globally reflected in seismic data. Microseism-based wave state studies spanning shorter timescales than presented here have identified spatiotemporal trends in storm intensity, duration, and tracking26, and have been applied to estimate high-latitude sea ice variations and associated ocean wave attenuation28. Wave state is modulated by inter-annual climate processes31 and extreme microseism intensity associations, particularly with El Niño (ENSO) states, have previously been noted using shorter duration data sets25. However, global evidence for widespread secular intensification of microseism amplitudes has not been previously documented.Increasing ocean basin surface wind speeds since the mid-20th century have been inferred from meteorologic, oceanographic, and satellite altimetry data. The greatest wave powers and power increases are attributed to the Southern Ocean between 40In this work, we assess primary microseism intensity since the late 20th century using data from globally distributed research and monitoring seismographs. We demonstrate a strong prevalence of increasing seismic amplitudes and energies at rates that are consistent with ocean wave intensification estimates from other disciplines. We additionally perform a correlation and clustering analysis of seismic amplitude time series to demonstrate that the primary microseism signal is a consistent proxy for long-range ocean wave spatial and temporal variability.32. The PSD estimation methodology is similar to that of ref. 33 but does not implement smoothing or binning beyond the inherent frequency discretization and spectral leakage properties of the discrete Fourier transform. We calculate seismic spectra in 1-hour 50% overlapping windows from continuous long-period high-gain vertical component (channel LHZ) 1 sample per second seismic data, which is insensitive to Rayleigh wave propagation direction, recorded by primary station sensors (location code 00) retrieved from the EarthScope Data Management Center (DMC) from the IU34 and II35 networks. Additional detail on spectral estimation is included in Methods.We calculated microseism metrics from power spectral densities (PSDs) through 1 August 2022 using the section averaging method applied for the conterminous United States in ref. 36 and large shallow events produce strong seismic surface waves that overlap with the 14–20 s primary microseism period band38. We remove potential earthquake transients from global earthquakes with magnitudes ≥5.75 using origin times and magnitudes from the U.S. Geological Survey Comprehensive Catalog of Earthquake Events and Products (ComCat)39 to cull intervals during which the primary microseism may be obscured. ComCat event selection is based on W phase40 moment magnitude Mww or on body wave magnitude mb for smaller earthquakes, and we remove data for all stations beginning at the earthquake origin time for 3, 6, 12, 24, and 48 hours for magnitude ranges 5.75 ≤ M ≤ 7.0, 7.0 ≤ M ≤ 7.5, 7.5 ≤ M ≤ 8.0, 8.0 ≤ M ≤ 9.0, and M ≥ 9, respectively. These data removal windows are highly conservative given that the global transit time for surface waves in this period range is about 3 hours and only very large earthquakes produce significant multi-circumglobal signals37.Global earthquakes occur with a clustered Poissonian time distribution41, applying an acceptance corridor for the primary microseism period band between five times that is predicted by the (only rarely reached) low-noise model and 50 times that are predicted by the high-noise model.Seismic data contain calibration pulses that produce values that greatly exceed naturally occurring levels, and may also contain periods of nonphysically low or high amplitude values corresponding to local physical disturbances or technical malfunctions. We remove these nonphysical outliers by comparing integrated signal power to the global New High-/Low-Noise models (NHNM/NLNM) of ref. 28. We characterize stationary annual variations as a standard Fourier series representation H(t) in which the Fourier coefficients for the tropical year fundamental and its first three harmonic coefficients are estimated by projecting microseism amplitude A(t) or energy  E(t) time series onto orthogonal trigonometric basis functions at periods T0, T0/2, T0/3, and T0/4 to obtain corresponding coefficients ai and biT0 = 365.242 days. Aperiodic sampling and data gap tolerant Lomb-Scargale PSD analysis42 of daily sampled median acceleration amplitude time series and examination of decaying coefficient  amplitudes confirmed that four Fourier terms were sufficient to characterize all significant spectral lines for our purposes.Seismic data commonly exhibit large annual variability in microseism intensity corresponding to the winter development of extratropical cyclonic storms, high-latitude formation of sea ice, and other seasonal factorsℓ1-norm minimizing; see Methods) trend estimation to progressively processed data sets for each station. The removal of short data intervals using (1) earthquake catalog and (2) noise model determined outlier procedures, as described above, produces trend estimates with lesser uncertainties but does not appreciably affect overall assessment of global seismic amplitude and energy trends nor the conclusions of this study  functioℓ1-norm minimizing linear trend determination. We obtain trend estimates for signals within the primary microseism band (14–20 s) at global broadband seismic stations selected solely for operational histories exceeding 20 years and data completeness exceeding 80%. These selection criteria allow for the estimation of primary microseism trends at 52 globally distributed stations (Table Hourly time series as described above are smoothed using a two-month 61-day) moving median in daily steps to produce 1 sample per day series signals for -day moviA(t)   and velocity squared E(t) trend results , 41 stations (79%) show positive and 8 (15%) show negative slopes at 3σ significance  and E(t)  Fig.  with ℓ1- RA Fig.  for each RE Fig. . CorrespRA, RE; Tables σ uncertainties range from  at PMSA  to  at HKT. Trends exhibit a modest (correlation coefficient of 0.213) proportionality in that stations with high historical median primary microseism amplitudes , and for sites in the extratropical southern hemisphere. Stations with significant negative trends are restricted to the northern and western Pacific Ocean regions and to two sites  in the southern United States. Seismic acceleration and velocity squared trends  and at central North America station RSSD  at 0.837 ± 0.090 and 0.810 ± 0.088% y−1, respectively (Table −1) is not as high as at other  stations  which are expected to have sensitivity to the state of the Southern Ocean  when the analysis is restricted to post 1 January 2000 data . High absolute microseism amplitude increase rates for southern stations such as TAU , PMSA , and PTCN (Pitcairn Island) are sustained in these later data and are consistent with studies showing increasing surface winds in the far southern hemisphere20. Negative primary microseism amplitude trends in parts of the north and west Pacific region generally continue in the post-2000 era. This may reflect decadal-scale reanalysis and in situ observation supported conclusions of decreasing wave height in this region since the mid-1990s attributed to the strengthening of the negative phase of the Pacific-North American teleconnection between about 1996 and 2012 ) 45.Southern US stations TUC  and HKT , which were the most negative trending stations for the complete data interval, both change significantly (with TUC becoming positive at 3σ significance).To examine a uniform interval during which all stations were in operation , Pacific Decadal Oscillation (PDO), Western Pacific Oscillation (WPO), and Atlantic Multidecadal Oscillation (AMO) time series and did not find comparably strong correlations for these indices with microseism amplitudes.Cluster and global station stacks of amplitude and energy time series reveal correlated multi-year variations in near-coastal wave energy over the past 34 years in the primary microseism. We demonstrate this with a zero-lag correlation-based dendrogram analysis using detrended and demeaned 61-day-median smoothed vertical component acceleration time series with stationary annual harmonic functions , 2010–2011 (La Niña), 2015–2016 (El Niño), and 2020 (La Niña)  water waves decays with depth z asp(z) = 0.05 by z/λ ≈ 0.48, and ocean regions for which the 14–20 s period primary microseism source mechanism is active are wavelength-dependent and correspondingly restricted to coastal and continental shelf regions with z < 150–295 m. This constitutes ~11% of the global seafloor lying almost exclusively along continental and island coasts  and array methods have been shown to image primary and secondary source regions at regional to global scales48 and offer further impetus for improved modeling and model validation. The rate of median microseism amplitude and energy increase is a fraction of a percent per year and long-period global-scale seismic wave propagation characteristics are temporally invariant. Given these conditions, we suggest that ocean wave and seismic energy in these observations should be proportional, and specifically that changes in median primary microseism energy at the 61-day averaged scale as examined here will be proportional to similar time scale and geographically integrated changes in median ocean wave energy expressed as seafloor tractions across Earth’s coastal regions.Spatio-temporally oscillatory tractions across variable bathymetry integrate to non-zero long-spatial wavelength seismic source terms, with the strongest coupling occurring at geographically limited . Seismi49 and inferences from carefully processed satellite altimeter data. Data integration and joint assessments of both ocean-wide and coast-proximate sea-state are expected to be increasingly fruitful as data quality, density, and analytical methodologies improve for multiple types of observation.Primary microseism observations at a variety of spatial and temporal scales constitute a period-dependent and complementary near-coastal-sensitive metric to multi-decade sea-state data collected at fixed ocean buoysPE and corresponding seafloor tractions increase across 52 long-operational seismograph sites is 0.27 ± 0.03% y−1 for the entire historical data set beginning in the late 1980s and 0.35 ± 0.04% y−1 for post 1 January 2000 data. These estimates are geographically biased towards the high PE North Atlantic region by historical seismographic station density 2/Hz. We estimate microseism band square root integrated power by integrating the hour-long PSD estimates in microseism period bands using the trapezoidal rule and then obtain a time series of the band-limited root power in acceleration units (ms−2). Acceleration spectra are integrated in the frequency domain and squared to obtain seismic energy metrics. Integration to velocity to estimate the velocity squared energy proxy does not have a large effect on proportional amplitude trend statistics but makes metrics more sensitive to lower-frequency signals and produces a secondary effect on station trend ranking  networks ICℓ1-norm metricm is the 2-parameter model vector specifying the linear trend intercept and slope, G is an n by 2 system matrix consisting of a first n-length column with each element Gi,1 = 1 and a second n-length column Gi,2 = ti where ti is the time of the ith data point, and d is an n-element acceleration amplitude or seismic energy time series vector. We do not interpolate across data gaps. The slope and y-intercept parameters and their covariance matrix C are estimated using iteratively re-weighted least squares (IRLS)61 implemented via the robustfit function of MATLAB®. C is estimated from the convergent least-squares solution of the weighted IRLS equations.The robust parameter estimates in this study solve for intercept and trend (slope) parameters for the linear function that minimizes the outlier-resistant 62 in which each iterative linking step minimally increases the total within-cluster variance of the time series. The associated separation metric used in the MATLAB® linkage function is Cij is the correlation between time series i and j.Dendrogram associations between the microseism acceleration and climate index time series . After installation, responses are subject to calibration and consistency tests that have included Earth tides66, observations of normal modes such as 0S0 from great earthquakes67, and continuous use and consistency checking of the network for the location and quantification of earthquake sources, seismic tomography, and other applications. The EarthScope DMC also continuously calculates and monitors frequency-dependent quality assurance metrics for GSN and other stations in its ongoing operations65. Time-dependent gain reductions68 in the early GSN noted in a systematic study of MW > 6.5 earthquakes were traced69 to humidity-related corrosion in feedback electronics in a few percent of Streckheisen STS-1 very broadband sensors. These issues were documented and corrected in the field, and effects on station responses occurred at longer periods than those analyzed here. Anomalous limited  contiguous time periods associated with apparent system malfunctions or incorrect metadata were observed at ten stations after inspection of overlapping hourly PSD integral time series and were excised  is jointly operated and maintained by the EarthScope Consortium under funding from the U.S. National Science Foundation and the U.S. Geological Survey. This study utilizes authoritative metadata retrieved for GSN stations from the EarthScope data management system to convert time series counts to physical units. The network incorporates instrumentation configurations that have been increasingly and asynchronously standardized over time. Seismic sensors and data loggers in the network are subject to acceptance testingSupplementary InformationPeer Review File


This decline is often attributed to reduced CO2 conductance, increased CO2 loss from photorespiration and respiration, reduced chloroplast electron transport rate (J), or deactivation of Ribulose-1,5-bisphosphate Carboxylase Oxygenase (Rubisco). However, it is unclear which of these factors can best predict species independent declines in An at high temperature. We show that independent of species, and on a global scale, the observed decline in An with rising temperatures can be effectively accounted for by Rubisco deactivation and declines in J. Our finding that An declines with Rubisco deactivation and J supports a coordinated down-regulation of Rubisco and chloroplast electron transport rates to heat stress. We provide a model that, in the absence of CO2 supply limitations, can predict the response of photosynthesis to short-term increases in leaf temperature.Net photosynthetic CO 2 assimilation rate with rising temperatures can be accounted for by Rubisco deactivation and declines in chloroplast electron transport rate.Photosynthesis declines at mild temperatures in terrestrial plants. Here, the authors use published data to show that decline in photosynthetic CO Photosynthesis (net CO2 assimilation—An) is particularly susceptible to heat stress, and the temperatures at which An decreases are well below those for comparable leaf metabolic processes like respiration3. The Farquhar, von Caemmerer, and Berry C3 photosynthesis model (FvCB model)4 is a powerful tool for predicting the response of An to environmental perturbations, and for determining what aspects of biochemistry limit photosynthetic rate and capacity. The FvCB model predicts An based on the minimal rate generated from Rubisco carboxylation reactions (Ac), Ribulose-1,5-bisphosphate (RuBP) regeneration associated with chloroplast electron transport rate (Ar), and triose phosphate utilisation (Ap)5. The model accounts for declines in An above the temperature optimum of photosynthesis (Topt) based on concomitant declines in chloroplast electron transport rates (J)4, which has been linked to heat damage of thylakoid membranes7. However, other studies suggest that Ac can be a greater contributor than Ar to the loss of An when leaf temperatures exceed Topt8. Deactivation of Rubisco and its impact on Ac has long been suspected of contributing to An inhibition above Topt9. Indeed, an analysis by Crafts-Brandner and Salvucci10 noted that declines in An with leaf heating occur well before expectations based on Rubisco kinetics, and are instead consistent with the temperature dependence of Rubisco deactivation. Further experiments and modelling have identified Ac as the rate limiting step in some instances, while other studies have implicated Ar due to declines in J with rising temperatures12. Whether Ac or Ar determines An above the Topt is often attributed to interspecific differences or environmental factors such as nitrogen availability, growth temperature, and ambient CO2 concentration13. An alternative possibility is that Ac and Ar are both regulated to be co-limiting. For example, Sage14 proposed and observed15 synchronised Ac and Ar biochemical adjustments within minutes of altering irradiation and CO2 concentrations.The rapid rise in leaf temperature during a heatwave has detrimental impacts on plant performance2 and the light dependent generation of RuBP be impaired by heat, but the availability of CO2 substrate at the site of assimilation can fall and become limiting. Reduced An due to falling intercellular and chloroplast CO2 concentrations following heat-associated rises in vapor pressure differences between leaves and air have been observed18. Additionally, foliar CO2 loss from photorespiration and respiration in the light (RL) may contribute substantially to declining An under high temperature19, as both processes rise sharply with warming21. From a modelling perspective, this means that for each new temperature, several parameters must be treated independently and updated. Despite, or perhaps because of, the above numerous aspects of photosynthetic metabolism that are impaired by heat, it is difficult to establish a general predictor for the decline in An at relatively moderate temperature applicable across many higher plants.Not only can the capacity of Rubisco to fix COVcmax) is a key parameter in the FvCB model22. Gas-exchange estimates of Vcmax increase exponentially with temperature before peaking and then declining at higher temperatures; the point of decline is influenced by acclimation to growth temperature24. This decline in apparent Vcmax is not explained by susceptibility of Rubisco to high temperature. Rubisco is a relatively thermally stable protein, and in vitro thermal characterisation of Rubisco, in the absence of phosphorylated compounds, demonstrates that it has an exponentially rising carboxylation rate constant (kcat) and remains functional at temperatures far exceeding the in vivo deactivation point27. Rather, the deactivation of Rubisco is due to the heat sensitivity of Rubisco activase (Rca), the accessory protein of Rubisco that removes tightly bound sugar phosphate inhibitors from the Rubisco active site. Rubisco is prone to decarbamylation, where a Mg2+ ion and CO2 molecule is not bound to the active site prior to RuBP substrate binding, leading to deactivation and the need for Rca to remove bound RuBP from the active site28. Loss of Rca function leads to a reduction in the proportion of Rubisco catalytic sites that are activated and to concomitant declines in photosynthesis26. Accurately modelling An at temperatures above the Topt therefore requires knowledge about the activation state of Rubisco catalytic sites.The maximum carboxylation capacity of Rubisco  and the number of functional sites under rising leaf temperature. One work-around is to regard Vcmax as a variable in time, like temperature itself. Alternatively, a more satisfying reconciliation of this inconsistency is to calculate Vcmax based on the kcat of Rubisco and its deactivation based on biochemical observations30. We hypothesise that we can accurately predict An above the Topt by allowing the number of functional Rubisco catalytic sites to vary with temperature. We explore the extent to which this Rubisco deactivation-based Ac corresponds to a previous model that predicts J-dependent Ar declines in An. We tested the scalability of these models against published temperature response curves and a global composite response curve of An measured over a wide range of leaf temperatures, biomes, and plant functional types.A central assumption of the FvCB model is that all Rubisco catalytic sites in a leaf are functional and invariantVcmax when accounting for the biochemically reported deactivation of Rubisco with rising temperature, the Sharpe-Schoolfield equation for enzyme deactivation at high temperatures31 was used:To capture n), and the kcat of Rubisco at a given temperature were based on reported values from more than 70 higher plant species as described in the methods and presented in Supplementary Table Ed) and the temperature at which enzyme activity was halved (T0.5)31 through a non-linear least-squares regression fit of Eq. 33. Therefore, as with Rubisco kinetic parameters, we separated activation data based on whether a species grew at a day temperature below (cool) or above (warm) 25 °C, respectively , modelled Ac did not reach a Topt below 50 °C for either cool or warm grown plants  but not Rubisco deactivation, Ac reached a Topt at the relatively hot temperatures of 45.1 °C for cool and 46.6 °C for warm grown plants. With both photorespiration and Rubisco deactivation accounted for, the Topt of Ac was 29.4 °C for cool and 32.7 °C for warm grown plants and Ac declined sharply as temperatures exceeded these Topt  of 6.6 μmol CO2 m−2 s−1 due to it maintaining stable An to temperatures below 10 °C  in model predictions based on Ac that included Rubisco deactivation or based on Ar that included temperature dependence of J  loses 50% of its functionality45. Similarly, the warm grown T0.5 of 42.4 °C is within the 40 to 43 °C range in which isolated Rca from warm grown rice  loses 50% of its ability to activate Rubisco46. The difference in T0.5 between cool and warm grown observations in the global activation state data  and the cytochrome b6/f complex (Cyt b6/f ) seem particularly important in setting dynamic temperature-effected rates of J51. There are four Mn atoms per PSII reaction centre responsible for oxidation of H2O. Mn is held by 33 kDa D1 proteins. Prolonged heat stress can dislodge D1 proteins and subsequently Mn2+ ions from the oxygen evolving complex of higher plants, resulting in a decline in J54. The disruption in electron accepting ability of PSII leads to the reaction centre being overly oxidised (P680+) and conducive to ROS formation, which can impair D1 protein synthesis and further diminishes PSII functionality55. The heat sensitivity of the PSII oxygen evolving complex makes it a key reason for why J declines under high leaf temperatures. Heat damage to thylakoid membranes is not confined to PSII. Moderate temperature of 40 °C is shown to disrupt the balance of electron flow between PSII and PSI which is controlled by Cyt b6/f, and through damage or regulation, the flow of electrons through Cyt b6/f leads to an overreduction of PSI upon heat exposure56. With an overly reduced PSI, cyclic electron flow is upregulated as a means of dissipating electrons and preventing irreversibly damage to the stroma57. However, cyclic electron flow is insufficient to maintain An in the absence of linear electron flow since it does not produce the necessary NADPH to run the Calvin-Benson cycle57. This is a strong indicator that the imbalance in electron flow as temperatures exceed the Topt contributes to declining J and subsequently Ar.The dynamic and reversible decline in J suggest a closely aligned temperature limitation on the functionality of both, a tight temperature dependent regulation of one to a limitation in the other, or a combination of the two. Rca activity is modulated by ATP and inhibited by competitive binding of ADP60. Declines in J with rising temperature due to electron transport imbalance, leakiness of thylakoid membranes, or other damage likely reduce stromal ATP concentrations. Lower stromal ATP concentrations reduce the active state of Rubisco61, presumably through reduced Rca activity. Conversely, a lack of CO2 fixation by Rubisco due to heat instability of Rca may lead to an accumulation of RuBP, reductant, and ATP. Recent analysis suggests that Cyt b6/f tightly controls the dynamic flow of electrons between PSII and PSI, thus an accumulation of reductant and ATP would quickly downregulate Cyt b6/f electron transfer51. Interestingly, Rca has previously been found to associate with thylakoid membranes under heat stress in spinach 62, and a recent report in rice noted a reduction in the quantum yield of photosystem I with overexpression of Rca63. Whether Rca and components of the electron transport chain interact directly during heat perturbation to coordinate downregulation of photosynthesis with rising temperature requires further exploration.The alignment of Rubisco deactivation and declines in Ac that included Rubisco deactivation and Ar were accurate across a wide range of cool and warm grown higher plant species from a range of plant functional biomes , and net CO2 assimilation rate per unit leaf area (An) for individual species were collated through searching the published scientific literature. Metadata relating to the publication and conditions of measurement are provided in Supplementary Tables 64 following package instructions. For Rubisco activation data, papers that biochemically characterised the Rubisco activation state to increasing leaf measuring temperature were collated. Values were normalised to the maximum recorded value in each temperature curve. Data were separately analysed based on the mean day growth temperature being below (cool) or above (warm) 25 °C. Where plants were grown at 25 °C, cool or warm grown distinctions were made based on whether the peak in photosynthesis was below or above 30 °C, respectively. For An observational data, studies that measured An on a leaf area basis equal or less than one hour after increasing leaf measuring temperature were included. Where light, CO2 concentrations, or nitrogen were varied, we only used curves with the greatest light or nitrogen application and CO2 concentrations corresponding to ambient concentrations of 400 ± 50 μmol mol−1. Only curves with more than four temperature data points were included.Published temperature response curves of Rubisco activation state, chloroplast electron transport rate 17. The global gas-exchange data and that of Panama tropical species were accessed through the TRY database65.The interspecific temperature response curve comprising observations obtained from 310 species Fig.  was base2 fixation (Ac) was calculated using the FvCB C3 photosynthesis model29 using the equation:Net photosynthetic CO2 partial pressure at the site of fixation (C) was assumed to be an ambient atmospheric CO2 partial pressure (40 Pa for current projections or as stated otherwise) multiplied by 0.7 to account for assumed intercellular CO2 drawdown. We further assumed an infinite mesophyll conductance and no CO2 conductance response to temperature. The partial pressure of oxygen in the atmosphere (O) was either set to ambient atmospheric partial pressure (21 kPa) or zero when assessing effects of photorespiration on An. Respiration in the light (RL) was assumed to be 70% of dark respiration which was 1.29 μmol m−2 s−1 at 25 °C calculated from the relationship between nitrogen and respiration as presented in Atkin et al.66, and its response to rising temperature calculated using a global quadratic model67. The CO2 compensation point in the absence of RL , the Michaelis–Menten constant of Rubisco for CO2  and O2 , and Rubisco kcat (CO2 s−1) at a given temperature were calculated using the Arrhenius equation:R is the gas constant (8.314 J K−1 mol−1), T is the leaf temperature in degrees Celsius and TK the leaf temperature in Kelvin. P25 is the parameter value at 25 °C and Ea the activation energy in J mol−1. The P25 and Ea values were based on multiple species both in vitro and in vivo presented in Galmés et al.68 and Orr et al.69 , -∆H describes the temperature dependency of solubility .The COressure 2 kPa or zressure 2 kPa or zn), and the kcat of Rubisco at a given temperature determined above, we calculated Vcmax as:Based on the expected number of Rubisco catalytic sites (n was obtained by solving the Eqs. An measured at 22 °C or closest observation above (temperatures where no Rubisco deactivation was observed):When models were fitted to individual species or combined species photosynthesis observations, the n was 26 μmol m−2 based on 1.8 g m−2 of leaf Rubisco content across a range of species70 and a molecular weight of 70,000 g per active site71. To model the impact of RuBP regeneration-dependent assimilation (Ar)—the other commonly attributed limitation on An at high temperatures29—we used the equation:J) and its temperature response modelled and parameterised using the equation of June et al.47:J(To) is the electron transport rate (μmol e m−2 s−1) at its temperature optimum (To), and Ω is the difference in temperature from To at which J declines to e−1 (0.37)J(To). J(To), To and Ω were the means of multiple species reported in June et al. (2004)47 or derived from non-linear least squares fits of Eq. J listed in Supplementary Table To and Ω were supplemented with relativised temperature response curves of the quantum efficiency of PSII (ϕPSII). We considered the relative changes in ϕPSII to short-term changes in leaf temperature as equivalent to relative changes in J. Again, we separated the analysis into cool and warm grown plants based on mean day growth temperatures as outlined above. When fitting Ar to individual species or combined species photosynthesis observations, we solved for J(To) using Eqs. An measured at 22 °C or closest observation above:For a species independent estimate, to e−1 0.7J(To). JVcmax based on kcat and Rubisco deactivation  of 25 °C and set to 1. Hd was the deactivation enthalpy and was set as 200 kJ mol−1. The activation enthalpy (Ha) in J mol−1 was calculated as 82,992-632×Tgrowth. The entropy factor (∆S) in J mol−1 was calculated as 668.39-1.07×Tgrowth. Growth temperature (Tgrowth) was set to either 24 or 36 °C which provided the closest fit to Vcmax derived from Eq. tion Eq.  were com72 with Rstudio graphical interface73. The R package readxl (v.1.3.1)74 (https://CRAN.R-project.org/package=readxl) was used to analyse excel data files, and the package Metrics (v.0.1.4)75 (https://CRAN.R-project.org/package=Metrics) was used to calculate root mean squared error (RMSE) and the bias between observed and predicted values.All modelling and analysis were performed using R v.4.1.2 (2021-11-01) statistical softwareFurther information on research design is available in the Supplementary Information NewReporting SummaryPeer Review File


To observe the changes in hemodynamic, stress and inflammatory responses during labor and their labor outcomes after continuous spinal anesthesia labor analgesia for hypertensive pregnant women, and to evaluate whether the continuous spinal anesthesia had any advantages compared to continuous epidural analgesia for hypertensive pregnant women and their newborns.0), 10 min after analgesia (T1), 30 min (T2), 60 min (T3), when the uterine opening was complete (T4) and when the fetus was delivered (T5); the duration of the first stage of labor and the second stage of labor were recorded; the number of cases of treatment with oxytocin and antihypertensive therapy, mode of delivery, eclampsia and postpartum hemorrhage were counted; pregnant women Bromage scores were recorded at T2. We also recorded neonatal weight, Apgar scores at 1, 5 and 10 min after birth; arterial blood gas analysis of the umbilical cord was performed in newborns; finally, TNF-α, IL-6, and cortisol in pregnant women venous blood were measured at T0, T5, and 24 h after delivery (T7). The number of successful compressions and the total drug dosage administered by the analgesic pump were recorded for both groups.A total of 160 hypertensive pregnant women were selected and randomly divided into continuous spinal anesthesia analgesia group (CSA group) and continuous epidural analgesia group (EA group). Participant age, height, weight and gestational week were recorded; MAP, VAS score, CO and SVR were recorded after the onset of regular uterine contractions (TP < 0.05); the MAP, VAS and SVR value in CSA were lower than EA group at T1, T3 and T4 (P < 0.05); in contrast, the CO in CSA at T3 and T4 was higher than in EA (P < 0.05). The oxytocin was more often used whereas the antihypertensive drugs were less used in CSA as compared to EA. The level of TNF-α, IL-6, Cor in the CSA at T5 was lower than the EA group (P < 0.05), and the level of TNF-α in the CSA group at T7 was lower than the EA group (P < 0.05).The first stage of labor in CSA was longer than EA (For pregnant women with hypertension during pregnancy, continuous spinal anesthesia labor analgesia has no significant effect on the final mode of delivery, but shows precise analgesic effect and stabilizes circulatory system, it is recommended to perform continuous spinal anesthesia early in labor for hypertensive pregnant women, which can effectively reduce the stress reaction.ChiCTR-INR-17012659.Date of registration: 13/09/2017. Hypertension in pregnancy is a unique disease during pregnancy . The basCurrently, the commonly used method of labor analgesia is continuous epidural analgesia, which requires a large amount of anesthetics , 8. ContIn our previous study, we applied continuous spinal anesthesia and continuous epidural anesthesia for analgesia in normal laboring mothers and achieved satisfactory clinical results, and we also considered the results of Tao et al.’s study regarding the dose application of continuous spinal anesthesia –11.It is known that maternal position changes, effects of anesthesia, delivery of the fetus, and delivery forceps application can cause significant fluctuations in hemodynamics, whereas obstetricians usually only monitor heart rate, blood pressure, pulse as well as blood oxygen saturation , 12. TheThis study was approved by the ethical committee of Beijing Obstetrics and Gynecology Hospitaland was registered at clinical trials registry on 13/09/2017 with registration ID: ChiCTR-INR-17012659.The informed consent was signed by every parturient after explanation of aim, risks and benefits of the study.A total of 160 parturient, aged 22–35 years old, body weight between 55 to 85 kg, who delivered in Beijing Obstetrics and Gynecology Hospital from September 2017 to September 2020 were enrolled. They were randomly divided into CSA group and EA group with 80 cases in each group. The sample size was calculated using PASS 15.0 software, and a two-sided test with a test level of 0.05 and a test efficacy of β = 0.2 was used, and the rate of loss was calculated at 10%.9/L, and blood coagulation function was normal.①All participants were diagnosed Hypertensive Disorder Complicating Pregnancy according to the diagnostic criteria;②All parturients were classified to grade II or III according to American Society of Anesthesiologists standard;③New York Heart Association Cardiac Function Grade I;④According to the diagnosis of obstetricians, vaginal trial labor is feasible and labor analgesia is voluntary;⑤No history of cesarean section;⑥No contraindication of intraspinal anesthesia, platelet > 100 × 109/L, or parturients with contraindication of intraspinal anesthesia;③Parturients with nervous system diseases;④Parturients with systemic infectious diseases. The parturients who were transferred to cesarean section were excluded.①Parturients previous diagnosed with circulatory disorders, blood system diseases, coagulation disorders, immune system diseases and mental system diseases; ②The platelet count was less than 100 × 10Gestational hypertension is defined as the first occurrence of hypertension during pregnancy, systolic blood pressure ≥ 140 mmHg and (or) diastolic blood pressure ≥ 90 mmHg, urine protein is negative, and it returns to normal 12 weeks after delivery.9/L; microvascular hemolysis indicating anemia, jaundice, or elevated blood lactate dehydrogenase (LDH) level; (8)heart failure; (9)pulmonary edema; (10) fetal growth restriction or oligohydramnios, intrauterine death, placental abruption, etc.Severe preeclampsia is defined as: (1) continuous increase in blood pressure: systolic blood pressure ≥ 160 mmHg and/or diastolic blood pressure ≥ 110 mmHg; (2) persistent headache, visual impairment or other central nervous system abnormalities; (3) persistent upper abdominal pain and liver subcapsular hematoma or liver rupture; (4)abnormal liver enzymes: elevated blood alanine aminotransferase (ALT) or aspartate aminotransferase (AST) levels; (5)renal function impairment: urine protein > 2.0 g/24 h; oliguria , or blood creatinine > 106 μmol/L; (6)hypoproteinemia with ascites, pleural effusion or pericardial effusion; (7)platelet count is continuously decreased and less than 100 × 10All parturients undergo labor analgesia after regular uterine contractions, and continue to apply analgesic pump until placental delivery . Ringer’s solution was infused before labor analgesia, and all parturients underwent fetal heart rate monitoring and LiDCO-rapid system monitoring.For the CSA group, parturients were placed in the left decubitus position. Continuous spinal anesthesia was given between L3 and 4, and the Pajunk continuous spinal anesthesia kit (Germany) was used to puncture the 21 G spinal anesthesia needle into the subarachnoid space, and a 3 cm catheter (25G) was placed on the head side. The first dose of ropivacaine 0.5 mg/ml + sufentanil 0.5 ug/ml within 5 ml in total, 15 min later, a continuous spinal analgesia pump was connected. The formula of the analgesic pump is 100 ml of ropivacaine 0.2 mg/ml + sufentanil 0.2 ug/ml, the background dose is 3 ml/h, the patient-controlled analgesia is 3 ml/time, and the lock time is 15 min.The parturients in the EA group were given continuous epidural anesthesia at the interval L3 to 4, and a 3 cm catheter was placed on the head side. The dose was ropivacaine 1 mg/ml + sufentanil 0.5ug/ml for a total of 5 ml, 5 min later, the same treatment was given for another time. The analgesic pump was connected after 15 min. The analgesic pump formula was 100 ml of ropivacaine 1 mg/ml + sufentanil 0.5ug/ml, a background dose of 5 ml/h, patient-controlled analgesia 5 ml/time, and a lock time of 15 min. The parturients were instructed to press the analgesic pump when VAS ≥ 4 to maintain VAS between 2 and 4 during labor. In both groups, the infusion was stopped after delivery of the placenta and the catheter was removed before the women returned to the ward.0), 10 min after labor analgesia(T1), 30 min after labor analgesia(T2), 60 min after labor analgesia(T3), the full opening of uterine orifice(T4), fetal delivery(T5) and before leaving the delivery room(T6); The time of the first stage of labor (from the regular contraction of the uterus to the full opening of the uterine orifice) and the second stage of labor (from the full opening of uterine orifice to the delivery of the fetus) were recorded; the number of cases of oxytocin and antihypertensive therapy, mode of delivery , occurrence of eclampsia and postpartum hemorrhage ; recording of maternal lower limb muscle strength using the Bromage score at T2; recording the number of successful compressions and the total drug dosage administered by the analgesic pump; neonatal weight, Apgar score at 1, 5 and 10 min after birth were collected; the umbilical cord arterial blood gas analysis was also analyzed and recorded. The changes of TNF-α, IL-6, Cor in maternal venous blood were measured at T0, T5 and 24 h after delivery (T7).The LiDCO-rapid monitor was used throughout the labor process. The MAP, VAS score, CO and SVR were recorded at the time of regular uterine contraction was used for statistical analysis. Data was shown as mean ± SEM and analyzed using unpaired t-test. For categorical data like adverse events, Chi-square test was applied. In this study, In this study, in total 80 parturients were included in CSA group, 8 parturients received caesarean section due to fetal distress, 3 parturients received caesarean section due to prolongation of the first stage of labor; 80 cases were included in EA group, 9 parturients received caesarean section due to fetal distress, 3 parturients received caesarean section due to prolongation of the first stage of labor. This clinical trial is in compliance with CONSORT 2010 guidelines  for every parturient.To comprehensively analyze the hemodynamics’ change during throughout the labor with different anesthesia methods, we recorded the mean arterial pressure (MAP), visual analogue scale (VAS), cardiac output (CO) and systematic vascular resistance (SVR) at different time points   Table .Fig. 4ThOur data showed that there was no significant difference in newborn body weight and Apgar scores at 1,5 and 10 min after birth between CSA and EA groups Table . Further5 was lower than that of EA group (P < 0.05), and the level of TNF-αin the CSA group at T7 was lower than that of EA group (P < 0.05).By comparing the inflammatory response factors and stress response hormones in the serum of pregnant women in the labor process between CSA group and EA group Table , we founThe main pathological feature of hypertension in pregnancy is systemic arterial spasm , 13. WitThe implementation of labor analgesia can effectively maintain the stability of the circulation during the delivery process and reduce the occurrence of related complications . HoweverContinuous epidural anesthesia is a widely used method for labor analgesia, but the dose of drugs used in this way may lead to excessive maternal absorption of drugs into the bloodstream, causing respiratory depression in the newborns, and there is also incomplete analgesic block in some cases. Continuous subarachnoid anesthesia is delivering the anesthetic drugs through a micro catheter placed into the subarachnoid space directly. Compared with continuous epidural anesthesia, the multiple advantages of continuous subarachnoid anesthesia are small dosage, accurate effect, and stabilizing circulatory system, which is an ideal anesthesia strategy for pregnant women with hypertension as the dosage of ropivacaine is reduced, significant motor nerve block is rarely occurred .The accurate hemodynamic monitoring system is also essential during the labor process . The LiDFor those patients with continuous epidural analgesia, sufentanil is only used in the epidural space, the analgesic effect is not so good although the dosage is large, sufentanil can be absorbed into the blood through the venous plexus of the epidural space, increasing the risk of neonatal respiratory depression ; RopivacThe first stage of labor in the CSA group was longer than EA group because ropivacaine partially blocked the visceral nerves, reduced the intensity of maternal uterine contractions, and reduced the frequency of uterine contractions. There was no significant difference between the duration of the second stage of labor in the CSA group and the EA group, suggesting that the combined application of ropivacaine and sufentanil for subarachnoid analgesia had less effect on the second stage of labor. In terms of adverse reactions, the application rate of oxytocin in the CSA group was higher, but the application rate of antihypertensive drugs was significantly lower than EA group, indicating that the subarachnoid application of ropivacaine combined with sufentanil had a stronger analgesic effect. Compared with traditional epidural labor analgesia, continuous subarachnoid analgesia had no significant effect in the final delivery method. The newborns in the two groups had similar Apgar scores at 1, 5, and 10 min, and no significant respiratory depression occurred. The results of umbilical arterial blood gas analysis of newborns in both groups were all within the normal range, and there was no obvious acidosis.5 was lower than the EA group, suggesting that continuous subarachnoid anesthesia can better suppress the stress response effectively. TNF-α and IL-6 are pro-inflammatory response factors, and two indicators in the body trauma can indicate the degree of inflammatory response of the body. Hypertension in pregnancy and childbirth all lead to increased maternal TNF-α and IL-6 levels. In this study, TNF-α and IL-6 levels in the serum were lower in the CSA group than the EA group at T5, and TNF-α in the serum was lower in the CSA group than the EA group at T7, suggesting that continuous subarachnoid anesthesia is more effective in suppressing the inflammatory response.Previous studies have shown that both hypertension in pregnancy and normal delivery induce protective mechanisms such as stress and inflammatory responses, but overexpression of stress and inflammatory responses can impair maternal recovery. Cor is a stress-responsive hormone that is released in large amounts during trauma. In this study, the level of Cor in the CSA group at TTaken together, for pregnant women with pregnancy induced hypertension, continuous subarachnoid analgesia can improve the oxygen supply to the fetus with better analgesia effect and stable circulatory system without significant effect to the final delivery method and newborns, but it can effectively reduce stress response and inflammatory factor release of parturients therefore serves as an ideal anesthesia method for parturients with hypertension.One limitation of this study is that our study was not blinded, and the sample size included in our study is too small, and there may be some deviations in the prospective analysis; Another limitation was the anesthesia method in the study is not very commonly used clinically.