To investigate the diagnostic accuracy of fecal calprotectin (FC) for inflammatory bowel disease (IBD) and organic gastrointestinal disease (OGID) in primary care. To examine the association with demographic factors, symptoms and concomitant medical therapy.A retrospective analysis of data on all semiquantitative FC tests from individuals ≥18 years conducted in primary care in Östergötland County in 2010. A 5‐year follow‐up with inclusion of new gastrointestinal diagnoses.A total of 1293 eligible patients were included. IBD was found in 8.8% and other OGID in 30.8% of patients with positive FC. Positive FC was associated with diarrhea, age >60 years, duration <3 months, use of nonsteroidal anti‐inflammatory drug (NSAID), and proton pump inhibitor (PPI). Predictors of IBD were positive FC, diarrhea, rectal bleeding, and male sex; predictors of OGID positive FC, age >35 years, abnormal clinical findings, and duration <3 months. FC yielded the highest sensitivity and negative predictive value compared with demographic factors, symptoms, and duration. Use of NSAID and PPI showed a marginal increase in the sensitivity, positive predictive value, and decrease in the specificity of FC. Within 5 years, 4.0% had a new gastrointestinal diagnosis among patients with positive FC (0.6% IBD).FC reliably rules out IBD and contradicts the presence of other OGID in primary care patients. Positive FC test together with other predictors, such as diarrhea, rectal bleeding, short duration, or age >35 years, should encourage a prioritized investigation. Use of NSAID, PPI, and ASA may affect the diagnostic accuracy of FC for IBD and OGID. Fecal calprotectin reliably rules out IBD and contradicts the presence of other OGID in primary care patients. Treatment with nonsteroidal anti‐inflammatory drugs and proton pump inhibitors may affect the diagnostic accuracy of fecal calprotectin. Patients with gastrointestinal (GI) symptoms represent approximately 10% of primary care appointments and are a frequent diagnostic challenge for general practitioners (GPs).Fecal calprotectin (FC) is reported to be a reliable marker of intestinal inflammation. It is a useful tool for differentiating between inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), and monitoring of disease activity in IBD patients.et al.The measures of FC test accuracy have mainly been performed in selected secondary care populations, and the evidence available from primary care is still limited.The aim of the present study was to determine the diagnostic accuracy of FC for IBD and organic GI disease (OGID) in primary care patients with gastrointestinal symptoms and to examine the association with demographic factors, symptoms, and concomitant medical therapy.Data on all semiquantitative FC tests analyzed in Östergötland County in 2010 were retrieved from the Department of Clinical Chemistry, Center for Diagnostics, Linköping University Hospital, Sweden. At that time, just over 343 000 people ≥18 years lived in the county.Medical records were retrospectively reviewed in 2013, with focus on patients' GI problems and investigation results. Data collected were sex, age, symptoms, and symptom duration  thoroughly reviewed patients' medical records and chose the significant diagnosis, that is, that which correlated clinically with patients' symptoms and examination results. IBD and tumor diagnoses were prioritized. For example, if the investigation revealed ulcerative colitis (UC) and gastroesophageal reflux disease in a patient presenting with diarrhea and rectal bleeding, UC was chosen.Subsequently, a follow‐up was performed, by retrieving all records from Östergötland County between 2010 and 2015, pertaining to the ICD‐10 diagnosis code groups C‐D (Neoplasms) and K (Diseases of the digestive system). This aimed to identify any possible missed cases of IBD or OGID in patients with a negative FC test, in whom the GPs did not proceed with further investigation. Patients were matched to those included in our study and only diagnoses related to the GI tract were selected. Diagnoses made in 2010 were excluded, as these were already reviewed during the primary analysis. Diagnoses were compared with previous results of investigations as well as patients´ known GI conditions and only new GI findings were included. The follow‐up took place during the time the patients lived in Östergötland or until death.FC was analyzed with the semiquantitative immunochromatographic rapid test PreventID® CalDetect®  at the Department of Clinical Chemistry, Center for Diagnostics, Linköping University Hospital. It is an immunological lateral flow test for the detection of human calprotectin via gold‐conjugated anti‐calprotectin antibodies. The results are expressed as FC concentrations of <15 mg/kg, 15–60 mg/kg, or >60 mg/kg. According to the manufacturer, the test is considered positive when the concentration is ≥15 mg/kg.p value <0.10 were included in a binary logistic regression model. Predictors of IBD and OGID selected in the binary logistic regression were assessed for accuracy . Confidence intervals for sensitivity, specificity, NPV, and PPV were calculated using the method described by Newcombe with continuity correctionp value <0.05 was considered statistically significant.Statistical analyses were performed using SPSS version 27.0 . Data are presented as numbers, percentages, or median, range and interquartile range (IQR). Age was divided into three categories and hence regarded as a categorical variable. Fisher's exact test or Pearson's chi‐squared test was used for nominal data to compare proportions. Clinical variables that showed a The Regional Ethical Review Board approved the study protocol (Dnr 2011/467–31) and subsequently the amendment pertaining to a 5‐year follow‐up (Dnr 2016/456–32).n = 269) and tests that had not been conducted in primary care (n = 149) were excluded. Subsequently, FC tests in patients occurring more than once (n = 82), patients with missing journal records (n = 1), and previously known diagnosis of IBD or GI cancer (n = 8) were also excluded. Finally, 1293 eligible patients were included  , 154 patients on PPI , 70 patients on ASA , and 69 patients on combination of these .Distribution of patient characteristics according to FC outcome is presented in Table P < 0.05); however, only NSAID and PPI were found to be significant in the binary logistic regression.The use of NSAID, PPI, and ASA was associated with a positive FC in the univariate analysis . Of those with positive FC, 8.8% were diagnosed with IBD and 30.8% with OGID , compared with 0.1% and 9.5%, respectively, of those with negative FC tests. In contrast, a higher proportion of patients with negative FC had functional GI disorders  and other diagnoses in the GI tract.Tables n = 13), according to the Montreal classification, the most common age group was >40 years (61.5%), colonic disease (38.5%), and non‐stricturing and non‐penetrating behavior (92.3%) (Table In patients diagnosed with Crohn's disease (ehavior 9.3% (TablP < 0.05) but found to be nonsignificant in the binary logistic regression. Abdominal pain was more commonly found in negative FC patients (P < 0.05) and apart from that, it did not have any statistical significance.Associations between IBD, OGID, and clinical outcome variables were further explored statistically Fig. . The likP < 0.05) but not in the binary logistic regression.OGID was associated with positive FC (OR = 3.75), higher age , and abnormal findings in abdominal physical examination (OR = 3.14). The likelihood of OGID was lower in patients with duration >3 months (OR = 0.55). Significant association with sex, gases, diarrhea, and stool consistency fluctuations was seen for OGID in the univariate analysis (P < 0.05). However, none of the drugs showed significant associations with IBD or OGID by binary logistic regression  moved to another county and were lost to follow‐up. New GI diagnoses were found in 78 patients  was found in 39.6% of patients with positive FC, which is in line with previous studies that found an organic diagnosis in 13–37% of primary care patients.et al.et al.,et al.Abdominal pain has been shown to be a rather nonspecific predictor of IBD and OGID. Despite the selected primary care population in studies by Pavlidis et al.Use of NSAID and PPI was significantly associated with positive FC in our study, and PPI showed the strongest association. This concords with the findings by Lundgren et al., the CalDetect test exhibited a sensitivity of 100%, specificity of 94.5%, PPV of 82.1%, and NPV of 100%, at a cutoff of ≥15 mg/kg.et al.In the differential diagnosis of IBD and IBS, according to Otten The main strengths of the present study are the large, unselected, heterogeneous primary care population and FC testing performed in connection with symptom presentation. FC has been shown to be a useful tool for the assessment and follow‐up of IBD,However, the study also has some limitations. Our data are based on medical records and not patient questionnaires. Hence, there is a risk that GPs did not record the symptoms correctly and some symptoms may not have been included. This, however, seems to reflect daily practice. Hence, the 5‐year follow‐up helped to identify any possible missed cases of IBD or OGID. Data collectors were not blinded for the FC test results, which may have introduced a review bias. The blinding was not possible because the result was presented in the patients' medical records. This, however, should not have altered the collector's interpretation of the index test as the investigations and diagnosis were already recorded by the treating physician. However, a selection bias may have been introduced because only the FC test and no demographic or clinical patients' characteristics constituted the eligibility criteria for this study. Consequently, a rather higher proportion of women in the study cohort, may have potentially resulted in a reduced likelihood in women for IBD and OGID. An additional concern was the lack of reliable information regarding the duration of drug utilization in the medical records.Furthermore, when planning this study, little evidence of FC testing in general practice was available. The semiquantitative FC analysis, which constituted a base for the present study, has in the meantime been replaced by fully quantitative laboratory‐based tests. Several studies compared various rapid tests with Enzyme‐linked Immunosorbent Assay (ELISA) and found that they compared well across a range of FC levels.This retrospective study confirms a high NPV of FC in primary care patients ≥18 years with GI symptoms. It reliably rules out IBD and contradicts the presence of other organic GI diseases. A positive FC test together with other predictors, such as diarrhea, rectal bleeding, short duration, or age >35 years should encourage a prioritized investigation. Combining FC with other significant predictors of IBD and OGID increases the specificity and PPV but tends to decrease the sensitivity. Although the likelihood seems to be low, the use of NSAID, PPI, and ASA may affect the diagnostic accuracy of FC for IBD and OGID.Table S1. Clinical characteristics of participants with negative and positive fecal calprotectin (FC) at cut‐off 60 mg/kgTable S2. Final diagnoses—Other gastrointestinal (GI) inflammatory conditions and Other diagnoses and conditionsTable S3. Results of the univariate and binary logistic regression analysisTable S4. Results of the 5‐year follow‐up. The number and valid percentage of patients diagnosed with a new gastrointestinal (GI) disease within 5 yearsClick here for additional data file.


We aimed to identify the neurotrophic activities of apigenin  via its coordination with brain‐derived neurotrophic factor (BNDF) and an elevated signaling of tyrosine kinase receptor B (Trk B receptor).25‐35‐induced cellular stress was revealed by propidium iodide staining, mitochondrial membrane potential, bioenergetic analysis, and formation of reactive oxygen species levels. Activation of Trk B signaling was tested by western blotting.The direct binding of apigenin to BDNF was validated by ultrafiltration and biacore assay. Neurogenesis, triggered by apigenin and/or BDNF, was determined in cultured SH‐SY5Y cells and rat cortical neurons. The amyloid‐beta (Aβ)25‐35‐induced cytotoxicity and mitochondrial dysfunction. The synergy could be accounted by phosphorylation of Trk B receptor, and which was fully blocked by a Trk inhibitor K252a.Apigenin and BDNF synergistically maintained the cell viability and promoted neurite outgrowth of cultured neurons. In addition, the BDNF‐induced neurogenesis of cultured neurons was markedly potentiated by applied apigenin, including the induced expressions of neurofilaments, PSD‐95 and synaptotagmin. Moreover, the synergy of apigenin and BDNF alleviated the (Aβ)Apigenin potentiates the neurotrophic activities of BDNF through direct binding, which may serve as a possible treatment for its curative efficiency in neurodegenerative diseases and depression. In cultured human neuroblastoma SH‐SY5Y cells and rat neurons, the synergistic effects of apigenin with BDNF in stimulating the BDNF‐induced neurite outgrowth and protective effect against amyloid‐beta was demonstrated: this synergism was mediated by a direct interaction between BDNF and apigenin, through activating the signaling cascade of high‐affinity BDNF receptor, Trk B. Many brain diseases, e.g., Alzheimer's disease (AD), depression, are closely associated with decreased level of neurotrophic factors, particularly, the amount of BDNF.The binding of BDNF to its specific receptor Trk B triggered the receptor autophosphorylation and the downstream cascades, e.g., extracellular signal‐regulated kinase 1/2 (ERK1/2), protein kinase B (Akt), phospholipase C‐γ1 (PLCγ1), and cAMP response element‐binding protein (CREB). The induced signalings are accounting for the functions of BDNF in growth, differentiation, survival, plasticity of neurons. Several neuronal cell lines, e.g., NT‐2/D1, SH‐SY5Y, PC12 cells being transfected with cDNA encoding Trk receptor, have been utilized to demonstrate the functionality of BDNF.Flavonoid is a class of compounds commonly found in fruits and vegetables, showing large varieties of pharmacological activities, including beneficial effects to the brain.25‐35‐induced cell toxicity and mitochondrial dysfunction was determined. Coinciding with the enhanced BDNF function, apigenin potentiated the BDNF‐triggered Trk B receptor for its autophosphorylation and dimerization, thereby activating the receptor signaling cascades. This study provides a new rationale in developing apigenin as nutraceutical products to treat neurotrophin deficiency‐associated neurodegenerative diseases and depression.In search for active phytochemical, the binding of apigenin to BDNF was evidenced by molecular docking, ultrafiltration assay, and biacore assay. The roles of apigenin in facilitating the BDNF‐induced neurogenesis were demonstrated in cultured SH‐SY5Y cells and rat cortical neurons. Meanwhile, the coordination of apigenin and BDNF in reducing the Aβ22.125‐35, retinoid acid, oligomycin, carbonyl cyanide 4‐(trifluoromethoxy)phenylhydrazone (FCCP), and rotenone/antimycin A were purchased from Sigma‐Aldrich. Aβ25‐35 was dissolved in Milli‐Q at 2 mM and incubated at 37°C for 2 days before being applied to the cultures. An inhibitor of TrkB, k252a, was purchased from Cell Signaling Technology. Probes of propidium Iodide (PI), tetramethylrhodamine ethyl ester perchlorate (TMRE) and dihydroethidium (DHE) were obtained from MedChemExpress. MitoSOX and all the culture reagents were from Thermo Fisher Scientific.Apigenin, >98% purity determined by HPLC, was obtained from the Yuanye Biotechnology. Human BDNF was purchased from Alomone Labs. Amyloid‐beta (Aβ)2.2https://www.biosolveit.de/), as below (i) The binding site was determined according to the residues forming the identified druggable pocket. Ligand binding states, including protonation and tautomeric forms, were subsequently evaluated using ProToss method to generate the most accessible hydrogen network. (ii) Docking modulation was performed using the “Compute LeadIT Docking” mode in the FlexX algorithm; 10 binding conformations for each ligand were generated. (iii) The binding energy  and estimated HYDE affinity (KiHYDE) for each ligand pose were calculated using the “Assess Affinity with HYDE in SEESAR” mode in HYDE rescoring function.Chemical structures of molecules were downloaded from PubChem, and the protein structure of BNDF protein was downloaded from Protein Data Bank (PDB ID:1B8M). Virtual screening was performed on SEESAR software . Briefly, BDNF (20 μg/mL in water) was sufficiently captured by a CM5 sensor chip when flowing across the surface of chip. The coupling buffer was 10 mM NaAC, 150 mM NaCl, pH at 5.5. Apigenin was diluted into series concentrations of the running buffer  and then sequentially flowed across the chip for analysis. The regeneration was performed with 10 mM glycine–HCl solution, pH 2.0. The increased response resonance units (RUs) were instantly recorded for each apigenin solution after attaining a steady state. Data were fitted to a steady affinity model in Biacore T100 software, with the calculated KD value.2.52) with DMEM medium containing 15% FBS. SH‐SY5Y cells were seeded onto 6‐well plate (2 × 104 cells/mL) and incubated for 24 h. The medium was replaced by 2% FBS DMEM supplemented with 10 μM retinoid acid. Following 4 days of pretreatment with retinoid acid (replace with fresh medium in between), cultures were changed into nonserum DMEM medium with BDNF, or apigenin, for another 3 days of culture. Cells were fixed by 4% paraformaldehyde prior to being photographed via a phase‐contrast microscope (Carl Zeiss). A cell/cell clump with at least one visible neurite connecting to neighbored cells was counted as the cell with neurites. The percentage of cells with connected neurites was calculated according to >100 cells from 5 randomly selected imaging fields for each well. To test the neurotrophic function of apigenin and BDNF in maintaining the cell viability in nonserum stress, cells were seeded in a 96‐well plate at a density of 5 × 104 cells/mL, followed by 4 days of retinoid acid pretreatment, as well as 2 days of apigenin/BDNF treatment. The Aβ25‐35 protective effect of apigenin/BDNF was carried out in DMEM medium with 2% FBS. One hour after BDNF/apigenin treatment, Aβ25‐35 was applied to the cultures for 24 h.Human neuroblastoma, SH‐SY5Y cells (ATCC 1721), were cultured in a humidified incubator ‐2,5‐diphenyl tetrazolium bromide (MTT) methods. Cells were cultured in 96‐well plate for indicated time and drug treatment. MTT was diluted in basal DMEM at the final concentration of 0.5 mg/mL, which was then applied to cells by replacing the prior culture medium. After 4 h of incubation, DMSO was used to lyse the cells and absorbance at 570 nm was recorded by a microplate reader. The reading was adjusted by deducting the value of blank well, and then normalized by the untreated control group.2.7For SH‐SY5Y cells, the transfection of pNF200‐Luc constructs was performed by jetPRIME (Polyplus) reagent on the fourth day of retinoic acid induction. Subsequent to 6 h of transfection, the medium was replaced by 2% DMEM with apigenin/BDNF for 2 days of treatment. Lipofectamine 3000 (Thermo Fisher Scientific) was used for the transfection of cultured neurons. Six hours after transfection, cells were exposed to apigenin and BDNF for 2 days. Luciferase assay was performed by a commercial kit (Thermo Fisher Scientific), and the intensity was detected in a luminometer (Promega). The value of each sample was normalized by protein concentration.2.825‐35 treatment, the cells were washed once with PBS, and stained with Hoechst 33342 (5 μg/mL) for 10 min, followed by 15 min of PI (2 μg/mL) staining. Images were taken via Celldiscoverer7 (Carl Zeiss), and the density of PI‐positive cells was calculated for at least 5 fields. In immunofluorescent analysis, the cells cultured on coverslip were fixed with 4% PFA and were blocked by PBST (PBS + 0.2% Tween 20) with 4% BSA and 0.3% Triton X‐100. After washing, the primary antibodies, PSD95 and MAP2  diluted in 1% BSA in PBST, were employed at 4°C. Following overnight incubation, the secondary antibody conjugated with Alexa 594  was used to probe the protein targets. After loading with DAPI in mounting medium, the images for MAP2 and PSD95 stainings were taken via Celldiscoverer7 and LSM980 confocal microscope (Carl Zeiss), respectively.Upon 24 h of Aβ2.925‐35 treatment, JC‐1 probe (1 μg/mL) was dissolved in basal DMEM and loaded to PBS‐rinsed culture for 30 min of staining at 37°C incubators. Following another PBS washing step, the fluorescence intensity ratio of red (Ex: 525 Em: 595) to green (Ex: 490 Em: 530) was tested via FlexStation microplate reader . Dihydroethidium (DHE) and MitoSOX were used to label the intracellular ROS and mitochondrial ROS, respectively, in SH‐SY5Y cells. Following 24 h of Aβ25‐35 treatment, the cultures were twice washed with PBS, and then applied with 20 μM DHE or 5 μM MitoSOX dissolved in basal DMEM. After 30 min of incubation, cells were washed, and images were taken via Celldiscoverer7. The density of DHE‐positive cells, as well as the averaged fluorescent intensity of MitoSOX, were analyzed.To determine the change of mitochondrial membrane potential (MMP) in cultured SH‐SY5Y cells and cortical neurons after Aβ2.1025‐35 challenge for 24 h. Afterward, the medium was gently changed with Agilent XF seahorse DMEM and incubated for 2 h in 37°C incubator without CO2. Then, the mini assay plate was inserted into the Seahorse machine with the help of a Seahorse XFp‐extracellular flux cartridge (Agilent) that was preloaded with mitochondrial uncouplers and inhibitors, i.e., oligomycin (complex V inhibitor), FCCP  and a mixture of antimycin A/rotenone . After being added to the cells, the final concentrations of those inhibitors were 1, 3, and 1 μM, respectively. The real‐time oxygen consumption rate (OCR) was collected for baseline and after sequential injection of three mitochondrial inhibitors. In total, 12‐time points were recorded, and the result of each well was normalized by protein concentration determined by the Bradford method.Bioenergetic features of the SH‐SY5Y cells were measured by using Seahorse XFp Extracellular Flux Analyzer (Agilent). Briefly, the cells were seeded in Seahorse XFp‐cell culture miniplate (Agilent), and then applied with apigenin/BDNF preincubation for 1 h, as well as Aβ2.11The cells were collected and lysed on ice with lysis buffer , supplemented with 100 mM PMSF. After configuration, the supernatant was mixed with a 5 × SDS‐PAGE gel loading buffer, and the protein concentration of each sample was determined. An 8% gel was applied in SDS electrophoresis with loading amount of 25 μg per well. After gel separation, proteins were electrically transferred to the nitrocellulose membrane. The unspecific sites were blocked with 2.5% BSA, and the primary antibody was employed overnight at 4°C. Monoclonal HRP‐conjugated secondary antibody was employed to detect the blots and was visualized by a Pierce ECL substrate (Thermo Fisher Scientific). For the quantification of phosphorylated targets. Apigenin and BDNF was added to the cultures for 15 min of incubation. The supernatant was then immediately aspirated, and the cells were digested with 2 × direct lysis buffer . The primary antibodies against β‐actin, neurofilament‐68 (NF68), neurofilament‐160 (NF160), neurofilament‐200 (NF200), PSD‐95, synaptotagmin, Trk B, phospho‐p44/42 MAPK (ERK1/2) (Thr202/Tyr204), p44/42 MAPK (ERK1/2), phospho‐Akt (Ser473), Akt, PLCγ1, phospho‐PLCγ1 (Tyr783), phospho‐CREB (Ser133), and CREB were purchased from Cell Signaling Technology. Phospho‐Trk B (Tyr705) was obtained from Sigma‐Aldrich. The protein bands were photographed under the ChemiDoc system (Bio‐Rad), and the intensities were analyzed by Image J.2.12p < 0.05.The amount of protein was determined by the Bradford protein assay. All the statistical analyses were performed in GraphPad prism 8.00 software. The Shapiro–Wilk test was employed to assess the normality for all the data. The two‐tailed unpaired t‐tests was used for comparison of two groups. Difference among multiple groups was evaluated by One‐Way ANOVA with Bonferroni post‐hoc test. When data failed to pass the normality test, the Mann–Whitney and the Kruskal–Wallis tests were used as non‐parametric equivalents. Statistical significance was determined as (*) when 33.1Flavonoids have been shown binding to NGF, and thereafter which potentiated the neurotrophic functions of NGF.KD value at ~14.2 μM. These results indicated a direct binding of apigenin to BDNF . In contrast, high concentrations of Aβ declined MMP in both cultures, and Aβ at 10 μM was able to trigger a ~50% MMP loss Figure . In corr3.6BDNF triggers Trk B receptor for its autophosphorylation and dimerization, thereby activating the receptor signaling cascades. The aforementioned synergy of BDNF and apigenin could be mediated by enhancement of Trk B receptor activation. Thus, the phosphorylation level of Trk B, stimulated by BDNF in the presence or absence of apigenin, was identified Figure . In SH‐STo show the receptor specificity, a Trk inhibitor K252a was utilized to validate the neurotrophic activities mediated by the synergy of BDNF and apigenin. The phosphorylation of Trk B, as well as its downstream signalings of p‐ERK, p‐Akt, p‐PLCγ, p‐CREB, was mostly blocked by applied K252a in both neuronal cultures Figure . Meanwhi4Similar to many other flavonoids, apigenin is a phytoestrogen with weak estrogenic property. Apigenin possesses superb anti‐oxidative and anti‐inflammatory effects, exerting potential therapeutical efficacy in treating a series of health problems. Several clinical trials have been conducted to validate its bioactivity, such as prevention of skin aging, increasing blood antioxidant enzyme, reducing recurrence risk of neoplasia, as well as pain relief in migraine. The chamomile extract having high amount of apigenin has been demonstrated, clinically, in reducing the depression rating scale of patients with a primary DSM IV Axis I diagnosis of generalized anxiety disorder.25‐35, apigenin was able to enhance the protective effects of BDNF in reducing the Aβ‐induced toxicity and mitochondrial dysfunction. Furthermore, apigenin alone could not activate the BDNF‐specific Trk B receptor, while together with BDNF, they showed synergy. The signaling specificity was validated by a Trk inhibitor, K252a, that blocked the activation of Trk receptor signaling, as well as the neurotrophic or neuroprotective properties, mediated by the co‐treatment of BDNF and apigenin.This study highlighted a direct interaction between apigenin and BDNF, as well as their functional synergy. We hypothesize that the binding of apigenin onto BDNF could potentiate the neurotrophic activities. Indeed, the combined usage of apigenin and BDNF at low‐concentration synergistically promoted viability and neurogenesis of cultured neuronal cells. When the cultures were exposed to AβApigenin possesses moderate permeability to BBB. A detection of 0.42 μg/g of apigenin, estimated to be ~1.55 μM, has been detected in mouse brain tissues after a single intraperitoneal administration of apigenin at 0.4 mg/g.Flavonoid is a popular class of compounds in searching for candidate drugs mimicking the function of neurotrophic factors. Some of the flavonoids have been reported to induce differentiation, or neurite outgrowth, of cultured neuronal cells, and these effects could be explained by the activations of Trk receptor, PI3K‐Akt, ERK1/2‐CREB, estrogen receptor, and calcium signaling.Among the neurotrophic factors, NGF is commonly considered to have synergy with candidate drugs to have higher activity of neurotrophic functions. The flavonoid‐induced neuronal differentiation could get potentiated when co‐applying with a small amount of NGF.Mature BDNF is a noncovalently associated dimer and is structurally similar to other neurotrophic factors. In our molecular docking result, the residues 8–116 of BDNF (PDB:1B8M) were recognized as a domain binding to Trk B receptor. Several H‐bonds were established between apigenin and amino acid residues, such as Glu9, Ser11, and Met61, which anchored the accommodation of the ligand at the binding domain. Here, we hypothesize that the apigenin/BDNF interaction could increase the binding affinity of BDNF to Trk B receptor, which thereby leads to the enhancement of downstream signaling. However, the low solubility of flavonoid raises the question of whether the oral availability of apigenin could support its potentiating effects in vivo. We supposed the apigenin's metabolites may possess similar interaction with BDNF as apigenin does. In addition, the binding of flavonoids onto BDNF does not guarantee the functional activation. Among several other flavonoids with a good docking score to BDNF, only alpinetin showed a weak synergism with BDNF in inducing differentiation of SH‐SY5Y cells.Today, nutritionists have been dedicated to finding ways of increasing endogenous BDNF levels. Useful tips, such as regular exercise, everyday good sleep, intermittent fasting, as well as having more plant‐derived foods, may help to secrete more BDNF from the brain and to promote neurogenesis.Participated in research design: Tsim, Gao. Conducted experiments: Gao, Xia, and Lin. Performed data analysis: Gao, Xia, and Dong. Wrote or contributed to drafting the manuscript: Tsim, Gao. Editing and approval of final manuscript: All the authors.This work is supported by The Key‐Area Research and Development Program of Guangdong Province (File no. 2020B1111110006); Special project of Foshan University of science and technology in 2019 (FSUST19‐SRI10); GBA Institute of Collaborate Innovation (GICI‐022); Shenzhen Science and Technology Innovation Committee , Zhongshan Municipal Bureau of Science and Technology (ZSST20SC03); Guangzhou Science and Technology Committee Research Grant ; Hong Kong RGC Theme‐based Research Scheme (T13‐605/18‐W); and Hong Kong Innovation Technology Fund .The authors declare that they have no competing interests.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.


BRAF V600E was clustered in ESCAT I, with a prevalence of 3.7%, KRAS G12C and ERBB2 amplification were clustered in ESCAT II, whose prevalence was 4.2% and 1.6%, respectively. Most alterations were classified in ESCAT III  and IV , with a single prevalence under 5%, except for PIK3CA mutation (9%). The final rate of inclusion into genomically guided clinical trials was 2.7%, including therapies targeting BRAF V600E or RNF43 mutations in two patients each, and ERBB2 mutation in one patient. In conclusion, EGP programmes in patients with advanced CRC are feasible and identify a subset of patients with potentially druggable genomic alterations. However, further efforts must be made to increase the rate of patients treated with genomically guided therapies.Efficiency of expanded genomic profiling (EGP) programmes in terms of final inclusion of patients in genomically matched therapies is still unknown. Fit patients with advanced and refractory colorectal cancer (CRC) were selected for an EGP programme. Next‐generation sequencing (NGS) analysis from formalin‐fixed paraffin‐embedded tumour samples was performed. The purpose was to describe the prevalence of genomic alterations defined by the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT), as well as the percentage of patients finally included in genomically guided clinical trials. In total, 187 patients were recruited. Mutational profile was obtained in 177 patients (10 patients were failure due to insufficient tumour sample), copy number alterations in 41 patients and fusions in 31 patients. ESCAT‐defined alterations were detected in 28.8% of the intention‐to‐analyse population.  We have observed that an expanded genomic profiling programme in advanced colorectal cancer unveils druggable alterations in up to 30% of patients. However, the prevalence of these aberrations for single genes according to our programme is low, and the clinical benefit of their matched drugs is limited. Finally, our rate of inclusion in biomarker‐guided trials is under 3%. AKTAKT serine/threonine kinaseALKanaplastic lymphoma kinaseAnti‐EGFRanti‐epidermal growth factor receptorAPCadenomatous polyposis coliATMataxia telangiectasia mutatedBGTbiomarker‐guided trialsBRAFv‐Raf murine sarcoma viral oncogene homologue BCNAcopy number alterationsCRCcolorectal cancerCTNNB1catenin (cadherin‐associated protein), beta 1ECOGEastern Cooperative Oncology GroupEGFRepidermal growth factor receptorEGPexpanded genomic profilingERBBErb‐b receptor tyrosin kinaseESCATESMO Scale for Clinical Actionability of Molecular TargetsESMOEuropean Society for Medical OncologyFBXW7F‐box and WD repeat domain containing 7FFPEformalin fixed paraffin embeddedFGFRfibroblast growth factor receptorGNASguanine nucleotide binding protein (G protein) alpha stimulatingJAKJanus kinaseKRASKirsten rat Sarcoma virusmCRCmetastatic colorectal cancerMETMET proto‐oncogeneMMRmismatch repair systemMSI‐H/dMMRmicrosatellite instability high, deficient mismatch repairNGSnext‐generation sequencingNOTCHDrosophila) homologueNotch  antibodies [BRAF V600E mutation, Microsatellite Instability High/Deficient Mismatch Repair (MSI‐H/dMMR), POLE mutation, ERBB2 amplification, MET amplification or NTRK fusion, among others [RAS/BRAF and Mismatch Repair System (MMR) status are already recommended per clinical guidelines in all patients with mCRC, and they do not require the upfront use of broad NGS panels [per se, but also for the proper interpretation of the results and accessibility to clinical trials with innovative targeted drugs [Colorectal cancer (CRC) is one of worldwide leading causes of cancer death . The protibodies , 5. Beyog others , 8. DeteS panels . Third, ed drugs . ConsequIn this work, a cohort of mCRC patients included in a EGP programme with therapeutic purposes has been analysed. The final aim was to describe the landscape of druggable alterations according to ESCAT, as well as the final inclusion in genomically guided clinical trials.2Patients from Catalan Institute of Oncology who were included in an EGP programme between January 2015 and December 2020 and who met the following inclusion criteria were selected for the study cohort: (a) Refractory mCRC, defined by failure or intolerance to oxaliplatin, irinotecan, fluoropyrimidines, and antiangiogenics and anti‐EGFR, if both indicated; (b) Eastern Cooperative Oncology Group (ECOG) performance status (PS) 0 or 1; (c) No major comorbidities that could preclude participation in a clinical trial; (d) Availability of formalin fixed paraffin embedded (FFPE) sample, either from primary tumour or metastases. (e) Signed specific informed consent for tumour molecular profiling was approved by Local Ethics Committee . The study methodologies conformed to the standards set by the Declaration of Helsinki.KRAS and NRAS genes, and codon 600 of BRAF gene by Real Time Polymerase Chain Reaction (RT‐PCR) if RAS wild‐type (WT). MSI‐H/dMMR phenotype was determined through PCR or by immunohistochemistry, following ESMO recommendations [Local molecular profile consisted of hotspot analysis of codons 12, 13, 59, 61, 117 and 146 of Next‐generation sequencing analyses were performed within the Vall d'Hebron Institute of Oncology (VHIO) Molecular Prescreening Program. Mutations were determined through a custom amplicon‐based NGS assay (MiSeq) covering genes relevant for cancer study Table . Copy nuSummary tables of absolute and relative frequencies were used for descriptive analysis of categorical variables. Central value, average or median, and their values rank or 95% confidence intervals (CI) were applied for continuous variables.ibm® spss® statistics V22 .Overall survival (OS) was defined as the time between the date of diagnosis of metastatic disease and the date in which cancer death was documented. Patients were censored at the date of the last contact in the absence of cancer death. OS was calculated using Kaplan–Meier curves. Statistical analyses were performed with 33.1RAS mutant tumours, 8 (4%) BRAF V600E tumours and 6 (3%) MSI‐H/dMMR tumours, although MMR status was not fully completed in the whole cohort. Median number of pre‐EGP treatments for advanced disease was 2. One, two and three or more lines of treatment had been previously administered to 12 (6%), 82 (44%) and 93 (50%) of patients, respectively. Regimens had included approved anti‐EGFR drugs and antiangiogenics at some point of advanced disease in 87 (46%) and 82 (44%) cases, respectively. Ten patients (5%) had been enrolled in clinical trials before NGS analysis, one of which was a biomarker‐guided trial (targeting BRAF V600E). The median OS of the cohort was 35.9 months , after a median follow‐up of 39 months (3.13–138.8 months).One hundred and eighty‐seven patients were included in the study cohort, whose baseline characteristics are described in Table 3.2Procedures regarding NGS analysis are summarised in Fig. 3.3versus left‐sided CRC) and local molecular profile according to RAS status (RAS wild‐type versus RAS mutant). Local BRAF and MMR status were not considered for the interpretation of the results because they were unknown in 11 and 15 patients, respectively , TP53 , RAS  and PIK3CA . Intriguingly, some discrepancies were observed between local determination and NGS analysis regarding RAS. In previously reported as RAS wild‐type per local assessment, NGS analysis revealed KRAS and NRAS mutations in five and three patients, respectively. Tumour sample origin in which local PCR and NGS were performed was different in only one of them. Influence of anti‐EGFR treatment did not justify these findings in any case, because it was administered to patients after tumour sample collection. Conversely, RAS was mutated per local PCR in three cases, unlike NGS, even though tumour sample origin was the same for both analyses in all cases. Regarding BRAF gene, one tumour harboured V600E via local assessment, in contrast to NGS result; samples used for both procedures were from different origin.Considering the intention‐to‐analyse population of 187 cases, DNA‐seq did not show any alteration in 10 cases and no gene fusions were identified. The most frequent mutated genes were BRAF V600E prevailed in right‐sided CRC (7% versus 2.8% in left‐sided CRC). ESCAT II: ERBB2 amplification was identified only in RAS wild‐type patients (3.2%) and KRAS G12C prevailed in right‐sided CRC (7% versus 3.5% in left‐sided CRC). ESCAT III: ERBB2 mutation was only found in left‐sided CRC (2.1%). PIK3CA mutation, although much more frequent in RAS mutant population , could only be considered as druggable in RAS wild‐type population . FGFR1‐3 mutations were only found in right‐sided CRC (2.3% each gene), contrary to MET amplification (1.4%), that additionally was only observed in RAS wild‐type population. ESCAT IV: non‐V600E BRAF mutations prevailed in right‐sided CRC (4.6% versus 1.4% in left‐sided CRC), like RNF43 (4.6% versus 2.1%), and contrary to FBXW7 mutations . Regarding local RAS status, FBXW7 mutations prevailed in RAS mutant population (8.8% versus 1% in RAS wild‐type population). Genomic alterations in MSI‐H/dMMR patients were classified in ESCAT III and IV , and one of them was included in two trials consecutively (patient whose tumour harboured BRAF V600E and RNF43 mutation)   included in an NGS programme for therapeutic purposes. As expected, left‐sided CRC prevailed in more than 2/3 of cases, and about 50% of tumours were Considering NGS analysis, the results were not available in 10 out of 187 patients due to sample failure. This rate is lower than the 30% reported in other pan‐cancer studies , 13, parAPC, TP53, RAS and PIK3CA as the most prevalent events, as described in other series [RAS/BRAF status between NGS and local PCR occurred in 12 out of 187 patients, probably explained by molecular heterogeneity in two cases (samples assessed were different in each technique), and by technical assay sensitivity issues in the rest [ERBB2 amplification was observed in 1.6% of patients, and the remaining aberrations belong to ESCAT III and ESCAT IV categories with an individual prevalence below 5%, aligned with previous reports [Next‐generation sequencing results showed mutations in r series , 15, allr series . Of notethe rest . Regardi reports , 16. TheRAS/BRAF wild‐type [RAS mutant population, that accounted for almost 50% of the cohort, descriptive data in Table RAS mutant tumours in EGP could be argued, although updated research could change this assumption, like the preliminary data of trastuzumab deruxtecan activity in this subset of patients [RAS WT population treated with anti‐EGFR, molecular aberrations resulting from therapeutic pressure were not analysed [This work has some limitations. There was a bias in the selection of patients because only those with ECOG PS suitable for clinical trial inclusion were included. Therefore, the representation of less prevalent molecular profiles associating druggable aberrations in CRC, like right‐sided and ild‐type , is limipatients . Second,patients  could hapatients , and a rpatients . In RAS analysed , 25, sinanalysed , we coulanalysed . In addiIn conclusion, EGP programmes in mCRC are feasible in a reference centre and useful for identifying druggable alterations, although the inclusion rate in BGT is still very low. With the current implementation of EGP programmes in the daily practice, near‐future efforts must be focussed on: (a) reducing tissue and economical costs to guarantee equity; (b) improving the BGT portfolio to increase the therapeutic efficiency of NGS tests; (c) reshaping NGS panels periodically to cover emerging biomarkers according to basal CRC molecular profile; (d) redefining the decisive instant to perform NGS to capture the biological evolution of mCRC under therapeutic pressure; and (e) implementing liquid biopsy as an alternative to tissue when indicated.5PIK3CA mutations) and they mostly belong to ESCAT III and IV, although this classification could be variable over time. The rate of inclusion in BGT related with NGS programmes is under 3%, but it is highly dependent on clinical trials portfolio.Expanded genomic profiling programmes are feasible and unveil druggable alterations ESCAT I to IV in up to 30% of advanced CRC. However, the prevalence of druggable alterations for a given gene in mCRC is less than 5% : Agios Pharmaceuticals – Amgen – Bayer – Beigene USA – Blueprint Medicines – BMS – Cellestia Biotech – Debiopharm – F. Hoffmann La Roche Ltd – Forma Therapeutics – Genentech Inc – Genmab B.V. – GSK – Glycotope Gmbh – Incyte Biosciences – Incyte Corporation – ICO – Kura Oncology Inc – Lilly, S.A – Loxo Oncology Inc – Macrogenics Inc – Menarini Ricerche Spa – Merck, Sharp & Dohme de España, S.A – Nanobiotix, S.A – Novartis Farmacéutica, S.A – Pfizer, SLU – Pharma Mar, S.A.U – Pierre Fabre Medicament – Principia Biopharma Inc. – Psioxus Therapeutics Ltd – Sanofi – Sierra Oncology, Inc – Sotio A.S – Symphogen A/S. Josep Tabernero reports personal financial interest in form of scientific consultancy role for Array Biopharma, AstraZeneca, Bayer, Boehringer Ingelheim, Chugai, Daiichi Sankyo, F. Hoffmann‐La Roche Ltd, Genentech Inc, HalioDX SAS, Hutchison MediPharma International, Ikena Oncology, Inspirna Inc, IQVIA, Lilly, Menarini, Merck Serono, Merus, MSD, Mirati, Neophore, Novartis, Ona Therapeutics, Orion Biotechnology, Peptomyc, Pfizer, Pierre Fabre, Samsung Bioepis, Sanofi, Scandion Oncology, Scorpion Therapeutics, Seattle Genetics, Servier, Sotio Biotech, Taiho, Tessa Therapeutics and TheraMyc. Stocks: Oniria Therapeutics and also educational collaboration with Imedex/HMP, Medscape Education, MJH Life Sciences, PeerView Institute for Medical Education and Physicians Education Resource (PER). Núria Mulet Margalef receives travel and academic grants from Amgen, Merck and Roche. Ramon Salazar has served in a consultant or advisory role for Amgen, Merck, S.L., Madrid, Roche Dx and research funding for Roche Dx. Rodrigo Dienstmann has an advisory role at Roche and Boehringer‐ Ingelheim, has received a speaker’ s fee from Roche, Ipsen, Amgen, Sanofi, Servier, Libbs, Merck Sharp & Dohme and further received direct research funding from Merck and Pierre Fabre. José Carlos Ruffinelli has received travel grants from Merck and MSD and a speaker’ s fee from Amgen. The other authors have declared no conflicts of interest.CS, RS, RD and NMM have designed the work. NMM, CCa, MM, AR and CS have collected clinical data. XP, FR‐P and RD have performed statistical analysis and tables. MMV, CCu, JCR, FL, GS, AT, RC and RG have selected the patients for NGS programme. EG and EE have treated the patients in clinical trials. SA, AV, JT and RD have developed and supervised the NGS programme. All the authors have contributed to the manuscript design and they have approved the final version.https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/1878‐0261.13444.The peer review history for this article is available at Table S1. Amplicon‐based NGS assays.Table S2. Mutational genomic profile of MSI‐H/dMMR tumours.Click here for additional data file.


Zabelia tyaihyonii is a familiar shrub, called “Hardy abelia” and “Fragrant abelia” growing in the karst forests of Korea, where it is one of the most threatened species. We investigated the genetic structure and demographic history of Z. tyaihyonii, which allow us to develop appropriate conservation and management strategies. The genetic structure was evaluated using a total of 187 samples from 14 populations, covering the entire distribution of Z. tyaihyonii in South Korea. We utilized 254 and 1753 SNP loci obtained via MIG‐seq (Multiplexed ISSR Genotyping by sequencing) for structure and demographic analyses, respectively. The population demographic modeling was performed with site frequency spectrum. To gain further historical insights, we also employed ENM . We found two distinct clusters (CLI and CLII) of ancient origin (ca. 490 ka). Despite CLII experiencing a more severe bottleneck, both clusters showed similar levels of genetic diversity, indicating mutual historical gene flow. Their historical distribution range seems to have changed very little. We proposed a historical distribution scenario for Z. tyaihyonii, taking into account its intrinsic factors, and emphasized a more complex response to Quaternary climate change beyond simple allopatric speciation models. These findings provide valuable insights for conservation and management strategies for Z. tyaihyonii.Similar to the global phenomenon, many plant species endemic to Korean limestone karst forests are at risk of extinction due to human intervention.  Zabelia tyaihyonii is a familiar shrub, called “Hardy abelia” and “Fragrant abelia” growing in the karst forests of Korea, where it is one of the most threatened species. We explored the evolutionary history and demographic dynamics for populations of Z. tyaihyonii using genome‐wide SNP markers. Here, we provide effective strategies on how to optimally conserve the historical genetic determinants of Z. tyaihyonii, known to have adaptively evolved on calcareous soils. Hara is a temperate deciduous, broad‐leaved shrub in the family Caprifoliaceae that is endemic to the dry karst forests on the Korean Peninsula , excellent fragrance, and strong cold tolerance  Nakai: Chung et al., Saussurea chabyoungsanica Im: Jeong et al., Z. tyaihyonii have sampled a very narrow range, and lacked historical inferences  provides a powerful framework for investigating the interplay between ecological and evolutionary factors that have contributed to the genetic diversity of populations  to investigate their genetic diversity and structure, (2) to evaluate the evolutionary potential and conservation value to the populations from inferring the demographic history, and (3) to provide effective conservation guidelines for the recovery and management from a long‐term conservation genetics perspective.In this study, we aimed to explore the evolutionary history and demographic dynamics for populations of 22.1Z. tyaihyonii. Controversy exists over whether the taxa distributed in the Korean Peninsula should be treated as the genus Zabelia (Rehder) Makino or Abelia R. Br.  collected in South Korea and Abelia mosanensis [= Zabelia mosanensis (T. H. Chung ex Nakai) Hisauti & H. Hara] collected in North Korea  with hairs on the filaments. However, distinguishing these two taxa is inherently difficult because the reference specimens of Z. tyaihyonii were collected during the fruiting season  according to the manufacturer's instructions. The concentration of extracted DNA was determined using Nano‐300 micro spectrophotometer (Allsheng), and diluted to 15 ng/μL to obtain the same concentration of template DNA in each sample.We collected 187 leaf samples of 2.2To obtain genome‐wide single‐nucleotide polymorphism (SNP) data, we used the MIG‐seq method. Preparation of the MIG‐seq library was conducted under standard conditions, according to Suyama et al. , without2.3http://hannonlab.cshl.edu/fastx_toolkit/) so that the length of each read became 134 bp. The low‐quality reads were removed using the program quality_filter in the FASTX‐Toolkit, and extremely short sequence reads were then removed by TagDust 1.12 , observed heterozygosity (HO), expected heterozygosity (HE), and inbreeding coefficient (FIS). Nucleotide diversity (π) was calculated using the ‘populations’ command of Stacks. Allele richness (AR) and genetic differentiation among populations were determined according to the method of Weir and Cockerham  assumed ancient migration during from T1 to T2. Model 4 (secondary contact model) assumed recent migration during from current to T1. We also assumed different population size change in different three time periods, from current to T1, from T1 to T2 and before T2.In order to identify divergence times, patterns of migrations, and population size changes, a coalescent based maximum likelihood analysis estimating parameters of the population demographic model was performed with fastsimcoal2 version 2709 . Missing data was compensated by a bootstrapping within the cluster.To make the input data for fastisimcoal2, as we need information that how many SNPs were obtained from sequences of certain lengths, SNPs were re‐extracted using populations of stacks with options of ‐p 2 ‐r 0.80 ‐‐max‐obs‐het 0.60 ‐‐min‐maf 0.0. The re‐extracted data was constructed from 242,107 all sites, 4178 variant sites (SNPs) and 1753 loci (stacks). Two dimensional minor allele site frequency spectrum (2D‐mSFS) was calculated from the .vcf file with our own R script  Rehd., takes 10–20 years to reach its ultimate height  optimization cycles, and 100,000 coalescent simulations. Mutation rate was set to 5.39 × 102.6Z. tyaihyonii. We first developed a model of current distribution based on occurrence data, and then past distribution was estimated by projecting the model to paleo‐climatic data. We used only 14 occurrence data obtained from our investigations in the analysis because of the rareness of the species. We downloaded 19 bioclimatic variables from Climatologies at High resolution for the Earth's Land Surface Areas . After the quality control of the raw reads, 234,710,807 reads were retained for SNPs calling. Sample coverage for genotyping of Z. tyaihyonii was 32.36x. From the population program in Stacks with the parameter combination of ‐p 14 ‐‐max‐obs‐het 0.60 ‐‐min‐maf 0.03 and write‐single‐snp, a total of 3, 21, 47, and 254 SNPs (loci) were detected under r = 1.00, 0.90, 0.85, and 0.80, respectively. Genetic diversity was estimated from 254 SNPs.In total, we obtained 462,669,080 raw reads from the 187 samples of Z. tyaihyonii, are shown in Table Z. tyaihyonii populations showed relatively similar allelic richness, expected heterozygosity, and nucleotide diversity  across all populations except for KY_H1 and CJ_S6. At the population level, AR and HE ranged from 1.217 to 1.570 (mean 1.471) and 0.086 to 0.198 (mean 0.167), respectively. π ranged from 0.093 to 0.202 (mean 0.175). At the pooled cluster level, the levels of genetic diversity were almost equivalent between cluster I  and cluster II . Also, each of the two clusters harbored private alleles .Genetic diversity parameters, evaluated at the population and pooled cluster levels for all 187 individuals of Z. tyaihyonii, we performed STRUCTURE, PCoA, and Neighbor‐Net phylogeny analysis with 254 SNPs from MIG‐seq. The results clearly demonstrated that the two clusters are genetically distinct. The genetic structure strongly supported K = 2 as the optimal number of clusters for the datasets, based on ΔK statistics in the STRUCTURE analysis  and cluster II . The results of the PCoA for individuals were not clearly separated, but were divided into two clusters based on similarity indices  between genetic differentiation and geographic distances  was significantly larger than that of CLII  because NCLI_0/NCLI_1 and NCLII_0/NCLII_1 were significantly smaller than 1.0. CLI also showed significant increase in population size at its divergence. Divergence time between the two clusters (T2) was 490 ka (95% CI: 292–671 ka). Strengths of migrations between clusters denoted by the number of migrants per generations (Nm) were significantly larger than 1.0 in both direction, and there was no statistically significant difference between directions, as their 95% CIs overlapped.Isolation with the migration model model 2) was selected as the best model . The variable showing the highest percent contribution is glim  and second one is bio04 . The current predicted distribution shows that it is significantly associated with the limestone area in Korean Peninsula , and we were able to identify the historical and intrinsic factors that shaped their genetic composition. Despite CLII having a more severe bottleneck, both the clusters had similar levels of genetic diversity. This can be attributed to bidirectional historical gene flow that contributed to the genetic diversity of both groups without compromising their genetic uniqueness. We propose a historical distribution scenario for Z. tyaihyonii that considers its intrinsic factors, and highlights a more complex scenario that takes into account its response to Quaternary climatic fluctuations, beyond simple allopatric speciation models.We used the MIG‐seq technique to study the genetic diversity of 4.1Z. tyaihyonii populations are structured in two genetically different clusters, as shown in the STRUCTURE, Neighbor‐Net phylogeny, and PCoA analyses with a significant IBD pattern. However, genetic variation in the CJ_S6 population appears to be inconsistent with the geographical proximity of the two clusters in the limestone zones. This population is isolated from other populations by a physical barrier of non‐calcareous substrata. Despite this, the CJ_S6 population does not show unique genetic characteristics and instead forms a clade with geographically more distant populations within CLI, indicating genetic homogeneity. Because a previous study conducted by Kang et al.  can withstand minimum temperatures from −28.9 to −23.3°C, thus it is considered cold hardy , our idea regarding their persistent distribution is considered reasonable. It is, therefore, conceivable that the extant populations are descended from ancestor populations  that had lived in the same (much not different) place as those of the present.We noted that ENM simulated in bedrock conditions revealed that the potential distribution converges to zero across the Korean Peninsula, as if 4.2We detected signs of a recent bottleneck in both CLI and CLII, which can be inferred from the change in the effective population size Table . HoweverZ. tyaihyonii . Due to their flowering time (May), strong floral scent, and floral structure, these shrubs are considered to be active in cross‐fertilization, but often give rise to generations through vegetative reproduction  Blume: Zhu et al., Z. tyaihyonii could mitigate the negative effects of locally occurring or varying strength bottlenecks. This would have allowed for the maintenance of similar genetic diversity throughout the species' distribution range.The one of most plausible factors can be found in symmetric and persistent historical gene flow, as shown in our demographic analysis Figure . Althoug4.3Z. tyaihyonii populations in South Korea should be developed to maintain the unique genetic identity of each cluster. Additionally, since it is uncertain whether other Z. tyaihyonii populations exist in North Korea, it is important to consider that the few remaining populations in South Korea may represent the entire distribution range of this species. This fact should be a fundamental consideration when contemplating industrial development in specific habitats of this species. The possibility of the species existing in North Korea could potentially make it more vulnerable to extinction of this shrub by providing a more favorable perspective towards development.Based on full range of analyses, we recommend that conservation strategies for Z. tyaihyonii may be a strategic outcome that has contributed to their long‐term survival, potentially due to their flexible outcrossing and vegetative reproductive systems. Moreover, our analysis suggests that the uniform genetic diversity across the entire populations may be a result of historical environmental changes, rather than recent human‐induced destruction ; data curation (lead); methodology ; writing – original draft (lead); writing – review and editing . Eun‐Kyeong Han: Formal analysis ; methodology ; software ; visualization (lead). Martin Wojciechowski: Writing – review and editing . Tae‐Im Heo: Conceptualization ; investigation ; project administration ; resources . Jong‐Soo Park: Methodology ; software ; visualization (supporting). Jong‐Cheol Yang: Investigation ; project administration ; resources . Amarsanaa Gantsetseg: Data curation (supporting); formal analysis ; visualization (supporting). Kyeong‐Sik Cheon: Writing – review and editing . Ichiro Tamaki: Methodology (lead); software ; visualization (supporting); writing – review and editing . Jung‐Hyun Lee: Conceptualization ; supervision (lead); visualization (supporting); writing – original draft (supporting); writing – review and editing .This research was funded by a research grant from the Baekdudaegan National Arboretum (KIAM‐2021‐KS‐OB‐02‐01‐02).The authors declare no conflict of interest.Figures S1–S2Click here for additional data file.


To determine the pathogenesis and molecular targets of anaphylaxis caused by hydatid cyst fluid leakage.Echinococcus granulosus, and then the anaphylaxis model was developed. The mice were separated into: anaphylaxis caused by the cystic echinococcosis group (ANPC), the cystic echinococcosis without anaphylaxis group (CE group), and the normal control group (CTRL). Following this, the spleen tissue was collected for microRNA (miRNA) sequencing. Using bioinformatics analysis, differentially expressed miRNAs (DEMs) were identified. Then, through the use of protein–protein interaction (PPI) networks, the key target genes for miRNA regulation associated with echinococcosis‐induced anaphylaxis were identified.First, Balb/c mice were infected with ANPC and CE groups have 29 and 39 DEMs compared to the CTRL group, respectively. Based on these 25 DEMs, interactions between miRNA and mRNA were screened, and 174 potential target genes were identified. We performed gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis on these 174 target genes, and the results revealed that the three pathways with the highest enrichment were the PI3K‐Akt signaling pathway, FoxO signaling pathway, and Focal adhesion. The interaction analysis of PPI and miRNA‐hub gene networks revealed that interleukin 6 (IL‐6) was regulated by miR‐146a‐5p and miR‐149‐5p, while IL‐10 was regulated by miR‐29b‐3p and miR‐29c‐3. Using reverse transcription polymerase chain reaction, we found that the miRNAs regulating IL‐6 and IL‐10 were significantly upregulated in the ANPC group, and there are three pathways involved in that process: Pathways of PI3K‐Akt signaling, FoxO signaling, and Focal adhesion. IL‐6 and IL‐10 play an important role in cellular pyroptosis and apoptosis. Therefore, the aforementioned results provide significant reference value for elucidating the mechanism of cellular pyroptosis and apoptosis in echinococcosis‐induced anaphylaxis, and for formulating tissue and organ protection strategies for patients with cystic echinococcosis when anaphylaxis is triggered by hydatid cyst rupture. Many provinces in China are affected by cystic echinococcosis, with Xinjiang, Inner Mongolia, Sichuan, Gansu, Ningxia, and Tibet having the highest prevalence of patients with cystic echinococcosis. The disease has impeded the growth of the local economy and animal husbandry.Echinococcosis, a severe zoonotic disease caused by In preliminary clinical practice, it has been determined that anaphylaxis resulting from surgery, trauma, and spontaneous cyst rupture are severe complications of the disease. This aggressive complication may result in severe consequences or even death if treated improperly.22.12.1.1A total of 18 female BALB/c mice, aged 4–8 weeks and weighing (20 ± 2) g, were purchased from the Laboratory Animal Center of the First Affiliated Hospital of Xinjiang Medical University.2.1.2The liver of sheep containing cysts was collected from the slaughterhouse in Urumqi, Xinjiang. After cleaning and drying the liver, the cyst fluid containing protoscoleces was collected and naturally precipitated. The supernatant was obtained, and the endotoxin was removed. The lipopolysaccharide (LPS) concentration was below 1.2 endotoxin units/mg. Using the BCA protein kit, the protein level was determined to be greater than 2815.2 µg/mL. The sample was kept in a refrigerator at −80°C. The sample was taken out 24 h before anaphylaxis and stored at 4°C.2.1.32 and a constant temperature of 37°C.The cystic fluid was digested with 1% pepsin. The cyst fluid was aspirated slowly after protoscoleces naturally settled to the bottom. Protoscoleces were inoculated at a culture density of 2000/mL in RPMI 1640 medium and incubated at 37°C for 40 days in an incubator with 5% CO2.22.2.1There were six mice in the cystic echinococcosis without anaphylaxis (CE) group , six in the anaphylaxis caused by cystic echinococcosis (ANPC) group , and six in the normal control (CTRL) group .2.2.2E. granulosus infection model of BALB/c mice. An equal amount of normal saline was injected in the CTRL group. Six months after infection, crude cystic fluid of sheep‐derived E. granulosus was injected intraperitoneally at a dosage of 0.1 mL/10 g mouse body weight to induce anaphylaxis. An equal amount of normal saline was injected in the CTRL group. After anaphylaxis, the mice were scored based on a symptom score table (refer to the classic reaction symptom table of equine serum‐induced mice anaphylactic shock), and their anus temperature was measured every 5 min. After 1 h of anaphylaxis, the epicanthal venous blood was extracted, and the spleen was collected to prepare single‐cell suspension.The microcapsules were inoculated via intraperitoneal injection to infect BALB/c mice (50/mouse) to establish the Refer to the classic reaction symptom tables of equine serum‐induced anaphylactic shock in mice.2.3Three mice were collected from the CTRL, CE, and ANPC groups, respectively. The spleen tissue was quick‐frozen with liquid nitrogen and then stored at −80°C. The sequencing was performed using the Illumina HiSeq. 2000 platform. RAW reading began with data cleansing, which included the removal of adapters, inferior tags, and several contaminants from 50 NT tags. The label length distribution was then summarized. The RNA‐seq data set was visualized using the Integrative Genome Observer.2.4E. granulosus by summarizing the pathway enrichment analysis network with quantitative reverse transcription polymerase chain reaction (qRT‐PCR) and verified the previous research results. GAPDH was used as an internal control, and the cycle threshold (Ct) value was normalized to determine the gene expression level. The 2‐ΔΔCt method was used to calculate the expression of relevant genes, with three replicates per group to ensure quantification accuracy.We analyzed the relative expression of key mRNAs in mice infected with 2.52.5.1p < .05 was chosen as the threshold for identifying DEMs. Overlapping miRNAs in both datasets were screened using Venn analysis and the VennR package.The edgeR package in R software was used to examine the relationships between the differential miRNA expressions of the ANPC and CE groups, and the CTRL group. 2.5.2RAVID v2.0 is an experimentally validated database of miRNA target interactions used to predict potential DEM target genes. The miRNACancerMAP database was adopted for miRNA pathway analysis.2.5.3https://david.ncifcrf.gov/) of the predicted target genes of 25 DEMs. Values of p < .05 were considered significant.Using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, the data were processed with the DAVID online tool to perform a functional and pathway analysis  was used to analyze the highly connected (hub) genes in protein–protein interaction (PPI) networks. After identifying the hub‐dem and hub‐target genes, the cell landscape was used to visualize the obtained miRNA gene network.2.5.5X ± SD), and a one‐way analysis of variance was used for between‐group comparisons. The significance level is α = .05.GraphPad Prism 7.0 software was used for plotting and statistical analysis. The measurement data are expressed as the mean ± standard deviation ” Figure , “collag3.3A PPI network was constructed to identify the hub gene among the targets of the 25 DEMs. The predicted hub genes for the 25 identified miRNAs are IL‐6, Pten, Ccnd1, Jun, Mtor, Sirt1, IL‐10, Notch1, Fgf2, and Cdkn1a Figure . We also3.4p < .01). The IL‐10 levels in the CTRL, CE, and ANPC groups were 1.89 ± 0.23, 2.28 ± 0.33, and 3.95 ± 0.35, respectively. As compared with the CTRL group, the IL‐10 level was significantly elevated in both the CE and ANPC groups  can increase the expression of three miRNAs , which are associated with inflammation, oxidative stress, and epigenetics. In addition, studies have also demonstrated that exposure of airway epithelial cells and alveolar macrophages to PM significantly upregulates miR‐29b‐3p, which promotes the occurrence and development of inflammation. Additionally, miR‐29b‐3p can directly target C1QTNF6, thereby inhibiting the activation of the anti‐inflammatory AMPK signaling pathway. These results suggest that miR‐29b‐3p and miR‐29c‐3p regulate the inflammatory response.E. granulosus infection and subsequent anaphylaxis remain unknown.However, their biological functions and mechanisms in Echinococcus capsulatus cyst fluid is a systemic validated reaction whose target organs are usually the lungs, liver, and other organs.Echinococcus capsulatus cyst fluid, and some studies have shown that both encapsulation can cause splenic injury in buffaloes and patients,Echinococcus capsulatus cyst fluid are still rare, so we would like to investigate what kind of differential miRNAs are expressed in the spleen to participate in the occurrence of systemic inflammatory response, and whether such differential miRNAs are involved in some mechanisms of organ damage related to inflammatory response.Usually, the allergic reaction caused by + T cell activity, and promote an inflammatory response in IL‐10‐positive CD4+ cells, in addition to its expected anti‐inflammatory properties in autoimmune diseases.The PPI network interaction diagram revealed that IL‐6 was regulated by miR‐146a‐5p and miR‐149‐5p, while IL‐10 was regulated by miR‐29b‐3p and miR‐29c‐3p. Additionally, RT‐PCR verification revealed that the expressions of IL‐6 and IL‐10 were significantly upregulated in the spleen tissues of the ANPC group. IL‐6 is a cytokine secreted by Th2 cells that can enhance the role of IL‐4 in promoting IgE synthesis and participate in the immune response and immune regulation of the body.The majority of the 174 target genes regulated by differential miRNAs were enriched in three pathways, that is, the PI3K‐Akt signaling pathway, the FoxO signaling pathway, and the Focal adhesion signaling pathway, based on the KEGG signaling pathway results. miR‐16‐5p regulates 5 target genes  among the 10 hub genes targeted by miRNAs. These five target genes are also associated with the PI3K‐Akt signaling pathway. In patients with cystic echinococcosis, the levels of TLR2 and TLR4 in blood are significantly increased.5In this study, miRNA sequencing analysis revealed that miR‐146a‐5p, miR‐29b‐3p, miR‐29c‐3p, miR‐149‐5p, and miR‐16‐5p play a crucial role in hydatid cyst fluid‐induced anaphylaxis. In response to anaphylaxis, these miRNAs regulate the expression of the cytokines IL‐6 and IL‐10 and participate in signaling pathways such as PI3K‐Akt. These 5 miRNAs‐miR‐146a‐5p, miR‐29b‐3p, miR‐29c‐3p, miR‐149‐5p, and miR‐16‐5p can therefore be considered as regulatory genes for hydatid cyst fluid‐induced anaphylaxis. Thus, it provides a significant reference value for elucidating the mechanisms underlying cellular pyroptosis and apoptosis in echinococcosis‐induced anaphylaxis, as well as in formulating tissue and organ protection strategies for patients with cystic echinococcosis when anaphylaxis is triggered by hydatid cyst rupture.Chun‐sheng Wang: Conceptualization; data curation; project administration; software; supervision; writing—original draft. Tao Yu: Data curation; formal analysis; investigation; validation; visualization; writing—original draft. Xilizhati Kulaixi: Data curation; formal analysis; methodology; validation; visualization; writing—review and editing. Jing‐ru Zhou: Investigation; methodology; project administration; software; validation. Xianyidan Abulajiang: Data curation; supervision; validation; visualization; writing—review and editing. Jia‐ling Wang: Data curation; formal analysis; methodology; project administration; validation; writing—review and editing. Si‐jia Wang: Data curation; formal analysis; supervision; validation; visualization; writing—review and editing. Jian‐rong Ye: Funding acquisition; project administration; writing—review and editing.The authors declare no conflict of interest.


In older patients with acute myeloid leukemia (AML), the definition of fitness, prognosis, and risk of death represents an open question.In the present study, we tested the impact on survival of disease‐ and patient‐related parameters in a large cohort of elderly AML patients homogeneously assigned to treatment with hypomethylating agents (HMAs).p = 0.003) can select patients with better‐predicted survival. However, a full disease‐oriented model had limitations in stratifying our patients, prompting us to investigate the impact of baseline comorbidities on overall survival basing on a comorbidity score. The albumin level (p = 0.001) and the presence of lung disease (p = 0.013) had a single‐variable impact on prognosis. The baseline comorbidity burden was a powerful predictor of patients' frailty, correlating with increased incidence of adverse events, especially infections, and predicted overall survival (p < 0.001).In 131 patients with a median age of 76 years, we confirmed that early response (<0.001) and biology‐based risk classification (The comorbidity burden may contribute to impact prognosis in addition to disease biology. While the therapeutic armamentarium of elderly AML is improving, a comprehensive approach that combines AML biology with tailored interventions to patients' frailty is likely to fully exploit the anti‐leukemia potential of novel drugs. In this study, we tested the impact on survival of disease‐ and patient‐related parameters in a large cohort of elderly AML patients assigned to treatment with HMAs. Serágnoli—Policlinico S. Orsola‐Malpighi in Bologna, at Division of Hematology in University Hospital‐ASUFC in Udine, and Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori”—IRST in Meldola from 1st Dec 2010 to 1st Jun 2021. Informed consent was obtained from every patient at the time of diagnosis in accordance with GCP and as approved by the local ethical review board. Within the entire patient population, we report data on elderly patients who received front‐line, single‐agent HMAs. Major criteria for enrolment were old age (>65 years old), AML defined according to WHO 2016 criteria excluding acute promyelocytic leukemia,2.2For every patient, we collected data on the onset of the disease, including age, history of the antecedent hematologic disorder, history of antecedent diseases, baseline comorbidities, clinical and laboratory features, and cytogenetic and molecular characteristics. Survival, disease status, therapies for AML, and adverse events (AE) were collected for the entire duration of follow‐up. For analysis purposes, we considered AEs, severe AEs, infections, and severe infections as AE categories.2.3AML was diagnosed and categorized according to WHO2008 or WHO2016 criteria and classified in the study database according to WHO2016 criteria.2.4Review of cytogenetic status included karyotype based on a minimum of 20 metaphase cells. Molecular analyses were performed on DNA or RNA of mononuclear cells by polymerase chain reaction, or Sanger sequencing, or capillary electrophoresis, as appropriate. The cytogenetic and molecular risk was stratified according to ELN 2010 Prognostic System.2.5Comorbidities were defined as previously reported by Mukherjee and colleagues2.6Azacytidine was administered subcutaneously at the dose of 75 mg/sqm on days 1–5, 8–9, or 1–7 of consecutive 28‐day courses. Decitabine was administered intravenously at the dose of 20 mg/sqm on days 1–5 of consecutive 28‐day courses. Courses delays and dose reductions were managed according to standard clinical practice to allow recovery from hematology toxicities in patients who are in complete remission or to consent to lower the grade of ongoing adverse events. Dose delays of more than 2 weeks not due to adverse events were registered as treatment interruption.2.7p‐values statistical significance. All confidence intervals (CI) were reported as 95% CI.Statistical analyses were performed on the entire sample population, if not differently specified. Data collected have been summarized by descriptive statistics such as mean and standard deviation or median with its interquartile range (IQR) for continuously distributed variables, otherwise, rates and relative frequencies have been reported for categorical distributions. Fisher exact test or Chi‐squared test have been adopted to evaluate associations between groups and nominal variables were appropriate. The Mann–Whitney test has been applied, alternatively, to assess differences between medians in non‐normal distributions. Survival analysis has been performed by means of the Kaplan–Meier estimator and its algorithm for survival curve generation. Subgroup analyses were conducted whenever appropriate. Log‐rank test was used to compare survivals curves probabilities, while semiparametric Cox regression analysis has been adopted to estimate Hazard Ratios (HR). All the analyses were conducted using R language and environment for statistical computing . 0.05 was taken as the cut‐off for two‐sided 33.1In total, 131 elderly patients received 1st line HMAs at the participating institutions. Baseline characteristics are reported in Table As expected, most of the patients had at least one comorbidity Table . Particu3.2With a median follow‐up of 28.2 months  or age (more or less than 70 years old) had no significant impact on survival.p < 0.001). Improved survival was confirmed also for patients who were in response at 4 or 6 months  and high ELN2010 risk (p = 0.003) were associated with a low probability of response.At month 2, 59 out of 119 patients reached response (49%), including 10 patients with CR, 1 patient with CRi, and 48 patients with partial response. As expected, early response to HMA therapy was highly predictive of better survival . We, then, analyzed the prognostic impact of comorbidities. For each baseline comorbidity, we tested the impact on overall survival. Interestingly, lung disease  and hypoalbuminemia  conferred significantly diminished OS. Taken together, these data may indicate that for better stratification of elderly patients treated with HMAs, disease‐related factors, as captured by ELN risk classification, would be more successfully integrated with the impact of baseline comorbidities.Given the great heterogeneity of outcomes in our cohort of patients, we sought to investigate the differential impact on the prognosis of disease‐ and patient‐specific factors. To this aim, molecular and cytogenetic parameters, captured and integrated into ELN2010 risk classification, as well as well‐established comorbidities were specifically correlated with OS. According to ELN2010 risk classification, patients belonging to the int‐1 risk category had the best OS (23.4 months), whereas those in the high‐risk category showed very short OS (6.5 months). Of note, “intermediate‐2” risk patients had a similar, statistically non‐different outcome as high‐risk patients, suggesting that disease‐specific biologic factors, captured by ELN2010 risk classification, might not be fully competent in stratifying our group of patients Figure . In part3.4n = 78) whereas patients with medium , high , or very high  comorbidity burden had a median OS of 13.2 (95% C.I. 7.4–23.3), 6.6 (95% C.I. 3.9‐NR), and 3.3 (95% C.I. 3.3–NR) months, respectively .The sample size in this study was not sufficient to constitute a new prognostic model. Then, for further analyses, the impact on survival of comorbidities alone and combined with disease‐related factors were assessed by using augmented‐CI (A‐CI) and AML‐CM scores, respectively.n = 24), 18.3 months (95% C.I. 14.2–26.1) in patients with intermediate AML‐CM , 11.1 months (95% C.I. 8.0–21) in patients with high AML‐CM score  and 6.4 months in patients with very high AML‐CM score , as shown in Figure p for trend<0.001). Of note, cerebrovascular disease, obesity, lung disease, prior tumor, and hypoalbuminemia were more frequent in patients with AML‐CM score >9  in patients with low AML‐CM score . Incidence of non‐hematologic AEs progressively increased along with AML‐CM risk groups. In particular, 84.55, 116.01, 131.45, and 229.3 events for 100 patients per year were observed in patients with AML‐CM scores 1–4, 5–6, 7–9, and >9, respectively. While considering the etiology of AEs, infections were the most represented non‐hematologic adverse events. Of note, infectious episodes were 53.80, 55.10, 85.95, and 140.13 for 100 patients per year for patients with AML‐CM scores 1‐4, 5–6, 7–9, and >9, respectively. Taken together, these data suggest that a higher AML‐CM score due to baseline comorbidities augments the risk to have an adverse event, especially of infective etiology. The impaired prognosis that we observed in AML‐CM higher risk groups may be explained by a higher incidence of infections and their life‐threatening consequences.4To discern how patient‐ and AML‐related factors impact prognosis, we analyzed data from a large typical set of patients who have been assigned to HMAs by physician's choice. Herein, we collected therapy response and applied ELN2010 to describe the prognostic weight of disease‐related factors, and we applied a predefined comorbidity index  to describe patient‐related factors. In this setting, AML‐specific factors alone, as defined by the ELN2010 classification, provided a partial stratification of prognosis, thus indicating that a more comprehensive approach, which takes into consideration both disease‐related biological factors and patient characteristics, may be helpful.As expected, our set was enriched for secondary diseases and high‐risk karyotype, while core‐binding factor, FLT3 and NPM1 mutated AML were occasional.To evaluate the role of patient‐derived factors as determinants of global clinical outcomes, we focused on baseline comorbidities. We investigated multi‐morbidity taking advantage of the well‐validated augmented‐CI scoreOur study has some limitations. It focuses on a cohort of patients receiving only HMAs, thus excluding the relevant impact of new and effective molecules, such as venetoclax and/or target therapies. In our cohort, the overall survival estimate overcomes results previously reported in phase 3 clinical trials of HMAs,In conclusion, the comorbidity burden was a powerful prognostic factor, capable to impact patients' stratification and to integrate a biology‐oriented model. The results of our study further support the notion that baseline multi‐morbidity is tightly related to patient frailty, underlying on‐therapy morbidity, especially of infectious etiology, and contributing to survival. In a scenario where new therapies, such as venetoclax and targeted drugs, have dramatically improved the prognosis of older AML patients, tailored interventions able to impact frailty are warranted. In that, the integration of quantitative assessment of comorbidity burden within a novel prognostic and risk‐classification algorithm, oriented to unfit‐for‐chemotherapy patients, may represent a fundamental step toward a comprehensive approach to elderly AML.Giovanni Marconi: Conceptualization ; investigation ; methodology ; resources ; writing – original draft (lead); writing – review and editing . Anna Candoni: Conceptualization ; data curation ; investigation ; resources ; writing – original draft ; writing – review and editing . Roberta Di Nicola: Investigation ; resources ; writing – original draft ; writing – review and editing . Chiara Sartor: Resources ; writing – original draft ; writing – review and editing . Sarah Parisi: Resources ; writing – original draft ; writing – review and editing . Mariachiara Abbenante: Resources ; writing – original draft ; writing – review and editing . Jacopo Nanni: Resources ; writing – original draft ; writing – review and editing . Gianluca Cristiano: Resources ; writing – original draft ; writing – review and editing . Letizia Zannoni: Resources ; writing – original draft ; writing – review and editing . Davide Lazzarotto: Resources ; writing – original draft ; writing – review and editing . Benedetta Giannini: Resources ; writing – original draft ; writing – review and editing . Carmen Baldazzi: Resources ; writing – original draft ; writing – review and editing . Lorenza Bandini: Resources ; writing – original draft ; writing – review and editing . Emanuela Ottaviani: Resources ; writing – original draft ; writing – review and editing . Nicoletta Testoni: Resources ; writing – original draft ; writing – review and editing . Chiara Di Giovanni Bezzi: Resources ; writing – original draft ; writing – review and editing . Rania Abd‐alatif: Resources ; writing – original draft ; writing – review and editing . Giulia Ciotti: Resources ; writing – original draft (supporting); writing – review and editing . Renato Fanin: Resources ; supervision ; writing – original draft ; writing – review and editing . Giovanni Martinelli: Resources ; writing – original draft ; writing – review and editing . Stefania Paolini: Resources ; writing – original draft ; writing – review and editing . Paolo Ricci: Resources ; writing – review and editing . Michele Cavo: Investigation (supporting); project administration (supporting); resources ; supervision ; writing – original draft ; writing – review and editing . Cristina Papayannidis: Conceptualization ; data curation ; investigation ; methodology ; project administration (lead); resources ; supervision ; writing – original draft ; writing – review and editing (lead). Antonio Curti: Conceptualization ; data curation ; investigation ; project administration (lead); resources ; supervision ; writing – original draft ; writing – review and editing .Dr. Giovanni Marconi received honoraria as consultant/speaker bureau from Menarini/Stemline, Pfizer, Servier, and Astellas; he received research support from Pfizer, AbbVie, and AstraZeneca. Dr. Anna Candoni received honoraria from Pfizer, Amgen, AbbVie, Janssen, Astellas, Celgene. Prof. Giovanni Martinelli acted as a consultant for Ariad/Incite, Jansen, Pfizer, Celgene, Amgen, J&J, and Roche. Prof. Michele Cavo acted as a consultant for and received honoraria from AbbVie, Glaxo Smith Kline, Bristol‐Myers Squib, Adaptive Biotechnologies, Takeda, Janssen, Celgene, Amgen. Moreover, Prof. Cavo is in the speaker's bureau of AbbVie. Dr. Cristina Papayannidis received honoraria from Pfizer, Amgen, Novartis. Dr. Antonio Curti received honoraria from Novartis, Pfizer, Abbvie and acted as a speaker in Advisory Board for Novartis and Abbvie. and Glaxo Smith Kline. The other authors declare no conflict of interest or activities that could appear to have influenced this manuscript.Data S1:Click here for additional data file.


Massive hepatocellular carcinoma  tends to have a poor prognosis. Therefore, this study aims to construct and validate prognostic nomograms for MHCC.Clinic data of 1292 MHCC patients between 2010 and 2015 were got from the surveillance, epidemiology, and end results (SEER) cancer registration database. The whole set was separated into the training and validation sets at a ratio of 2:1 randomly. Variables, significantly associated with cancer‐specific (CSS) and overall survival (OS) of MHCC were figured out by multivariate Cox regression analysis and were taken to develop nomograms. The concordance index (C‐index), calibration curve, and decision curve analysis (DCA) were taken to validate the predictive abilities and accuracy of the nomograms.Race, alpha‐fetoprotein (AFP), grade, combined summary stage, and surgery were identified as independent factors of CSS, and fibrosis score, AFP, grade, combined summary stage, and surgery significantly correlated with OS in the training cohort. They then were taken to construct prognostic nomograms. The constructed model for predicting CSS exhibited satisfactory performance with a C‐index of 0.727 (95% CI: 0.746–0.708) in the training group and 0. 672 (95% CI: 0.703–0.641) in the validation group. Besides, the model for predicting OS of MHCC also showed strong performance both in the training group  and the validation  group. All calibration curves and decision curves performed satisfactory predictive accuracy and clinic application values of the nomograms.The web‐based nomograms for CSS and OS of MHCC were developed and validated in this study, which prospectively could be tested and may serve as additional tools to assess patient's individualized prognosis and make precise therapeutic selection to improve the poor outcome of MHCC. We think the constructed predictive models will effectively and conveniently help clinicians provide MHCC patients with appropriately personalized interventions.22.1The medical data of a total of 104,173 HCC cases between 2010 and 2015 were extracted from the SEER plus database [18 registries (2000–2018)]. The inclusion criteria in this study were as follows: (I) adult patients (age ≥18 years old); (II) positive cytology or histology evidence of HCC (ICD‐O‐38170/3 to 8175/3); (III) tumor size ≥10 cm; (IV) survival time ≥1 month. Cases having inadequate clinic data were excluded. Limited by lagging in data updates of the SEER database, we excluded the patients from before 2010 and from 2015 onwards to reduce calculative bias caused by vast missing data of some variables.2.2Medical data comprised baseline demographics , tumor‐related characteristics , therapeutic strategies , survival condition . Notably, as for histological grade of differentiation, grade I/II refers to a well or a moderately differentiated tumor while grade III/IV means a poorly differentiated or an undifferentiated tumor.2.3www.R‐project.org), and MedCalc 19.0 were used for all statistical analyses. The whole set was then divided into the training and validation cohorts at a ratio of 2:1 randomly. Continuous variables are summarized as “mean ± SD” and their differences between groups were compared by the Mann–Whitney U test. Discontinuous variables are expressed as numbers and percentages. The chi‐square test or Fisher's exact test were utilized to explore differences in discontinuous variables between groups. The significantly independent factors of CSS and OS, identified by conducting Cox multi‐factor analyses, were utilized to construct prognostic nomograms. The concordance index (C‐index), calibration curve, and decision curve analysis (DCA) were used to validate the predictive abilities and accuracy; and then, the validation cohort was used to further evaluate the reliability and accuracy of the constructed nomograms. To elaborate on the prognostic differences between subgroups, Kaplan–Meier survival curve analysis and log‐rank test were performed. At last, two web applications based on the constructed nomograms for CSS and OS of MHCC were developed and deployed. A p < 0.05 in a two‐tailed test was deemed to have statistical significance.The medical data of all cases were extracted by the SEER *Stat 8.3.9 software. IBM SPSS Statistics 25.0, R 4.1.3 , White (64%), and married (59.2%). Notably, 71.9% of the patients presented a positive or elevated status of AFP before treatment, the average tumor size was 14.7 cm, and 30.8% of the tumors were grade III/IV. Approximately one‐third of the patients underwent surgery, while 176 (13.6%) patients accepted radiotherapy and 620 (48.0%) patients received chemotherapy. No statistical difference was found between the training and validation cohorts, and their baseline clinical information was exhibited in Table 3.2The median survival time of the total set was 8 months (ranges from 1 to 107 months). The 1‐, 3‐, and 5‐year CSS rate of the whole set were 42.9%, 23%, and 17.6% while the 1‐, 3‐, and 5‐year OS rate were 39.5%, 19.8%, and 13.8%, respectively. According to the results of the multivariate analyses in the training cohort, AFP, grade, combined summary stage, and surgery were identified as independent factors of both CSS and OS for MHCC. Besides, race was one of the risk factors for CSS, and fibrosis score was a significant statistical indicator for OS. Detailed information was shown in Tables 3.3https://sunyatsenmemorialhosipital.shinyapps.io/CSS_MHCC/) Figure A nomogram predicting CSS for MHCC was developed and then deployed the model into an open‐access online calculator based on the outcomes of the multivariate analysis (p < 0.001)  Figure .3.4https://sunyatsenmemorialhosipital.shinyapps.io/OSMHCC/)  in the training group and 0.667 (95% CI: 0.696–0.638) in the validation group. Besides, the calibration curves for the probability of 1‐, 3‐, and 5‐year OS were also highly consistent with the actual observation Figure . Moreovep < 0.001)  Figure  and the 3.5p < 0.001). In addition, the OS rate at 5 year in the surgery set was better than that in the no‐surgery set  . And the median OS values were 62 and 7 months in the surgery and no‐surgery groups, respectively (p < 0.001). While in the advanced stage (TNM stage III/IV) cohort, the median CSS and OS values in the surgery group were 22 and 16 months, respectively. But the median CSS value in the no‐surgery group was 5 months, and the median OS value was 5 months  cohort, the median CSS values in the surgery group and the no surgery group were 73 and 9 months, respectively .p < 0.001). Even patients at advanced‐stage can improve their prognosis by getting surgery . Those results reflect that the patients can gain better prognosis by accepting surgery, if eligible. But limited by the data provided by the SEER database selected, we did not further discuss the specific influences of different surgery methods on the prognosis of MHCC. What's more, we deeply analyzed the influences of chemotherapy and radiotherapy on the prognosis of MHCC by Cox regression analysis. Surprisingly, the results showed that those treatment methods did not significantly impact the long‐term outcomes for MHCC patients.Nowadays, several therapeutic choices can be selected for HCC, including surgery, radiofrequency ablation, anhydrous alcohol injection, and transhepatic artery chemotherapy and embolization (TACE), etc.However, surgery for MHCC often means extensive liver resection which may lead to insufficient residual liver volume, increase the risk of postoperative complications, and even death. Some studies reported the morbidity and mortality rates of MHCC after major resection ranging from 10.9% to 43.6% and 4.2% to 18.1%, respectively.Other variables in our models include histological grade, preoperative serum AFP status, etc. Numerous studies showed that they all were associated with the prognosis of HCC.Several limitations exist in this study. First, even if the data utilized in this study were extracted from the public database that provided a sea of cross‐race HCC cases, the developed nomograms still need further external validation to test their predictive accuracy and performance. Second, limited by the specific variables provided by the SEER database, we did not discuss the associations between specific clinical variables such as etiology, liver function status, vascular invasion, and prognoses of MHCC. Besides, numerous staging systems have been developed and widely employed to evaluate long‐term outcome for HCC including the Barcelona Clinic Liver Cancer (BCLC) system and Cancer of the Liver Italian Program (CLIP).5In summary, we constructed two web‐based predictive nomograms for clinical surgeons to precisely evaluate the prognosis of MHCC. Both of the models exhibited satisfactory predictive abilities and clinical application values.Guizhong Huang: Conceptualization ; data curation ; formal analysis (lead); investigation (lead); methodology ; project administration ; software ; validation ; visualization (lead); writing – original draft (lead); writing – review and editing . Qiaohong Lin: Data curation ; formal analysis ; writing – original draft ; writing – review and editing . Pengfei Yin: Data curation ; formal analysis ; writing – original draft . Kai Mao: Conceptualization ; supervision ; writing – original draft ; writing – review and editing . Jianlong Zhang: Conceptualization ; project administration (lead); resources (lead); supervision ; writing – original draft ; writing – review and editing .This research received no external funding.The authors have no conflicts of interest to declare.As the study consisted of the retrorespective analysis of anonymous data according to the local ethics committee, a special approval is generally not required.