The aim of the study was to adapt the German version of the insulin pump therapy (IPA) questionnaire to Italian (IT-IPA) and to evaluate its psychometric properties in adults with type 1 diabetes.We conducted a cross-sectional study, data were collected through an online survey. In addition to IT-IPA, questionnaires evaluating depression, anxiety, diabetes distress, self-efficacy, and treatment satisfaction were administered.The six factors identified in the IPA German version were assessed using confirmatory factor analysis; psychometric testing included construct validity and internal consistency.The online survey was compiled by 182 individuals with type 1 diabetes: 45.6% continuous subcutaneous insulin infusion (CSII) users and 54.4% multiple daily insulin injection users.The six-factor model had a very good fit in our sample. The internal consistency was acceptable .a positive attitude towards CSII therapy , less Technology Dependency, higher Ease of Use, and less Impaired Body Image. Furthermore, less Technology Dependency was associated with lower diabetes distress and depressive symptoms.Diabetes treatment satisfaction was positively correlated with The IT-IPA is a valid and reliable questionnaire evaluating attitudes towards insulin pump therapy. The questionnaire can be used for clinical practice during consultations for shared decision-making to CSII therapy. The use of technological devices in management of type 1 diabetes is widely increased in the past few years and has been shown to improve Glycaemic Control, health-related quality of life, and treatment satisfaction , and decMoreover, a large body of research over the past decade has shown several clinical benefits in people on insulin pump therapy. However, such benefits depend on the successful uptake and continued use of these devices . Thus, iWearing an insulin pump requires adjusting insulin dose according to meals, physical activity, and responding to fluctuations in glucose levels . For thePsychological characteristics and attitudes of individuals affected by type 1 diabetes may play a significant role in influencing adherence and efficacy of Continuous Subcutaneous Insulin Infusion (CSII) therapy. Some of the barriers identified in the literature are related to the potential negative impact on body image and the feeling of technology dependence , 12. MorIn Italy, a questionnaire evaluating attitudes towards diabetes technological device utilization does not yet exist. The Insulin Pump Attitudes Questionnaire (IPA)  has beenIn this cross-sectional study, data were collected through an online survey conducted from February to August 2021. Participants were enrolled using a chain sampling method. They were invited to take part in a study on the use of technology in the management of diabetes. In addition to the Italian version of the IPA questionnaire, the following questionnaires were also administered to the participants: Patient Health Questionnaire (PHQ-9) to evaluate depression, Generalized Anxiety Disorder (GAD-7) questionnaire to assess anxiety, Problem Areas in Diabetes Scale (PAID-5) for diabetes distress, the Italian version of Diabetes Management Self-Efficacy Scale (DMSES) to estimate self-efficacy, and Diabetes Treatment Satisfaction Questionnaire (DTSQ) for treatment satisfaction. Sociodemographic characteristics , type of device used (MDI or CSII), years of actual devices utilization, duration of the disease (years since the onset of type 1 diabetes), last detection of HbA1c (mmol/mol), body mass index (BMI), and self-reported clinical information  were also self-reported in a preliminary interview.Inclusion criteria were: age ≥ 18 years; diagnosis of type 1 diabetes more than 6 months.Exclusion criteria were: type 2 diabetes.The study was approved by the Ethical Committee for Psychological Research at the University of Padova.The questionnaire is composed of 26 items. The German version identified, through exploratory and confirmatory factor analysis, six subscales: Glycaemic Control (GC) Flexibility (Fle), Impaired Body Image (IBI), Technology Dependency (TD), Ease of Use (EoU), and Functionality (Fun). The IPA total score correlates significantly with diabetes distress, self-efficacy, diabetes empowerment, psychological well-being, and treatment dissatisfaction, supporting criterion validity. The total score ranges from 0 to 104, with higher scores indicating a more positive attitude towards CSII therapy . For thiThe PHQ-9 questionnaire, comprising 9 items, is used to investigate the presence of depressive symptoms for a possible diagnosis of major depression. Scores range from 0 to 27, with cut points 5, 10, 15, and 20, indicating, respectively, mild, moderate, moderately severe, and severe levels of depressive symptoms .The PHQ-9 has proven adequate psychometric characteristics, reliability, and validity in people with diabetes .This questionnaire is composed of 7 items to measure levels of anxiety in the last 15 days. The score ranges from 0 to 21, with cut points 5, 10, and 15 indicating, respectively, mild, moderate, and severe levels of anxiety .The GAD-7 has shown convincing psychometric properties, reliability, and validity, in the general population  and diffThis scale is used to investigate diabetes distress and the emotional burden related to diabetes management , 23. TheThe PAID-5 has resulted to be a psychometrically adequate, reliable, and valid measure of diabetes-related emotional distress , 24.The Italian version of the DMSES measures self-efficacy in diabetes management . IT-DMSEThe DTSQ is a valid and reliable questionnaire of 8 items measuring patients’ diabetes treatment satisfaction , 27. ItsThe IPA questionnaire was translated to Italian and then back-translated to German by a bilingual German native speaker , 29. To The version agreed with the team was then administered  to a pilot sample of 5 people with type 1 diabetes in CSII therapy, aged between 18 and 25. A cognitive interviewing methodology was applied to assess the perception, usefulness, and interpretation of each item , 31. DurDemographic and clinical characteristics were summarized with absolute frequencies and percentages for categorical variables, with mean and standard deviation (SD) or median and interquartile range (IQR) for continuous variables, according to the shape of data distribution.2-test for categorical variables.MDI and CSII users were compared using the t-test for continuous variables with a normal distribution, Mann–Whitney test for asymmetric continuous variables, and χConfirmatory factor analysis (CFA) was performed to compare the goodness of fit of the six-factor solution identified by Bergis et al.  in a stuInternal consistency was assessed using Cronbach’s α coefficient and its relative 95% confidence interval (95% CI). The internal consistency was considered excellent when α coefficient ≥ 0.9, good when 0.8 ≤ α < 0.9, acceptable when 0.7 ≤ α < 0.8, questionable when 0.6 ≤ α < 0.7, poor when 0.5 ≤ α < 0.6, and unacceptable when α < 0.5 .Spearman rank correlations were computed to examine convergent  and discriminant validity  based on data from the first assessment time point.p < 0.05.All analyses were performed using R version 4.1.0, and the significance level was set at The online survey was compiled by 182 individuals with type 1 diabetes: 99 (54.4%) MDI users and and 83 (45.6%) CSII users. About 53.3% of the total sample were females and the median age was between 27 and 29 for MDI and CSII users (Table p = 0.006) and lower level of HbA1c (p = 0.005), while no differences were observed for the presence of hypoglycaemia or ketoacidosis episodes in the last year nor the presence of diabetes-related complications.The two groups differed for years of actual devices utilization and HbA1c: CSII had more years of device utilization , as well as each subscale score  than MDI users   with a reasonable error of approximation in the population . The structure of the IPA resulting from confirmatory factor analysis is shown in Fig. p < 0.001: the strongest correlation was between Fle and Fun (r = 0.847) and between GC and Fle (r = 0.845), the lowest correlation was between GC and TD (r = -0.494).All correlations between factors were significant with p < 0.001 and they ranged from β = 0.52 of item 20 in the IBI factor  to β = 0.94 of item 1 in the Fle factor . Factor loadings in GC, EoU, and Fun factor were higher than 0.8, while one item in each TD, Fle, and IBI factor had a factor loading below 0.65 .Factor loadings (standardized estimates) were significant with Cronbach’s α of the total IPA scale indicated that the internal consistency was acceptable . For the subscales Flexibility and Glycaemic Control, the internal consistency was considered excellent , for Functionality , Ease of Use , and Impaired Body Image  the consistency was good, while for Technology Dependency the consistency was questionable .The subscales Impaired Body Image and Technology Dependency measure negative aspects of the attitude towards the insulin pump, so their correlations were inverted: positive correlations indicate less Impaired Body Image and less Technology Dependency Table .Table 3Cp < 0.01), less Technology Dependency , higher Ease of Use , and less Impaired Body Image .Diabetes treatment satisfaction was positively correlated with a more positive attitude towards the insulin pump therapy in general  and depression symptoms .Furthermore, less Technology Dependency was associated with lower diabetes distress  from German to Italian, evaluate its psychometric properties, and explore correlations between attitudes towards CSII treatment and psychological aspects. Face and content validity were applied to translate and adapt the terms to improve understanding. A final IT-IPA questionnaire has been agreed upon by the research team. Confirmatory factor analysis has confirmed the following six factors of the original version: Flexibility, Glycaemic Control, Impaired Body Image, Functionality, Ease of Use, and Technology Dependency.The IT-IPA resulted to be a valid and reliable questionnaire to be used with people with type 1 diabetes using or intended to use CSII. As expected and as reported by Bergis and colleagues , the IPAOur results also indicate that diabetes treatment satisfaction is positively correlated with a positive attitude towards insulin pump therapy in general. This point is particularly important because treatment satisfaction was associated with better Glycaemic Control in past studies , 34. In The observation that less Technology Dependency and Impaired Body Image and more Flexibility and Functionality were associated with lower diabetes distress and depressive symptoms is clinically meaningful given that psychological distress is associated with lower quality of life , higher On the other hand, some studies have previously reported that diabetes distress may be a barrier to the use of diabetes technology . In partWe should acknowledge some limitations. First, the conclusions are limited by self-report assessment of clinical characteristics, which imply inherent inaccuracies in the reported estimates. Second, the cross-sectional design of our study limits the identification of longitudinal psychological factors impacting the attitudes towards insulin pump therapy and the ability to evaluate the questionnaire’s degree of reproducibility.However, to our knowledge, this is the first scale in Italian assessing attitudes towards CSII therapy. In the next future, addressing psychological barriers and improving psychosocial outcomes in addition to clinical outcomes could be crucial to enhance patient acceptance of automated insulin delivery systems , 41. NonThe IT-IPA is a valid and reliable questionnaire evaluating attitudes towards insulin pump therapy, in particular experiences and expectations on using the pump. The questionnaire can be used for clinical practice and research to explore psychological barriers related to CSII dropout and to collect information on how best to support people with type 1 managing diabetes with an insulin pump. Further research is needed to compare attitudes towards insulin pumps and their relationship with glycaemic levels over time.


InsP) degradation, and thereby, P digestibility in pigs. This study assessed the effects of dietary Ca concentration and exogenous phytase on InsP degradation, nutrient digestion and retention, blood metabolites, and microbiota composition in growing pigs with ileal cannulation. In a completely randomized row–column design with four periods, eight ileal-cannulated barrows  were fed four corn–soybean- and rapeseed meal-based diets containing 5.5 or 8.5 g Ca/kg dry matter (DM), with or without 1,500 FTU of an exogenous hybrid-6-phytase/kg diet. No mineral P was added and the P concentration in the feed was 4.8 g P/kg DM. Prececal InsP6 disappearance in pigs fed diets containing exogenous phytase was lower (P = 0.022) with additional Ca than without. Concentrations of InsP2-4 isomers and myo-inositol in the distal ileal digesta and prececal P digestibility were greater (P < 0.001) with exogenous phytase than without exogenous phytase. In feces, InsP6 disappearance was lower (P < 0.002) and concentration of InsP5 and InsP4 isomers was higher (P ≤ 0.031) with additional Ca compared to without additional Ca. The prececal amino acid digestibility, energy digestibility, and hindgut disappearance of energy did not differ. The Shannon diversity index of the microbiota in the distal ileal digesta and feces was similar among the diets but was lower in the distal ileal digesta than in the feces (P < 0.001). Permutation analysis of variance revealed no dietary differences between the bacterial groups within the ileal digesta and fecal samples (P > 0.05). In conclusion, additional Ca reduced the effect of exogenous phytase on prececal InsP6 degradation. Endogenous InsP degradation was impaired by additional Ca only in the hindgut but the abundance of bacterial genera in feces was not affected.Variations in the dietary Ca concentration may affect inositol phosphate ( Increasing the dietary calcium concentration reduces the effects of exogenous phytase on prececal phytate degradation and endogenous phytate degradation in the hindgut of growing pigs. We hypothesized that the effects of exogenous phytase on InsP degradation, nutrient digestibility, and microbial groups in the digesta and feces are dependent on the Ca concentration of the feed.Therefore, the objectives of this study were to investigate the effects of dietary Ca concentration and exogenous phytase on 1) InsP degradation, nutrient digestibility and retention, blood metabolites, and 2) microbial composition in the ileal digesta and feces of pigs, as well as the concentration of volatile fatty acids . The care of the animals throughout the trial was in accordance with Directive 2010/63/EU .The experimental diets followed a 2 × 2 factorial arrangement with two dietary Ca concentrations achieved by limestone addition (6 and 14 g/kg diet) and two inclusion levels of exogenous 6-phytase  were obtained from the Agricultural Research Station, Unterer Lindenhof  of the University of Hohenheim. They were kept individually in stainless steel metabolism units (1.5 × 0.8 × 1.0 m). Room temperature was controlled at 22.0 ± 0.5 °C. The pigs were surgically fitted with a simple T-cannula in the distal ileum . Pigs weThe experiment was arranged in a completely randomized row–column design with eight pigs, four diets, and four periods to achieve eight replicates per diet. The experimental periods of 12 d each consisted of a 5-d dietary adaption, followed by a 4-d feces and urine collection, 2 d of ileal digesta collection, and 1 d of blood collection. Feces were collected from the floor by hand immediately after defecation. Urine was collected by placing a clean bucket under the pig as soon as the pig started urinating. Two persons were present in the barn during day time to ensure the start of urination was noticed. A subsample of each defecation was taken with a sterile spatula for microbiota analysis and was immediately frozen at −18 °C. Ileal digesta were collected between 0715 and 1915 hours by attaching plastic bags to the open barrel of the cannula with rubber bands, as described by The ileal digesta, feces, and urine subsamples were pooled for each pig and period. The ileal digesta and feces were lyophilized . Ingredients, diets, lyophilized feces, and ileal digesta were ground through a 0.5-mm sieve  and pulverized using a vibrating cup mill  or a mixer mill .GE) were determined in the feed ingredients, diets, feces, and ileal digesta using standard assays (Pi) and Ca in blood serum were analyzed as described by ALP) was determined by measuring the formation of p-nitrophenol from p-nitrophenyl phosphate in the presence of 2-amino-2-methyl-1-propanol. Blood urea nitrogen (BUN) was measured using a Beckman Olympus AU480 instrument , based on an adaptation of the enzymatic method described by Dry matter, crude nutrients, and gross energy . Because the InsP3, InsP3, and InsP3 isomers co-elute in this measurement, they were summarized as InsP3x. The results did not differentiate between the d- and l-forms of the measured InsP. Myo-inositol was determined using a gas chromatograph/mass spectrometer  as described by AA; N-acetylneuraminic acid (Neu5Ac), a marker of mucin synthesis  with some adjustments . The DNApc) InsP6 disappearance and digestibilities of nutrients and GE were calculated as follows:Prececal (y(X) is the disappearance or digestibility of X (%) and X is the concentration of InsP6, DM, nitrogen (N), AA, Ca, P (g/kg), or GE (MJ/kg). The corresponding values for the total digestive tract were calculated using the fecal concentrations.where 6, P, Ca, and N (g/kg) was calculated as follows:Hindgut disappearance of InsPy(X) is the hindgut disappearance of X in g/kg or MJ/kg of feed, and XTT and Xpc are the total tract or pc disappearance of N, Ca, P, InsP6 (g/kg) and GE (MJ/kg) of feed.where The amount of excreted urine (kg/d) was calculated as follows:KTT is the total tract digested amount of K in g/d; KA is the assumed accretion of K by the pig in g/d, according to GfE . The model wasyijkl is the response variable, µ is the overall mean, a is the fixed effect of dietary Ca concentration (i = 5.5 or 8.5 g/kg DM), b is the fixed effect of exogenous phytase inclusion , (ab)ij is the fixed interaction effect between the ith dietary Ca concentration and the jth exogenous phytase inclusion, c is the random effect of the animal (k = 1 to 8), τ is the random effect of the period (l = 1 to 4), and eijkl is the residual error.where 6 disappearance and nutrient digestibility data were logit-transformed, and concentrations in the digesta, feces, urine, and blood were log- or square-root-transformed to meet the assumptions of variance homogeneity and normality. If the F-test results were significant, a multiple t-test was used for pairwise treatment comparisons. All results are presented via a letter-based display as the least-squares means of the untransformed data. Statistical significance was set at P ≤ 0.05.The InsPASV) were identified using the SILVA database (Release 138.1). For unclassified ASV, the nearest representative was manually detected using seqmatch from the Ribosomal Database Project .Bioinformatics assembly and alignment of raw sequencing reads were performed using the MOTHUR pipeline . UCHIME  Project . Only ASPERMANOVA) using the Adonis function to compare the microbial communities associated with diets within sample types (digesta and feces) as well as between digesta and fecal samples.After the sequencing reads were standardized using total reads, a sample dissimilarity matrix was constructed using the Bray–Curtis dissimilarity coefficient. This was subjected to a permutation analysis of variance (NMDS) was plotted using the R package, ggplot2. The Wilcoxon test followed by the Benjamini–Hochberg procedure was conducted to analyze differences in abundance at the phylum and genus levels between both sample types. Spearman’s correlation coefficients between fecal genera with an average relative abundance > 1% and items from hindgut disappearance, total tract digestibility, and VFA concentrations were calculated after the determination of the z-scores for standardization. Visualization was performed using the R package, svglite. Statistical significance for all results was set at P ≤ 0.05. Sequences were submitted to the European Nucleotide Archive under the accession number, PRJEB61474.To visualize the ordination and clustering of the samples, nonmetric multidimensional scaling (5-6 provided by corn (45%), followed by soybean (30%), and rapeseed meal , implying a interaction  with additional Ca than without additional Ca and higher (P = 0.023) with supplemented phytase than without it. The hindgut disappearance of InsP6 was lower with additional Ca in diets without added phytase, but not in diets with added phytase (P = 0.045). The pc and total tract digestibility of P and Ca were greater (P < 0.001) with phytase than without phytase. Urinary P excretion was greater with phytase supplementation only in the diet without additional Ca (P < 0.001). Urinary Ca excretion was greater (P < 0.001) with additional Ca than without additional Ca, but lower (P < 0.001) with phytase than without phytase. The Ca retention was greater with additional Ca (P = 0.004) and phytase supplementation (P < 0.001) than without. The calculated disappearance of P and Ca from the hindgut did not differ. The digestibility and hindgut disappearance of GE also did not differ among the diets (P ≤ 0.019) with phytase than without phytase; however, N excretion in urine and N retention by pigs were similar. The pc digestibility of AA did not differ among the diets P5, and InsP5 were lower (P < 0.001) with phytase, whereas the concentrations of the InsP4 isomers, InsPx3, and myo-inositol were higher (P < 0.001) than those without phytase  with the addition of Ca. In the feces, the concentrations of InsP6, InsP5, and InsP4 were higher (P < 0.031) with additional Ca than without. Fecal concentrations of InsP6, InsP5, and myo-inositol were lower (P ≤ 0.015) with phytase than without. The Neu5Ac concentration in the ileal digesta was higher by a trend in pigs fed diets with additional Ca (P = 0.064) than without additional Ca. Urinary myo-inositol excretion was higher (P < 0.001) with phytase than without phytase and higher (P = 0.004) with additional Ca . The plasma myo-inositol concentration was increased by phytase supplementation (P < 0.001), whereas BUN concentration was reduced by phytase supplementation (P = 0.002). The serum ALP activity in the blood of one pig was consistently higher than the mean of the other pigs by a factor of 2.2. When the data of this pig were disregarded, the serum ALP activity decreased (P = 0.016) with the addition of phytase.The serum PP < 0.001; P = 0.09; P < 0.001; Amplicon sequencing of fecal and ileal digesta samples showed an average of 44,156 ± 3,213 reads per sample, and 2,648 ASV were identified from the reads. The Shannon diversity index in ileal digesta and fecal samples did not differ among the diets. However, the Shannon diversity index was lower in the ileal digesta than in the fecal samples , followed by Actinobacteria , and Bacteroidetes . At the genus level, the most abundant group was Bifidobacterium, with no marked difference between ileal digesta and feces . The relative abundance of Megasphaera (P = 0.012), Limosilactobacillus (P = 0.002), and Blautia (P = 0.021) were positively correlated with N hindgut disappearance (Megasphaera abundance was positively correlated with GE hindgut disappearance (P = 0.025). The relative abundance of unclassified Lachnospiraceae (P = 0.011) and Olsenella (P < 0.001) were positively correlated with the hindgut disappearance of Ca. Positive correlations with the total tract digestible P were detected for the relative abundance of Olsenella (P = 0.005), Limosilactobacillus (P = 0.016), Blautia (P = 0.098), and unclassified Lachnospiraceae  was added with limestone to a Ca concentration of 6 g Ca/kg DM, but not when further limestone was added to a Ca concentration of 10 g Ca/kg DM. In all these studies, pc InsP6 disappearance was low (≤35%) at the lowest Ca concentration in the feed. This might explain why a further reduction in pc InsP6 disappearance was hardly observed with the addition of Ca. The generally low pc InsP6 disappearance in pigs fed diets without phytase has often been reported in the literature P4 in the distal ileum digesta, which is consistent with the results of other studies that used this phytase P4 increased in the ileal digesta of pigs P2 is produced at the end of the ileum. This was consistent with the higher concentrations  of all intermediate dephosphorylation products.Consistent with previous studies, phytase addition in the present study increased the concentration of partially dephosphorylated InsP in the distal ileum digesta . The higing hens , 2020b aing hens . Hybrid  phytase . In stud of pigs . In contmyo-inositol concentration was markedly increased by adding exogenous phytase in ileum digesta and blood plasma of pigs. A similar effect has been reported in previous studies on pigs and poultry .The  poultry . Urinarytrations . The pre6 disappearance indicated that microbial InsP6 breakdown in the large intestine was impaired by the additional Ca in the feed. This is consistent with the results of 6 complexes formed along the gastrointestinal tract, which would remain insoluble in the large intestine because the physiological pH is above 6.0 P4 were similarly affected but to a lesser extent than that of InsP6. The diminishing effect of Ca with each further hydrolysis step of InsP concurs with in vitro results of 6–P among the diets was not decisive for the abundance of bacteria in the large intestine.Results of fecal InsPbove 6.0 . The fec6–P disappearance, which was 0.3 g/kg DM (dietary InsP6–P concentration multiplied by InsP6 disappearance). Most of the difference of 0.1 g/kg DM may reflect P contained in partially degraded InsP and therefore remained indigestible to the pig . Although this effect was not significant, it reflects the reduction in pc InsP the pig . Similari concentration increased with this diet, indicating that the amount of Ca absorbed was insufficient to retain the P that became digestible upon phytase addition, although the Ca digestibility increased to 72% and Ca excretion in urine decreased to 0.3 g/d.Except for the diet without additional Ca and with phytase, the urinary excretion of P was approximately 17 mg P/d. This value was close to the estimated urinary P loss of 0.35 mg/kg BW/d (or 17.5 mg P/d for a pig with 50 kg BW), which was considered inevitable for growing pigs by 6 in the hindgut was remarkable in diets without phytase, the released P was not absorbed, which is consistent with the results of previous studies  to 1.5 percentage units (Thr; Pigs fed diets without phytase exhibited greater fecal N excretion. This suggests that when more P enters the hindgut, bacterial cell replication and metabolism increase, leading to increased N incorporation into microbial proteins, which are subsequently excreted . In addiits Thr; . Howeverits Thr; .In the present study, the microbial community composition in the feces and distal ileum digesta was not affected by the treatment. Bacterial communities may stabilize in response to dietary changes . HoweverLactobacillus was lower in the distal ileum digesta than in the feces, whereas that of Bifidobacterium was higher. Bifidobacterium as the genus with the highest abundance in the ileum and colon. Consistent with other studies , the comMegasphaera correlated positively with fecal GE digestibility. Megaspahera elsdenii belongs to the lactate-utilizing bacterial group and can metabolize lactate as an intermediate product of carbohydrate fermentation in the hindgut (Megasphaeara may utilize lactate derived from fermentation as a substrate. hindgut . Corn wa hindgut . The genPrevotella correlated positively with isobutyric, butyric, isovaleric, and valeric acid concentrations in feces. Prevotella produces acetate, which other bacteria can use to produce butyric acid (Bifidobacterium and isovaleric acid concentration in feces might be due to the glycolytic abilities attributed to this genus, which generates peptidase to facilitate the utilization of N sources (ric acid . The pos sources .6 disappearance depend on exogenous phytase. These results imply that dietary Ca concentration must be precisely adjusted in feed formulations to avoid metabolic P loss or decreased pc InsP6–P release in low-P, corn-based diets with exogenous phytase. The variation in dietary Ca and the presence of exogenous phytase did not directly alter the microbial composition of the ileum and feces in the study period.Negative effects of dietary Ca concentration on pc InsPskad254_suppl_Supplementary_MaterialClick here for additional data file.


Hepatoid adenocarcinoma of the stomach (HAS) is a highly malignant and rare extrahepatic tumor. The prognosis is controversial because of its rarity and the lack of multi-center cohort studies, especially on the influence of serum Alpha-fetoprotein (AFP) level on prognosis. We aimed to analyze the clinicopathological characteristics and prognosis of HAS, particularly the effect of serum AFP on the prognosis of HAS.We retrospectively reviewed clinical data of one HAS patient treated at our institution in 2019 and of 252 patients reported between 1984 and 2020 in research databases.P = 0.000682) and liver metastasis (P = 0.000068). The 1-, 3-and 5-year progression-free survival(PFS) rates were 41%, 18%, and 0%, and the 1-, 3-, and 5-year overall survival (OS) rates were 64%, 26%, and 21%, respectively. The survival analysis showed that OS was significantly shorter for HAS with high-AFP (> 300 ng/ml) than with low-AFP (≤ 300 ng/ml) (P = 0.023). The univariate analysis indicated that the OS of HAS was associated with tumor location, pTNM stage, lymph-node metastasis, surgical resection, and serum AFP > 300 ng/ml. However,the prognostic factors for PFS was only pTNM stage and surgical resection. The multivariate analysis confirmed that the independent prognostic factor affecting OS of HAS included pTNM stage and surgical resection.Among these patients, 60.1% were > 60 years, 51% had lesions in the gastric antrum, and 51.0% (73/143) had the ulcerative lesion type. The preoperative elevated levels of serum alpha-fetoprotein (AFP) were detected in most patients (76.7%). Lymph-node (84.6%) and preoperative liver metastasis (39.1%) were often found. The high-AFP group was characterized by a higher rate of stage IV (Liver metastasis was increasingly more likely with increasingly higher serum AFP, but the prognosis of HAS is not necessarily poor. Serum AFP level is an important prognostic indicator in HAS and should be monitored. Hepatoid adenocarcinoma (HAC) is a highly malignant and rare extrahepatic tumor histologically similar to hepatocellular carcinoma (HCC) and characterized by high serum α-fetoprotein (AFP). Additionally, HAC has been reported in various organs, such as the esophagus, stomach, colon, lung, pancreas, peritoneal, and ovaries, but gastric tissue is the most common -6. In 19HAS is a unique and rare subtype of gastric adenocarcinoma, accounting for 0.38%–1% of all gastric cancers . Many reThe study aim was to analyze the clinicopathological characteristics and prognosis of HAS, particularly the effects of serum AFP level on prognosis.th edition of the American Joint Committee on Cancer. Finally, we identified 135 reports . Thirty reports (including 123 patients) were excluded because of the lack of information about age, sex, or serum AFP levels. Since our study mainly discussed the prognosis of HAS patients, 32 of the remaining 105 reports were eliminated because they provided no information on follow-up time,survival status,pTNM staging,lymph-node metastasis,preoperative liver metastasis,and treatment protocol.The follow-up period ranged from 3 to 131.8 months and three patients were removed for < 3 months . Ultimately,253 patients in the 70 reports were included in the study .Patients clearly diagnosed as HAS by surgery or gastroscopy biopsy with a tumor located in the stomach were included in this study, and patients with cirrhosis or HCC were excluded. Clinical data and follow-up times were extracted from published case reports. We have reclassified the pathology-Tumor-Node-Metastasis (pTNM) stage of all tumors according to the 7Pathology is the “gold standard” for diagnosing the HAS,morphology is the main basis for pathological diagnosis.Gastric cancer with hepatoid differentiation area in pathomorphology can be diagnosed as HAS regardless of the number of histological hepatoid differentiation . The tumP value less than 0.1 in the univariate model were included for further identify significant independent predictors of survival of HAS in the multivariable model.OS was calculated from the date of pathological diagnosis to the date of death or end date of follow-up, and PFS was determined from the date of surgery resection or chemotherapy to the date of recurrence or metastasis of the primary tumor. P < 0.05 was taken to be indicative of statistical significance for all tests. Kaplan–Meier survival plots were made by using GraphPad Prism 8 .The assessment of clinicopathological data was performed by using IBM SPSS Statistics for Windows version 26.0 software . Comparisons of the categorical variables were analyzed by using either the Chi-square test or Fisher’s exact test, as appropriate. Numerical variables were expressed as the mean ± standard deviation. The Kaplan–Meier method was used to evaluate both the overall survival (OS) and progression-free-survival (PFS), with the log-rank test being used to examine any differences between survival curves. The Cox regression models were used to determine prognostic factors associated to HAS,variables with The available clinicopathological characteristics of the 253 HAS patients are summarized in Table P < 0.001). Additionally, the incidence of liver metastasis was higher (37.4% vs. 62.6%) and tumor size was smaller in the high-AFP group. We observed that high-AFP tumors were often limited to the mucosa, submucosa, or muscle layer, whereas low-AFP tumors often invaded the serosa layer and beyond.To further study the clinical significance of AFP levels in HAS, according to serum AFP with a cutoff value of 300 ng/ml, we divided HAS into the low-AFP group (serum AFP ≤ 300 ng/ml) and high-AFP group (serum AFP > 300 ng/ml) to further compare the clinicopathological features of the two groups Table . The resP = 0.023), but the difference was not statistically significant in terms of PFS in these two groups. The 1-, 3-, and 5-year OS rates were 72% vs. 56%, 30% vs. 22%, and 25% vs. 16% (P = 0.023) in the low-AFP and high-AFP groups , and the median PFS time was 6 months (range: 0.3–36 months). The 1-, 3-, and 5-year PFS rates were 41%, 18%, and 0%, respectively, and the 1-, 3-, and 5-year OS rates were 64%, 26%, and 21%, respectively .However,the prognostic risk factors for PFS only included pTNM stage and surgical resection. The multivariable analysis confirmed that pTNM staging  and surgical resection  were independent prognostic factors affecting OS of HAS.However, surgical resection (HR = 0.267), 95% CI: 0.098–0.729, P = 0.010) was only independent prognostic factor for PFS because of the limited number of patients  targeted therapy might be beneficial in HAS patients -33.Our study had some limitations that should be considered. First, this was a retrospective study of published case reports, and the clinical data are incomplete. Second, the sample for analyzing PFS was not sufficiently large, which may have caused some statistical bias. Therefore, a multi-center cohort study with a larger sample size is needed to verify our findings.The majority of patients with HAS have elevated serum AFP, and the higher the serum AFP, the more likely liver metastasis will occur. However, the prognosis of HAS is not necessarily poor. High-AFP (> 300 ng/ml) was significantly associated with poorer OS in HAS, so physicians should monitor serum AFP in clinical practice. Early pTNM staging and surgical resection can improve the prognosis of patients with HAS.


Patients with chronic obstructive pulmonary disease (COPD) often present with atrial fibrillation (AF), but the common pathophysiological mechanisms between the two are unclear. This study aimed to investigate the common biological mechanisms of COPD and AF and to search for important biomarkers through bioinformatic analysis of public RNA sequencing databases.Four datasets of COPD and AF were downloaded from the Gene Expression Omnibus (GEO) database. The overlapping genes common to both diseases were screened by WGCNA analysis, followed by protein-protein interaction network construction and functional enrichment analysis to elucidate the common mechanisms of COPD and AF. Machine learning algorithms were also used to identify key biomarkers. Co-expression analysis, “transcription factor (TF)-mRNA-microRNA (miRNA)” regulatory networks and drug prediction were performed for key biomarkers. Finally, immune cell infiltration analysis was performed to evaluate further the immune cell changes in the COPD dataset and the correlation between key biomarkers and immune cells.CDK8), was identified through screening by machine learning algorithms and validated in the validation dataset. Twenty potential drugs capable of targeting CDK8 were obtained. Immune cell infiltration analysis revealed the presence of multiple immune cell dysregulation in COPD. Correlation analysis showed that CDK8 expression was significantly associated with CD8+ T cells, resting dendritic cell, macrophage M2, and monocytes.A total of 133 overlapping genes for COPD and AF were obtained, and the enrichment was mainly focused on pathways associated with the inflammatory immune response. A key biomarker, cyclin dependent kinase 8  make it a possible promising therapeutic target for COPD combined with AF.This study highlights the role of the inflammatory immune response in COPD combined with AF. The prominent link between  Chronic obstructive pulmonary disease (COPD) is characterized by progressive airway obstruction. It is estimated that COPD will be the third most deadly disease in the world by 2030 . In clinThere is a strong association between COPD and AF, with studies showing a 2.23-fold increased risk of AF in COPD patients compared to non-COPD patients . SimilarThe field of bioinformatics is developing rapidly, and large amounts of genetic data are publicly available to uncover many unknown pathophysiological mechanisms in the development of diseases and potential connections between diseases. Machine learning, an essential artificial intelligence component, has also been widely applied to bioinformatics research and has become an important tool . Based ohttp://www.ncbi.nlm.nih.gov/geo/) to filter gene expression datasets for microarrays by qualifying the keywords “COPD” and “AF” with the filter criteria “Homo Sapiens” and “tissues.” Four datasets were finally obtained. In the COPD group, GSE76925 (lung tissue samples from 111 COPD patients and 40 control patients) (We applied the Gene Expression Omnibus (GEO) database  (http://atients)  and GSE1atients)  and GSE1atients)  were selp-value. Finally, we select the genes in the modules closely related to the disease for subsequent analysis.WGCNA analysis was performed on GSE76925 and GSE79768, respectively, to obtain modules closely associated with COPD and AF. WGCNA analysis was constructed using the “WGCNA” package in R . The genhttps://cn.string-db.org/)  online platform (db.org/) . The spedb.org/) .-P < 0.05, and the visualization was presented using the Sangerbox platform (http://vip.sangerbox.com/). Meanwhile, Gene set enrichment analysis (GSEA) enrichment analysis was performed on the GSE76925 and GSE79768 datasets to comprehensively analyze the key pathways associated with COPD and AF pathogenesis. The reference dataset was “c5.kegg.v7.4.symbols.gmt” from the MSigDB database  and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the “clusterProfiler” package in R . The GO database . The sigP < 0.05 considered to be significantly different, and used the “ggpubr” R package to plot boxplots. Finally, genes that were differentially expressed in the disease and control groups in both sets of data and that showed the same expression trend in both microarrays were identified as candidate hub genes.Machine learning is now widely used to identify characteristic genes. To identify key genes associated with COPD and AF, four machine learning algorithms, including RF, SVM, XGBoost, and GLM, were used to screen for key genes in COPD and AF, respectively. In both training datasets, the response variable was set to whether the diagnosis was COPD and AF, and the overlapping genes were set as explanatory variables. Use 70% of the data for model construction and 30% for model validation. Models for RF, SVM, XGBoost, and GLM were constructed separately using the “caret” R package . It is wP < 0.05 was considered to be significantly different. The candidate genes with significant differences were finally considered to be hub genes and the boxplot was drawn for visualization. Afterwards, ROC curves of the diagnostic value of hub genes in the training set and validation set were plotted using “pROC” R package, and AUC was calculated to evaluate the accuracy of hub gene prediction.The identified candidate genes were validated in the validation sets for COPD and AF, respectively. The comparison of gene expression between disease group and control group with http://genemania.org) for co-expression and functional enrichment analyses. The JASPAR database (http://jaspar.genereg.net/) were used to predict TFs regulating hub genes. Prediction of miRNAs regulated by hub genes using the miRTarBase database (https://mirtarbase.cuhk.edu.cn/), and experimentally validated miRNAs were selected. The results were visualized using Cytoscape to demonstrate the “TF-mRNA-miRNA” regulatory network. In addition, we used the DGIDB 3.0 database (http://www.dgidb.org/) to predict potential drugs that could target the hub gene.Hub genes were entered into the GeneMANIA online website   and contained 745 genes (β = 10 (P = 0.004), pink , turquoise , and yellow  were positively correlated with AF and contained 3,444 genes ; “External side of plasma membrane,” “Immunological synapse,” “Plasma membrane signaling receptor complex,” (CC); “Immune receptor activity,” “Phosphatidylethanolamine binding,” “Coreceptor activity,” (MF) . Also, KCDK8), solute carrier family 22 member 15 (SLC22A15), and TNF receptor superfamily member 17 (TNFRSF17), were finally obtained, and the box plots of differential expression are shown in To identify key genes associated with COPD and AF, we constructed models using four machine learning methods and evaluated the models based on residuals and ROC. Box line plots of residuals and ROC are shown in CDK8, SLC22A15, and TNFRSF17 was confirmed in the external validation set. Only CDK8 showed a significant increase in expression in both the training and validation sets (P < 0.05) CDK8 was finally identified as a hub gene that may be related to AF and COPD. the CDK8′s ROC curves demonstrated that in all four data sets, the AUC was near to or greater than 0.7 , T cells and plasma cells (r = 0.42), and γδ T cells and T follicular helper cells (r = 0.42). In contrast, Macrophage M1 and activated dendritic cells were negatively correlated (r = −0.54)  . This suCDK8 and immune cells showed that CDK8 expression correlated with four immune cell types, positively with CD8+ T cells, resting dendritic cells, and macrophage M2, and negatively with monocytes , interleukin 1 beta (IL-1β), interleukin 6 (IL-6), C-X-C motif chemokine ligand 1 (CXCL1), and C-X-C motif chemokine ligand 8 (CXCL8), which attract circulating neutrophils, monocytes, and lymphocytes in the lungs leading to an inflammatory response (CRP), IL-6, CXCL8, and TNF-α , and C-X-C motif chemokine ligand 2 (CXCL2) have also been observed in AF  and TNF-α (IL-17) production during acute allergic airway disease and are involved in disease pathogenesis. Plasma cells are widely present in the connective tissue of the lamina propria of the respiratory tract and participate in the adaptive humoral immune response by synthesizing antibodies in response to the invasion of the respiratory tract  and CDK8 are jointly recruited to the promoters of response genes, driving the expression of NF-kB early response genes CXCL8, CXCL2, and C-X-C motif chemokine ligand 3 (CXCL3). In addition, CDK8 is involved in the activation of hypoxia inducible factor 1 subunit alpha (HIF1A)  . lungs oresponse . Elevatet atrium . CDK8 alytokines , 63. Traromoters . This avesponses , 65. Stuesponses  have fouCDK8 and immune cell infiltration showed a positive correlation between CDK8 and CD8+ T cells, resting dendritic cells, and macrophage M2 and a negative correlation with monocytes. Patients with COPD have increased infiltration of CD8+ T cells in lung tissue and produce pro-inflammatory factors such as TNF-α  and sarcoplasmic reticulum Ca-ATPase (SERCA2a) thereby participating in AF  and matrix metallopeptidase 9 (MMP-9) activities, promotes collagen breakdown, and exacerbates myocardial fibrosis , and interleukin 1 alpha (IL-1). This process may cause the onset of AF (CDK8 and monocytes. However, the exact mechanism still needs further investigation. In conclusion, our findings provide a new perspective on the pathogenesis of COPD combined with AF from the viewpoint of the inflammatory immune response and suggest a biomarker CDK8 that could potentially be a therapeutic target.Analysis of the correlation between as TNF-α . The invng in AF , 68. In fibrosis , 70. M2 fibrosis  et al. she atria –74. Incrhe atria . Studieset of AF . Dendritet of AF  et al. fCDK8 in the COPD training set was less than 0.7, and although the AUC area was improved in the validation set, its value in practical clinical applications still needs further validation. Finally, the specific mechanisms of immune inflammatory response and CDK8 in COPD with AF and the association between CDK8 and immune cells need further proof from subsequent in vivo and in vitro experiments.This study also has several limitations. First, the data in this study were obtained based on the GEO database. Although a dataset containing more samples was selected and validated in an external dataset, the results may be biased due to the different platforms from which they were obtained. Additionally, due to COPD being a heterogeneous disease, there are various phenotypes of COPD, such as small airway-predominant disease, frequent exacerbators, and asthma-COPD overlap, which have different pathophysiological mechanisms that are not completely the same . Recent CDK8 was finally identified as a key biomarker, and inhibitors targeting CDK8 may be able to be promising therapeutic agents for COPD combined with AF by inhibiting NF-kB-induced immune inflammatory responses.In this study, through bioinformatic analysis, we found that disturbances in immune regulation and subsequent activation of the inflammatory response may have a significant role in COPD combined with AF. Through machine learning algorithms,


Treatment of brain tumors in dogs can be associated with significant morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to assess perfusion parameters and change in size of suspected brain tumors before and during radiotherapy (RT) depending on their location and find a potential correlation with survival.Seventeen client-owned dogs with suspected brain tumors were prospectively recruited. All dogs had a baseline DCECT to assess mass size, blood volume (BV), blood flow (BF), and transit time (TT). Twelve dogs had a repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated.p = 0.005) and BV (p < 0.001) than extra-axial masses but not than pituitary masses. Pituitary masses had lower BF (p = 0.001) and BV (p = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT (p = 0.001) but not with BF and BV. Intra-axial masses showed a more marked decrease in size than extra-axial and pituitary masses during RT . Extra-axial masses showed a greater decrease in BF (p = 0.011) and BV (p = 0.012) during RT than pituitary masses and intra-axial masses. Heavier dogs had a shorter survival time (p = 0.011). Perfusion parameters were not correlated with survival.Intra-axial masses had lower BF (DCECT perfusion parameters and change in size of brain masses during RT might be different based on the location of the mass. RadiothIn human medicine, functional imaging is increasingly used in the diagnosis, treatment planning and prognostication of brain tumors, and includes magnetic resonance spectroscopy, diffusion-weighted magnetic resonance imaging (MRI), perfusion-weighted MRI and dynamic contrast-enhanced computed tomography (DCECT) , 22. DynThe aims of this study were (1) to compare DCECT-derived perfusion parameters among intra-axial, extra-axial and pituitary tumors, (2) to assess if pretreatment perfusion parameters are associated with survival, and (3) to describe early changes in perfusion parameters and size of the masses during RT in a subset of them. Our hypotheses were that extra-axial and pituitary tumors will have higher BF and BV than intra-axial tumors, that baseline perfusion parameters might be associated with survival time and that we can observe early changes in perfusion parameters and mass volume during RT.2.This is a prospective cross-sectional study. Ethical approval was granted by the Committee on Research Ethics at the Institute of Veterinary Science of the University of Liverpool (VREC560a).2.1.Client-owned dogs presented to the Small Animal Teaching Hospital (SATH) of the University of Liverpool for suspected brain tumors were prospectively enrolled from January 2017 to January 2020. Owner consent allowing for diagnostic tests including DCECT was obtained before inclusion into the study. To meet the inclusion criteria, dogs must have a brain mass on MRI and a presumptive diagnosis of brain tumor made by the attending board-certified radiologist and neurologist based on the imaging and clinical findings, but a final diagnosis of brain tumor made by histology was not necessary. Dogs must have undergone at least a baseline DCECT. Dogs who had already received RT, surgery or chemotherapy were excluded. Dogs receiving other non-chemotherapeutic medical treatments for their neurological signs (anti-inflammatory and anti-epileptic medication) were not excluded.2.2.Treatment received at the time of DCECT, heart rate and systolic blood pressure during DCECT, treatment administered to treat the suspected brain tumor and survival time from the referral consultation were recorded. Treatment administered before the consultation was categorized as corticosteroids, non-steroidal anti-inflammatory drugs (NSAID) and other  or none. Treatments received for the brain mass were categorized as RT or palliative (1 dog).2.3.All dogs were anesthetized. Premedication varied depending on the attending anesthetist, but most dogs received medetomidine (0.003 to 0.01 mg/kg) in association with butorphanol, lidocaine, buprenorphine or methadone. One dog received acepromazine (0.03 mg/kg) instead of medetomidine. Dogs were then induced using propofol or alfaxolone (to effect) and anesthesia was maintained using sevoflurane. Dynamic contrast-enhanced CT was performed using an 80-slice CT scan  with dogs in sternal recumbency. Dogs for which owners elected for RT were positioned using a thermoplastic mask and a bite block as part as the RT planning .Pre-contrast scans of the head were performed. Scanning parameters were 120 kV, variable mAs using Automatic Exposure Control, pitch factor 0.625, and images were reconstructed at 1 mm slice thickness using bone and soft tissue reconstruction algorithms. Dynamic contrast-enhanced CT planning was done using the pre-contrast soft tissue reconstruction in a soft tissue window . A 4-cm length field of view was chosen to include the whole mass.A 60-s continuous scan starting with intravenous injection of 2 mL/kg body weight of iodinated contrast medium (Ioversol 300 mg/mL iodine) using a power injector set at 3 mL/s injection rate  and followed by a bolus flush of saline 1 mL/kg at the same injection rate. Scanning parameters were 80 kV, 200 mA, 0.75 s rotation time, 0.5 mm scan slice thickness, 1 s time interval and 2 mm reconstruction slice thickness. Images were reconstructed using a soft tissue reconstruction algorithm.A post-contrast scan of the head was performed immediately after DCECT (90 s after intravenous injection of iodinated contrast medium), using the same scanning parameters as for the pre-contrast scan.A second DCECT using the same anesthetic protocol  and the same scanning technique was performed, after receiving 12 Gy of radiation.2.4.Radiotherapy was administered using a linear accelerator . Definitive RT was administered with 12 fractions of 4 Gy on a Monday, Wednesday, Friday basis. All treatments were carried out at 6MV and were 3D planned by a European College of Veterinary Internal Medicine board-certified veterinary oncologist and radiation oncologist (LB). Planning was performed from CT images using Eclipse 15.1 , with the intention to include at least 95% of the planning treatment volume in the 95 to 105% isodose, or 97% of the planning treatment volume in the 97 to 103% isodose. Gross tumor volume (GTV) and clinical target volume (CTV) were defined using CT and MRI. Gross tumor volume was contoured based on T1-weighted (or T1-weighted after IV administration of gadolinium) images. A margin of 1–2 mm of normal tissue, including questionable tissue, was added to the GTV to create the CTV. The CTV-margin was extended three-dimensionally by 3–5 mm to define the planning target volume (PTV). Organs at risk were contoured . Plans utilized 3 to 5 coplanar beams, with beam collimation using multileaf collimator beam modification and dynamic wedges where appropriate. Dogs were immobilized as described for the CT scans. Portal imaging was carried out at least twice during the treatment protocol to verify position.2.5.Conventional CT images of the head were reviewed by a European College of Veterinary Diagnostic Imaging board-certified veterinary radiologist (JM) blinded to the clinical data of the dogs, using a Macintosh workstation and an image viewer . Images were viewed using both a soft tissue window  and a brain window (window width: 100 HU and window level: 50 HU). Multiplanar reconstruction was performed for each dog. Length, width, and height with planes parallel and orthogonal to those of the head were measured and the volume of the mass (using the ellipsoid formula V = 4/3 × π × L × W × H) was calculated. In 2 dogs with an intra-axial lesion, the mass was not sufficiently visible on CT and T2w MRI sequences in transverse, sagittal and dorsal planes were used for initial morphological assessment. One of these dogs had a repeat DCECT but the mass could not be measured on the images. Masses were first classified as extra-axial, intra-axial or pituitary based on their location, relationship to the rest of the brain parenchyma and contrast-enhancement .™ , designed as part of a previous study  model implemented with MATLABus study . An arteus study . Care wa2.6.Statistical analyzes were performed using the statistical software programs SPSS 24.0  and R . Dependent (outcome) and independent variables were derived from signalment data, clinical data and CT examinations. Descriptive statistics were calculated for data as required; categorical variables were summarized as frequencies with 95% confidence intervals (95% CI) and continuous variables as medians with interquartile ranges (IQR). Categorical variables with multiple categories, categories containing small numbers, or both, were reviewed and groupings amalgamated if necessary. The distribution of continuous variables was assessed for deviation from normal both graphically and with the Kolmogorov–Smirnov test.p-value <0.25) were considered for inclusion in the final multivariable model for that outcome. Variables showing evidence of correlation (correlation coefficient > 0.7), were examined and only the variable with the smallest p-value was selected for entry in the multivariable models developed. Final models were developed with a manual backwards stepwise methodology with retention of variables with p-values < 0.05. Additionally, for the 12 dogs that were re-scanned, linear regression was used to compare the change in tumor parameters  between pituitary, extra-and intra-axial tumors and to evaluate associations between tumor volume and perfusion parameters .The three primary individual outcomes considered were BF, TT and BV, with associations between these continuous variables and the collected independent variables estimated with linear regression. All independent variables showing potential association with an outcome on univariable analysis . Median survival times were calculated from Kaplan–Meier product limit  analysis. Univariable comparison of survival times and associations between survival and independent variables were examined with the Log Rank test for categorical variables and Cox proportional hazard regression analysis for continuous variables. Multivariable regression models were constructed with the same approach as above, including all variables with univariable 3.3.1.Seventeen dogs met the inclusion criteria. There were 4 neutered females, 3 entire males and 10 neutered males. Breeds included 4 cross breeds, 3 Staffordshire bull terriers, 2 Labrador retrievers and 1 dog of each breed including cocker spaniel, boxer, Cavalier King Charles spaniel, Dalmatian, Jack Russel terrier, pug, West Island white terrier and dachshund. Median age of the dogs was 9.9 (6.6–14.3) years; median weight was 19.9 (6.6–59.6) kg.There were 7 pituitary masses, 6 extra-axial masses and 4 intra-axial masses. Among the extra-axial masses, 4 were localized against the basicranium, 1 at the cerebellar convexity and 1 at the cerebral convexity. Among the intra-axial masses, 2 were within the temporal cortex, 1 within the cerebellum and 1 within the thalamus.Nine dogs received corticosteroids , 1 dog received NSAID (1 pituitary), 2 dogs received “other” treatments  and 5 dogs had no treatment at the time of presentation .Twelve/17 dogs had repeat DCECT. There were 5 pituitary masses, 5 extra-axial masses and 2 intra-axial masses. Five dogs could not have repeat DCECT for logistical reasons. One did not received RT, DCECT failed in 1 dog and the remaining dogs were not considered stable enough to undergo the procedure.At repeat DCECT, 10/12 dogs were receiving corticosteroids, 1 dog was on phenobarbital  only and 1 dog was not receiving any medical treatment . Most dogs were receiving analgesics in addition to the aforementioned treatment.Sixteen/17 dogs had RT, and 1 dog did not receive any treatment for the suspected brain tumor. Median time between first DCECT and start of RT was 6 days .Twelve/17 dogs had a record of their heart rate during the baseline DCECT, at the time of injection of contrast medium. All were considered appropriate by the attending anesthetist and ranged from 40 to 110 bpm (median 68 bpm). Similarly, systolic blood pressure was obtained for 12 dogs and ranged from 90 to 130 mmHg (median 115 mmHg).3.2.3 (1.4–29.6), respectively. Median volume was 16 cm3 (1.8–25.5) for pituitary masses, 9.4 cm3 (1.5–15.8) for extra-axial masses, and 8 cm3 (1.4–29.6) for intra-axial masses.Median mass length, width, height, and volume were 1.4 cm (0.8–3.2), 1.2 cm (0.6–2.2), 1.2 cm (0.4–2.1) and 8.2 cmp = 0.005) and BV (p < 0.001) than extra-axial masses but not than pituitary masses. Similarly, pituitary masses had significantly lower BF (p = 0.001) and BV (p = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT (p = 0.001) but not with BF and BV. There was no statistical association between any other imaging characteristic of the masses and the perfusion parameters.Median BV was 3.6 ml/100 g (0.7–11), median BF was 33.4 ml/100 g/min (2.8–116.1) and median TT was 7.2 s (4.1–15.7). Results for the different locations of masses are shown in 3.3.p = 0.022 for the length and p = 0.05 for the height).Median change in volume, length, height, width for each type of mass is shown in p = 0.011) and BV (p = 0.012) than pituitary tumors and intra-axial tumors.The median change in perfusion parameters for each type of mass are presented in There was no statistically significant association between tumor volume change and change in BF, BV or TT.3.4.At the end of the study, 11 dogs were deceased, all due to progression of their intracranial mass, and six were either still alive or lost to follow-up.The median survival time was 186 days (95%CI 0–496) for all dogs. The only dog who did not receive RT had a survival time of 175 days. There was no statistical difference in survival time between intra-axial, extra-axial and pituitary masses.p = 0.011). More specifically, heavier dogs had a shorter survival time. Perfusion parameters were not significantly associated with survival in the final statistical model.On multivariate analysis, only the weight of the dog was associated with survival , intra-axial masses showed a greater decrease in size than masses of the other groups, and extra-axial masses had a more marked decrease in BF and BV than masses of the other groups.A study on 16 dogs with various types of brain masses (including 3 meningiomas and 7 gliomas but no pituitary masses) showed that meningiomas had the highest BV among all masses, although their results were not statistically significant . The autA more recent study investigated the change in volume and perfusion parameters of brain tumors (confirmed and suspected) before and approximately 3 months and 6 months after RT . They foThe fact that intra-axial masses showed a greater decrease in size than extra-axial and pituitary masses was interesting and unexpected. However, this result should be interpreted with caution given the small number of dogs in this group and the technical difficulty in accurately measuring intra-axial masses on CT. Imaging follow-up during or after treatment of brain tumor is rare and unstandardized in veterinary research and studies assessing the association between change in volume, type of tumor and survival are scarce. It seems that a reduction in size of gliomas 6 weeks after RT is associated with longer survival . These rExtra-axial masses had a greater decrease in BF and BV during RT than the other tumor groups. This could simply be explained by the fact that extra-axial masses were more perfused at baseline, therefore the toxicity of RT on vascularity could have been more pronounced in this group. However, the response of the tumor microenvironment to RT is a complex and still poorly understood topic, and oversimplified assumptions should be avoided. Relationships between baseline perfusion parameters, their variation after treatment and prognosis have been investigated in people with high-grade gliomas. High-grade gliomas tend to have higher baseline perfusion parameters than low-grade gliomas, while lower post-treatment perfusion parameters were associated with a better prognosis , 35–39. Heavier dogs had shorter survival in this study, regardless of tumor location. There is no clear reason to explain this finding, but it could simply be that heavier dogs with severe neurological clinical signs would be less manageable by their owners, therefore euthanized earlier in the course of the disease. Alternately, it could also represent a bias due to the small number of dogs included.This study has many limitations. The main one is the small number of dogs, limiting the statistical power. A second limitation is the absence of confirmation and characterization of the masses. Using only the imaging characteristics, it is often impossible to differentiate between meningioma and histiocytic sarcoma, between pituitary adenoma and carcinoma, and between types and grades of gliomas , 40, 41.Some dogs received ant-inflammatory drugs before first or repeat DCECT, or before both; other did not. The effects of anti-inflammatory drugs on DCECT perfusion parameters have not been studied, yet their anti-COX-2 activity have an anti-angiogenic action and could be responsible for changes in the perfusion parameters .The technique of DCECT images acquisition and analysis used in this study also has some inherent limitations. The DCECT protocol used meets the human recommendations except for the injection rates of contrast medium and saline flush. Indeed, due to catheter size limitations leading to overpressure during injection, a 5 ml/s injection rate was not feasible. However, the smaller size of dogs compared to human beings likely balances out this limitation. Finally, intra and inter-observer variability have not been calculated in this study but would have been interesting, especially since it represents the highest contributor to overall variability in DCECT . A studyContouring of masses close to the calvarium obliged to exclude a sliver of tissue to avoid including bone in the perfusion analysis. Another important technical limitation is the fact that in two dogs with an intra-axial mass, contouring was performed where the observer subjectively thought the mass was based on MRI studies, and therefore might have been inaccurate.In conclusion, this study found an association between the location of intracranial masses and the perfusion parameters at baseline  and during RT , and between the location of the mass and the size reduction during RT . Functional imaging, including DCECT, is of increasing availability in veterinary medicine yet still poorly studied. Further research in this field might be extremely valuable, with potential to help refine the diagnosis and prognosis, guide the choice of treatment, assess the treatment response, and detect recurrence in dogs with brain tumors.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The animal study was reviewed and approved by Research Ethics at the Institute of Veterinary Science of the University of Liverpool (VREC560a). Written informed consent was obtained from the owners for the participation of their animals in this study.JM, TM, VB, LB, and ML: conception and design. JM and LB: acquisition of data. JM and TM: analysis and interpretation of data. JM, LB, and TM: drafting the article. JM, TM, VB, LB, and ML: revising article for intellectual content, final approval of the completed article, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. All authors contributed to the article and approved the submitted version.The authors received a research grant from the University of Liège for this work (FSR 2018).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Ailuropoda melanoleuca), a global symbol of conservation, are believed to be involved in the host’s dietary switch to a fibrous bamboo diet. However, their exact roles are still largely unknown.The gut microbiota of the giant panda (n = 322), including 98 pandas sequenced in this study with deep sequencing (Illumina) and third-generation sequencing (nanopore). We reconstructed 408 metagenome-assembled genomes (MAGs), and 148 of which (36.27%) were near complete. The most abundant MAG was classified as Streptococcus alactolyticus. A pairwise comparison of the metagenomes and meta-transcriptomes in 14 feces revealed genes involved in carbohydrate metabolism were lower, but those involved in protein metabolism were greater in abundance and expression in giant pandas compared to those in herbivores and omnivores. Of note, S. alactolyticus was positively correlated to the KEGG modules of essential amino-acid biosynthesis. After being isolated from pandas and gavaged to mice, S. alactolyticus significantly increased the relative abundance of essential amino acids in mice jejunum.In this study, we first comprehensively analyzed a large number of gut metagenomes giant pandas (S. alactolyticus is an important player in the gut microbiota that contributes to the giant panda’s dietary adaptation by more involvement in protein rather than carbohydrate metabolism.The study highlights the unique protein metabolic profiles in the giant panda’s gut microbiome. The findings suggest that Video AbstractThe online version contains supplementary material available at 10.1186/s40168-023-01603-0. Ailuropoda melanoleuca), a flagship species for wildlife conservation worldwide, was upgraded from an endangered species to a vulnerable category in 2016  , medium , and low . The KEGG pathways related to essential amino-acid biosynthesis, including map00290 , map00300 (Lysine biosynthesis), and map00400 , were analyzed based on metagenomic sequencing reads. Comparative analysis revealed that the abundance of map00300 KEGG pathway  and low  groups. For the map00290 KEGG pathway , while trended to be higher in the high group than in the low group with no statistical significance (P = 0.073) Fig. Plant proteins often lack or are insufficient in some essential amino acids required by animals. To explore whether gut microbiome helped the host to synthesize essential amino acids, we analyzed the abundance of genes involved in essential amino-acid biosynthesis in S. alactolyticus from pandas, then administered it to BALB/c mice with low and normal protein diets via oral gavage. Forty-eight mice were randomly assigned into four groups . All mice were sacrificed 3 weeks after the end of treatment, and jejunal contents were collected. A total of 16 amino acids, including 9 non-essential amino acids and 5 essential amino acids, were detected using untargeted metabolomics by LC–MS  and essential amino acids  in the LS group were significantly higher than the LC group. The non-essential amino acids  and essential amino acids  were higher in the NS group, but without statistical significance. In particular, the abundance of L-Valine (LC vs. LS: P = 0.039) and L-tyrosine (LC vs. LS: P = 0.027) were significantly higher in S. alactolyticus treatment groups for the low protein diet, while L-glutamic acid (NC vs. NS: P = 0.033) was significantly enriched in the treatment group (NS) when normal protein diet was fed.To verify its role in synthesizing the essential amino acid in the gut, we first isolated S. alactolyticus) of the panda’s gut microbiota and verifying its roles in the biosynthesis of essential AAs in a mice experiment.As one of the “vulnerable of extinction animals,” the giant panda is a symbol of wildlife conservation. The metagenomic analysis provides insight into not only the microbial composition but also the metabolic potential of the gut microbiome in giant pandas. Several studies based on metagenomic data have suggested that the gut microbiome of giant pandas plays a crucial role in the energy metabolism, environmental adaptation, and health , 11, 31.n = 408) by substantially expanding the sample size (n = 322) and sequencing depth using both next- and third-generation sequencing technologies. Of note, we sequenced 98 samples with a much greater sequencing depth  than previous studies in giant pandas as well as in recent studies focusing on MAGs construction in pigs (11.46 Gbp/sample) [The reconstruction of MAGs has become a common task for microbiome studies as it provides critical insights into the microbial diversity, composition, and functions of a specific niche. Therefore, several studies have reconstructed MAGs in many mammalian species, such as humans , mice 1, pigs 2, and chi/sample) . In addi/sample) , 34, 35./sample) , 33.S. alactolyticus as the most abundant MAG, consistent with findings in our previous study [Streptococcus was the most abundant genus in the gut of captive giant panda. Jin’s study [Streptococcus as the second most abundant genus using a 16 s rRNA-based method. The discrepancy between these two studies might be due to the technology used to study the microbiome. Nevertheless, although S. alactolyticus has been reported as an opportunistic pathogen in humans [Streptococcus, although species-level classification was not available for these MAGs. Of note, 202 of the 408 MAGs did not match any existing reference genomes in the GTDB, suggesting that our data substantially expanded reference genomes in the gut microbiome of giant pandas at the species level.Among the 408 MAGs, 206 were classified into 149 bacterial species from the Genome Database Taxonomy (GTDB), with us study  that Str’s study  identifin humans , it has n humans , 38, chin humans , dogs [4n humans , and pign humans . InteresGiant pandas feed almost exclusively on highly fibrous bamboo that contains a large amount of cellulose and hemicellulose, which, if completely digested, would provide additional energy from carbohydrates. They were not fed any commercial diets. Due to the lack of genes involved in cellulose degradation in the host, there has been a growing interest in the gut microbiota’s functions in cellulose metabolism. Several metagenomics studies have shown the presence of genes encoding enzymes involved in digesting cellulose , hemicelBamboo is not only rich in fiber; it is also high in proteins, which provide about 61% of the energy in giant pandas, equivalent to that of the hypercarnivores as estimated by a macronutrient composition analysis . We thusE. flexneri and E. coli have been associated with infectious diseases in humans and other animals, and their abundances were relatively high in pandas’ guts. However, the expression levels of these species were relatively low, and the pandas have been healthy, suggesting that these species were not that “active” and were not causing diseases. In addition, MAGs associated with Escherichia also possess genes involved in carbohydrate degradation. Therefore, it is difficult to draw any conclusions regarding their roles in pandas’ health or nutrition. Interestingly, S. alactolyticus (24.34%) was less abundant than E. flexneri (27.10%) based on the metagenomic data; however, its expression level was greater (45.45% vs. 10.49%), suggesting that S. alactolyticus may be an “active” member and plays a more prominent role in pandas’ gut microbiome.Metagenomics and meta-transcriptomics are important approaches to studying the gut microbiota in different animal species. Metagenomics provides insights into the metabolic potential of the microbiota, revealing the abundance of the major bacterial taxa and metabolic pathways. Meta-transcriptomics, on the other hand, captures the active bacteria and their functions by analyzing the expressed genes. Members of the gut microbiota switch from dormant to active states frequently. Therefore, the most dominant bacterial species might not necessarily be the most active species. In addition, the genes encoding the metabolic pathways may or may not be transcribed, depending on many variables. Consequently, there are often differences in the overall gut microbiota and specific taxa revealed by metagenomics and meta-transcriptomics , 45. In S. alactolyticus, suggesting that S. alactolyticus may be an important factor affecting essential amino-acid biosynthesis in the gut microbiota of giant pandas. To establish a causal relationship, we subsequently fed mice with S. alactolyticus. We detected a greater amount of both non-essential and essential amino acids in the jejunum of mice, suggesting the involvement of S. alactolyticus in essential amino-acid biosynthesis. Previous studies indicated that S. alactolyticus was a lactic acid-producing bacterium associated with carbohydrate fermentation [S. alactolyticus in amino-acid biosynthesis, suggesting this bacterium plays an important role in the host’s dietary adaptation to bamboos.Our analyses showed that KEGG modules of essential amino-acid biosynthesis were significantly enriched in giant pandas with a higher relative abundance of entation  and was entation . Giant pS. alactolyticus, the most abundant bacterial species, were involved in the protein metabolism of the intestinal of giant pandas. The unique protein metabolic profiles in the gut microbiome discovered in this study, the straight and short carnivore-like gut intestinal tract, together with the evolutionary adaptations in their teeth, skull, and pseudo-thumb needed to process bamboo [In this study, we reconstructed a total of 408 MAGs. These data not only substantially improved our view of microbial diversity and metabolic potential but also provided a foundation for future metagenomics studies. In addition, we also performed a pairwise investigation of metagenomes and meta-transcriptomes in a subset of the samples, which allowed us to distinguish between abundant and active bacteria and determine gene expression profiles involved in nutrient metabolism. Our data show that the gut microbiota in the giant pandas plays important roles in protein rather than carbohydrate metabolism. s bamboo , explainA total of 90 fecal samples were collected from 36 captive giant pandas at the Chengdu Research Base of Giant Panda Breeding and 54 captive giant pandas at China Research  and Conservation Center for the Giant Panda at Wolong . In addition, eight fresh fecal samples of wild giant pandas collected from Wolong Nature Reserve (China) were also included in this study. All stool samples were flash-frozen in liquid nitrogen and stored at − 80 °C until further processing. We also included 13 fresh fecal samples from healthy cats from the cat feeding base at Remigao Animal Nutrition and Health Technology Co., Ltd. . Fecal samples of cats were flash-frozen in liquid nitrogen and stored at − 80 °C until further processing.The total DNA was extracted from thawed feces of giant pandas and cats by using the Magnetic Universal Genomic DNA Kit  according to the manufacturer’s protocol. The DNA quality and integrity were assessed on 1% agarose gels. DNA concentration was measured using Qubit® DNA Assay Kit with a Qubit® 3.0 Fluorometer . Library preparation was performed using the NEB Next® Ultra™ DNA Library Prep Kit for Illumina  following the manufacturer’s recommendations. The qualified DNA libraries were sequenced on the Illumina NovaSeq 6000 (PE150) platform.The total RNA was extracted from the feces of giant pandas and cats using the RNAprep Pure Cell/Bacteria Kit . RNA quality and concentration were first examined using 1% agarose gels and a NanoPhotometer® spectrophotometer and then further confirmed with an RNA 6000 Nano Assay kit of the 2100 Bioanalyzer  and Qubit® 3.0 Fluorometer . The ribosomal RNA was depleted from total RNA using TRIzol  before meta-transcriptomic library construction, which was subjected to meta-transcriptomic sequencing on the Illumina NovaSeq 6000 (PE150) platform.n = 27) and Guo et al. [n = 197) in addition to the deep sequencing data generated in our study, resulting in a total of 322 gut metagenomes. The Kneaddata pipeline v0.7.2 (https://bitbucket.org/biobakery/kneaddata) was applied for quality control and removal of host contamination. In brief, Trimmomatic v0.39 [To construct comprehensive MAGs in giant pandas, we also downloaded additional shotgun metagenomic datasets of giant pandas from three previous studies by Wu et al.  (n = 27)o et al. , 26 (n =ic v0.39  in the pic v0.39 .https://github.com/tseemann/barrnap) and tRNAscan-SE [The hybrid assembly of contigs from the ONT and Illumina clean reads was carried out using both OPERA-MS  pipelineAscan-SE , respectAscan-SE . The taxAscan-SE  with theThe raw meta-transcriptomic dataset, coming from giant panda and cat sequenced in this study, and the other five host species downloaded from public databases, were processed with the Kneaddata pipeline described in the section described above to perform quality control and host-contaminant removal. SortMeRNA software (v4.3.2)  and SMR To determine the abundant versus the active bacterial taxa in giant pandas, we performed a pairwise comparison of the metagenome and metatranscriptome data in the 14 giant pandas. To this end, we first built a customized database using the genome sequences of the 408 MAGs based on the format of the Kraken2 taxonomic classification software . We thenQIIME2 version 2021.4  was usedn = 14) [n = 10) [n = 13) [n = 8) [n = 6) [To compare the abundance and expression of cellulose degradation-related genes, and amino acid degradation-related genes in giant pandas, and place these data in the context of mammalian dietary patterns, we downloaded five datasets containing both gut metagenomes and metatranscriptomes in cattle  , sheep ([n = 10) , humans [n = 13) , mice (f [n = 8) , and pig [n = 6) .P ≤ 0.05. Except where noted, the figures were generated with the R package ggplot2.For other host species , contigs assembly and gene prediction were separately performed for each species. Both metagenomic and metatranscriptomic data were analyzed as follows. A non-redundant gene catalog of each species was generated by clustering with CD-HIT-EST  at a cutS. alactolyticus, according to metagenomic analysis, were pooled and diluted 100-fold in PBS. The diluted solution was streaked on a brain heart infusion  agar plate. Agar plates were incubated anaerobically for 24 h at 37 °C. After that, colonies were picked and streaked on a new BHI agar plate for pure cultures. The isolated microbial colonies were used for DNA extraction, 16S rDNA sequencing using the Sanger sequencing method, and alignment by the online blast (https://blast.ncbi.nlm.nih.gov) to identify the taxonomy of these colonies. The colonies identified as S. alactolyticus were stored using a mixed solution of newborn calf serum (4%), glycerin (16%), and brain heart infusion (80%).Seven fecal samples from giant pandas with a higher relative abundance of n = 12/group), including LC, LS, NC, and NS groups. LC and LS were fed a low protein diet (10% crude protein), and NC and NS groups were fed with a normal-protein diet (18% crude protein). The mice in the treatment group of LS and NS groups were administered with S. alactolyticus solution by gavage on day 1, day 3, day 5, and day 7. In contrast, the mice from LC and NC groups were administered with PBS (phosphate buffer solution) as a negative control. All mice were fed with about 70% of the daily diet requirements (2.6 g), which were calculated based on the data during the period of pre-feeding. On day 28, all mice were slaughtered, and the intestinal digesta were collected from the jejunum. The sample of jejunal digesta was placed into a 2-ml polyethylene tube and then stored in liquid nitrogen to snap-freeze immediately.A total of 48 BALB/cJ female mice aged 6 weeks were purchased from a commercial company . These mice were housed in standard cages (1 mouse per cage) under an average room temperature of 25℃ with corncob bedding. After 3 days of acclimation, all mice were randomly assigned into four groups  method analyses by a commercial company . Firstly, jejunal digesta (100 mg) was grounded separately with liquid nitrogen; subsequently, the homogenate was resuspended with prechilled 80% methanol and 0.1% formic acid. The processed samples were incubated at 4 °C for 5 min, followed by high-speed centrifugation  for 5 min at 4 °C. Afterward, the supernatant was collected and diluted to a final concentration of 53% methanol with LC–MS grade water. Finally, the prepared samples were subjected to the LC–MS system for untargeted metabolomic analysis using the vanquish UHPLC system  and Orbitrap Q ACTIVETM HF mass spectrometer (Thermo Fisher Scientific). The raw data were furtherly processed using compound discoverer 3.1  to obtain the quantitation of metabolites.Additional file 1.


Here, we aimed to investigate long non-coding RNA (lncRNA) expression characteristics in the peripheral blood lymphocytes of Xinjiang Kazakh people with essential hypertension and the underlying regulatory mechanisms of competing endogenous RNAs (ceRNA).From April 2016 to May 2019, six Kazakh patients with essential hypertension and six Kazakh healthy participants were randomly selected from the inpatient and outpatient cardiology departments of the First Affiliated Hospital of Shihezi University Medical College, Xinjiang. After detecting the expression levels of lncRNA and mRNA in the peripheral blood lymphocytes using gene chip technology, their levels in the hypertensive group were compared with those in the control group. Six differentially expressed lncRNAs were randomly selected for real-time PCR to verify the accuracy and reliability of the gene chip results. GO functional clustering and KEGG pathway analyses were performed for differentially expressed genes. The ceRNA regulatory network of lncRNA-miRNA-mRNA was constructed, followed by visualization of the results. The expressions of miR-139-5p and DCBLD2 after PVT1 overexpression in 293T cells were detected by qRT-PCR and Western blot.In the test group, 396 and 511 differentially expressed lncRNAs and mRNAs, respectively, were screened out. The trend of real-time PCR results was consistent with that of the microarray results. The differentially expressed mRNAs were found to be primarily involved in the adhesion spot, leukocyte migration via endothelial cells, gap junction, actin cytoskeleton regulation, and extracellular matrix-receptor interaction signaling pathways. By constructing the ceRNA regulatory network, we found that lncRNA PVT1-miR-139-5p-DCBLD2 has a potential ceRNA regulatory mechanism involved in the development of essential hypertension in Xinjiang Kazakh people. In 293T cells, lncRNA PVT1 overexpression inhibited miR-139-5p and DCBLD2 levels.Our findings indicate that differentially expressed lncRNAs may be involved in the development of essential hypertension. lncRNA PVT1-miR-139-5p-DCBLD2 was indicated to comprise a potential ceRNA regulatory mechanism involved in the development of essential hypertension in the Xinjiang Kazakh population. Thus, it may act as a novel screening marker or therapeutic target for essential hypertension in this population. It is the most common chronic cardiovascular disease in China. Essential hypertension accounts for 95% of all hypertension cases. According to the Fifth National Hypertension Control Survey released by the National Center for Cardiovascular Diseases in 2018, the prevalence of essential hypertension in China has risen to 23.2%. In the next 5–10 years, the average number of people with hypertension is predicted to rise to 1.1 billion globally . In receIn China, there are distinct geographical differences in the prevalence of hypertension, with more people suffering from hypertension in the north than in the south, and the prevalence of hypertension varies among different ethnic groups and races . In 2017Gene-specific expression differences determine the pathological progression of individual diseases. Non-coding region genes account for 98.2% of the total number of human genes. Long non-coding RNAs (lncRNAs) play a key role in the regulation of gene expression and participate in the pathological process of the body . lncRNAs2.2.1.From April 2016 to May 2019, six Kazakh patients with essential hypertension and six Kazakh healthy subjects were randomly selected from the inpatient and outpatient cardiology departments of the First Affiliated Hospital of Shihezi University School of Medicine, Xinjiang.According to the diagnostic criteria of the Chinese Guidelines for the Prevention and Treatment of Hypertension 2018, hypertension is defined as the measurement of blood pressure thrice on different days without the use of antihypertensive drugs, with systolic blood pressure (SBP) ≥140 (mmHg) and/or diastolic blood pressure (DBP) ≥90 (mmHg).Inclusive criteria for this study were as follows: ≥38-year-old patients who were initially diagnosed with essential hypertension were included in the hypertension group. Kazakh healthy people with no history of hypertension and antihypertensive drug treatment, average systolic blood pressure values <140 mmHg, and average diastolic blood pressure values <90 mmHg, measured as per the aforementioned guidelines, were categorized as the control group.Exclusion criteria for this study were as follows: Patients with secondary hypertension complicated with malignant tumors, heart/renal failure, stroke, and autoimmune system, among other diseases. All subjects signed informed consent, and the study was approved by the ethics committee of the First Affiliated Hospital of Shihezi University .2.2.2.2.1.The following information on the Kazakh patients with essential hypertension and Kazakh healthy people was obtained: Gender, age, SBP, DBP, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein (LDL-C), serum creatinine (Scr), and alanine transaminase (ALT) levels.2.2.2.Peripheral venous blood (5 ml) was collected into EDTA anticoagulant blood collection tubes. The number of subjects was marked on the tube wall, and the anticoagulant blood vessels were mixed upside down. Peripheral blood lymphocytes were isolated by using Ficoll-Hypaque density gradient centrifugation, and Trizol reagent was added to the isolated peripheral blood lymphocytes, which were then stored in a refrigerator at −80°C for further analysis.2.2.3.Total RNA in cells was extracted using the Trizol one-step method, and the amount and quality of RNA were evaluated using NanoDropTM 2000 . RNA integrity was evaluated using an Agilent2100 bioanalyzer . Total RNA was subsequently purified using RNeasy Micro Kit  and RNase-Free DNase Set .2.3.P-value was <0.05, it was defined as a differential gene. The mRNA-lncRNA co-expression analysis was performed according to the gene expression correlation. Pearson correlation coefficient was applied to measure the correlation between lncRNA and the target genes. We then calculated the Pearson correlation coefficient matrix and performed a correlation analysis. Values of |r| > 0.9 and P < 0.05 were set as the threshold for subsequent analysis. The differentially expressed lncRNAs targeting mRNA were analyzed for the KEGG pathway and GO function enrichment.In this study, CapitalBio Technology Human LncRNA Array v4 chip was used to detect the gene expression profile of human species, and the lncRNA and mRNA expression profiles in peripheral blood lymphocytes were determined by Beijing Boao Jingdian Biotechnology Co., Ltd. Here, 12 microarrays were prepared using 12 specimens, and the samples were labeled with the Jingxin® Biochip Universal Labeling Kit. The chip scans were processed using Feature Extraction software to obtain the original data files; these files were imported into the GeneSpring software for chip data homogenization and difference analysis. Cluster 3.0 software was used for cluster analysis and graphical presentation. When the fold change (FC) of lncRNA or mRNA expression between the two groups was >1.5 and the 2.4.According to the selected differentially expressed lncRNAs, miRNAs interacting with them were matched using the miRcode prediction database, and target genes were screened using the miRNA target gene prediction databases . Based on the selected lncRNAs, miRNAs, and mRNAs, Cytoscape architecture was used to draw the ceRNA regulatory network.2.5.The human embryonic kidney cell line 293T used in this study was purchased from the Cell Bank of Chinese Academy of Sciences . The cells were cultured in DMEM medium , in which 10% fetal bovine serum , 100 U/ml penicillin and 100 µ g/mL streptomycin  were added, and then maintained in an incubator at 37°C with 5% CO2. The overexpression plasmid of PVT1 (vector as control) was obtained from GenePharma . 293T cells cultured to 70%–80% confluence were transfected with Lipofectamine 2000 .2.6.After the cell intervention, whole-cell protein lysate was collected and ultrasonically broken, centrifuged at 12,000 rpm at 4°C for 10 min, and protein supernatant was collected. BCA protein assay kit was used to determine the total protein concentration, and then 1 × loading buffer was added and boiled for 5 min. During electrophoresis, protein in each group of samples was added according to the total amount of 30 µg per well. After electrophoresis, the protein in the gel was transferred to the PVDF membrane in the sequence of sponge—filter paper—gel—PVDF membrane—filter paper—sponge. After electrolysis, the membrane was closed with 5% BSA solution for non-specific binding sites. The antibody was diluted with TBST solution containing 1% BSA in accordance with the dilution ratio provided in the antibody instructions, and incubated at 4°C overnight. PVDF membrane was washed, secondary antibody was added, and incubated at room temperature for 90 min. 1 × TBST cleaning membrane was used and images were taken using the Tanon imaging system .2.7.−ΔΔCT. The primer sequences for qRT-PCR are summarized in qRT-PCR was performed through using SYBR Green PCR Kit , the experiment was performed in accordance with the product specification. lncRNA, miRNA and mRNA expression levels were detected by ABI 7900HT fluorescence quantitative PCR, and the relative quantitative analysis of data was performed by 22.8.r = 0.9 and P < 0.01. The GO and KEGG pathway bubble maps of key lncRNAs were displayed using the clusterProfiler package. All statistical analyses were performed using 0SPSS 20.0  and GraphPad Prism version 8.0.0 . Data consistent with normal distribution were expressed as mean ± SD, and comparison between groups was performed by t-test. The data of non-normal distribution were expressed by median, and enumeration data were compared using χ2 test. The experimental data of qRT–PCR were analyzed using 2−△△Ct. P < 0.05 indicated statistically significant difference.We used the R language for statistical analysis, the psych package for principal component analysis, and the ggplot2 package for three-dimensional mapping. The limma, pheatmap, and ggplot2 packages were used for t-test, heatmap, and volcano maps, respectively. The normalized fluorescence signal values of the selected differential lncRNA and mRNA were imported into the psych package for the Pearson correlation coefficient, and the threshold was set at 3.3.1.P > 0.05). Compared with those of the control group, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) values of the hypertensive group were significantly different , total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein (LDL-C) of the two groups of patients; no statistically significant difference was observed  and βγ (Gβγ) and PLC  is a mechanotransduction-sensitive protein that plays a critical role in regulating cytoskeleton reorganization, programming cell proliferation, and regulating cell migration . FAK is DCBLD2, a protein-coding gene located on chromosome 3, is a neurofibromin-like transmembrane protein that is upregulated in mRNA levels during arterial remodeling and may be involved in angiogenesis and tumorigenesis progression  is located in the cancer risk area 8q24.21. lncRNA PVT1 can bind and degrade miR-26b, promote the expression of connective tissue growth factor and angiopoietin-2, and thus regulate the angiogenesis of vascular endothelial cells . Moreovegression . DCBLD2 gression . It repogression . TherefoThis study has some limitations. The number of included samples was limited; this may lead to some bias in the number of screened lncRNAs and mRNAs. Some analyzed biological processes may also be missing. We used only bioinformatics methods for preliminary exploration in this study. Therefore, future cell and animal experiments are needed to further study the core ceRNA network and its key lncRNAs.5.In this study, by analyzing the differences in lncRNA and mRNA expression in the peripheral blood lymphocytes of Xinjiang Kazakh people with essential hypertension, we successfully constructed the relevant ceRNA regulatory network. Concurrently, our findings revealed that the differentially expressed lncRNA targeted genes were enriched in focal adhesion, gap junctions, regulation of actin cytoskeleton, ECM-receptor interaction, and other pathways involved in the pathogenesis of hypertension. Furthermore, we constructed a ceRNA regulatory network related to differentially expressed lncRNAs, among which lncRNA PVT1-miR-139-5p-DCBLD2 may have a potential ceRNA regulatory mechanism in the occurrence of essential hypertension in Xinjiang Kazakh people.