Jatropha curcas L., a perennial woody plant belonging to Euphorbiaceae.In higher plants, inflorescence architecture is an important agronomic trait directly determining seed yield. However, little information is available on the regulatory mechanism of inflorescence development in perennial woody plants. Based on two inflorescence branching mutants, we investigated the transcriptome differences in inflorescence buds between two mutants and wild-type (WT) plants by RNA-Seq to identify the genes and regulatory networks controlling inflorescence architecture in Jatropha. The duo xiao hua (dxh) mutant has a seven-order branch inflorescence, and the gynoecy (g) mutant has a three-order branch inflorescence, while WT Jatropha has predominantly four-order branch inflorescence, occasionally the three- or five-order branch inflorescences in fields. Using weighted gene correlation network analysis (WGCNA), we identified several hub genes involved in the cytokinin metabolic pathway from modules highly associated with inflorescence phenotypes. Among them, Jatropha ADENOSINE KINASE 2 (JcADK2), ADENINE PHOSPHORIBOSYL TRANSFERASE 1 (JcAPT1), CYTOKININ OXIDASE 3 (JcCKX3), ISOPENTENYLTRANSFERASE 5 (JcIPT5), LONELY GUY 3 (JcLOG3) and JcLOG5 may participate in cytokinin metabolic pathway in Jatropha. Consistently, exogenous application of cytokinin  on inflorescence buds induced high-branch inflorescence phenotype in both low-branch inflorescence mutant (g) and WT plants. These results suggested that cytokinin is an important regulator in controlling inflorescence branching in Jatropha. In addition, comparative transcriptome analysis showed that Arabidopsis homologous genes Jatropha AGAMOUS-LIKE 6 (JcAGL6), JcAGL24, FRUITFUL (JcFUL), LEAFY (JcLFY), SEPALLATAs (JcSEPs), TERMINAL FLOWER 1 (JcTFL1), and WUSCHEL-RELATED HOMEOBOX 3 (JcWOX3), were differentially expressed in inflorescence buds between dxh and g mutants and WT plants, indicating that they may participate in inflorescence development in Jatropha. The expression of JcTFL1 was downregulated, while the expression of JcLFY and JcAP1 were upregulated in inflorescences in low-branch g mutant.Two inflorescence branching mutants were identified in germplasm collection of Jatropha. The regulation of inflorescence architecture by the genes involved in floral development, including TFL1, LFY and AP1, may be conservative in Jatropha and Arabidopsis. Our results provide helpful information for elucidating the regulatory mechanism of inflorescence architecture in Jatropha.Cytokinin is an important regulator in controlling inflorescence branching in  Arabidopsis thaliana, CLAVATA (CLV) pathways regulate meristem maintenance by restricting the expression of WUSCHEL (WUS), which defines the stem cell niche [CLAVATA  results in the accumulation of meristem cells to generate an increased shoot meristem dome [WUS causes defective shoot and floral meristems [thick tassel dwarf1 (td1) and fasciated ear2 (fea2) are orthologs of CLV1 and CLV2, respectively. Loss-of-function mutant td1 exhibits a fascinated ear with extra rows of kernels and a tassel with more dense spikelets [fea2 mutant exhibits a massive ear inflorescence meristem and increased organ number [Inflorescence architecture directly influencing plant reproductive success , is a kell niche , 6. A mutem dome . Mutatiopikelets . The fean number .Arabidopsis, the transition time from the inflorescence to floral meristem is critical in the determination of inflorescence architecture; TERMINAL FLOWER1 (TFL1), LEAFY (LFY) and APETALA1 (AP1) participate in this process and regulate inflorescence branching patterns [TFL mutation promotes the conversion of the inflorescence meristem into the floral meristem, causing an abnormal inflorescence with a compound floral structure [TFL1 in a transgenic plant induces a highly branched inflorescence phenotype in Arabidopsis [LFY and AP1 repress the expression of TFL1 in the floral meristem [SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1), SHORT VEGETATIVE PHASE (SVP), AGAMOUS-LIKE 24 (AGL24), and SEPALLATA 4 (SEP4) redundantly regulate inflorescence architecture by directly suppressing the expression of TFL1; a soc1–2 agl24–3 svp-41 sep4–1 quadruple mutant displays a massive inflorescence branching phenotype [In patterns , 11. TFLtructure . By contbidopsis . Conversmeristem . Moreovehenotype .RCN1 and RCN2 and maize ZCN1-ZCN6, which are homologous to Arabidopsis TFL1, causes highly branched inflorescences through maintaining the indeterminacy of the inflorescence meristem [TAWAWA1 (TAW1) regulates inflorescence architecture by suppressing the specification of the spikelet meristem to maintain the indeterminacy of inflorescence architecture [tawawa1-D, exhibits a highly branched inflorescence and increased number of spikelets, whereas a TAW1 knockdown mutant displays a small, reduced branching inflorescence resulting from early termination of inflorescence meristems and the formation of spikelet meristems [WEALTHY FARMER’S PANICLE (WFP)/IDEAL PLANT ARCHITECTURE (IPA1) locus is linked to a Squamosa Promoter Binding Protein-Like 14 (OsSPL14) gene that can be suppressed by OsmiR156 [OsSPL14 that relieves the repression of OsmiR156 causes increased panicle branching and grain number [UNBRANCHED3 (UB3), an ortholog of rice OsSPL14, dramatically repressed tillering and panicle branching in rice; however, moderate expression of UB3 slightly suppressed tillering, but promoted panicle branching, resulting in an increased grain number per panicle in rice [Overexpression of rice meristem , 17. Ricitecture . A gain-eristems . In riceOsmiR156 . A singln number , 20. Ove in rice , 22.APETALA2-like genes, indeterminate spikelet1 (ids1) and sister of indeterminate spikelet 1 (SID1), are required for inflorescence branching by regulating the initiation of spikelet meristem and floral meristem, and an ids1 sid1 double mutant shows a reduced branching inflorescence phenotype [RAMOSA1 (RA1), RA2 and RA3, regulate the fate of the inflorescence meristem, and mutations in these genes cause an increased long-branching inflorescence [In maize, two henotype . Three mrescence –26.Arabidopsis, the YUC gene encodes flavin monooxygenases (FMOs) that catalyze a rate-limiting step in tryptophan-dependent auxin biosynthesis; overexpression of YUC promotes auxin levels during development processes [sparse inflorescence1 (spi1), a homologous Arabidopsis YUC, encodes a FMO, and spi1 mutation reveals defects in the initiation of axillary meristems and lateral organs, causing reduced branch number and floral organs in inflorescences [pin1 or pid causes a pin-like inflorescence with abnormal flowers because of defects in the initiation of the axillary meristem in Arabidopsis [barreninflorescence2 (bif2), an ortholog of PID, is required for the initiation of the axillary meristem and lateral primordia; the bif2 mutant displays a reduced number of branches, spikelets, florets and kernels in inflorescences [Barren inflorescence1 (bif1) mutation causes a similar phenotype to that of the bif2 mutant [barren stalk1 (ba1) mutant displays an unbranched inflorescence without spikelets because of a defect in auxin signaling [Setaria viridis, SvAUXIN1 is required for inflorescence development and its loss-of-function mutant sparse panicle1 (spp1) displays reduced and uneven inflorescence branching phenotype [Plant hormones such as auxin and cytokinin are required for the initiation and outgrowth of axillary meristems that generate inflorescence branches and florets during reproductive development , 28. Sevrocesses . In maizescences . Auxin tbidopsis , 32. Maiescences . Barren 2 mutant ; the barignaling . In Setahenotype .Arabidopsis, CYTOKININ OXIDASE 3 (CKX3) and CKX5 catalyze the degradation of cytokinin; ckx3 ckx5 double mutant display larger inflorescences and floral meristems because of the accumulation of cytokinin [Gn1, encodes an OsCKX2; the reduced expression of OsCKX2 causes higher cytokinin levels in the inflorescence meristem to increase the number of branches and spikelets, leading to enhanced grain yield [LONELY GUY (LOG) gene encodes an enzyme that participates in the final step of bioactive cytokinin synthesis; mutation in log causes a small inflorescence with reduced branch and spikelet number [Cytokinin is required for meristem activity and plays a positive role in the shoot meristem . In Arabytokinin . In ricein yield . A zinc in yield . The LONt number .At present, the studies on molecular mechanism of inflorescence architecture are focus on the model plants and few in perennial woody plants because of their long reproductive cycle and the difficulty in the establishment of genetic transformation system. To understand the regulatory mechanism of inflorescence architecture, the investigation of the evolutionary changes in developmental morphology and the identification of key factors controlling inflorescence development are crucial in closely related plant lineages that display different inflorescence structures , especiaJatropha curcas L. has high seed oil content and is considered a potential biofuel plant [Jatropha inflorescence exhibits a dichasial cyme pattern bearing male and female flowers in the same inflorescence. Few female flowers per inflorescence is considered one of the factors leading to poor seed yield in Jatropha [JcLFY delayed flower formation, leading to production of more secondary inflorescence branches [JcTFL1b [JcAP1 [Jatropha [Jatropha. In this study, two Jatropha mutants that exhibit different inflorescence branching traits were used for comparative transcriptome analysis to identify genes and regulation networks that participate in the regulation of inflorescence architecture. Our study will contribute to the understanding of the genetic basis of inflorescence architecture and to the breeding of high-yield Jatropha varieties.el plant , 42. TheJatropha . Our prebranches , but rol[JcTFL1b , 45 and b [JcAP1  in infloJatropha , 48. CytJatropha , 49, 50,Jatropha has a four-order branch cyme inflorescence bearing female and male flowers, and three- or five-order branch inflorescence is occurred occasionally in different growth conditions. Here, we reported two inflorescence branching mutants: a high-branch dxh (Chinese for “more florets”) mutant with a seven-order branch inflorescence, which came from a mutagenized population treated with cobalt-60 gamma rays; a low-branch g mutant with a three-order branch inflorescence, which originated from a natural mutation [dxh mutant, the total flower number, female flower number, fruit number, seed number, seed yield and oil content were significantly increased, whereas the female-to-male ratio was decreased, and the 100-seed weight remained constant in dxh mutant plants compared with those in WT plants  mutation  Fig. 1)Jatropha nts Fig. . The incdxh mutant (referred to as dxhI and dxhII), and inflorescence buds from the g mutant (referred to as gII). A multidimensional scaling (MDS) plot showed that ckI, dxhI and gII samples can be well separated from ckII and dxhII based on the biological coefficient of variation (BCV)  (Fold change ≥2.0 and FDR < 0.05) , FRUITFUL (JcFUL), JcLFY, SEPALLATA 1 (JcSEP1), JcSEP2a, JcSEP2b, JcSEP3 and WUSCHEL-RELATED HOMEOBOX 3 (JcWOX3) was upregulated, whereas expression of JcAGL24 and JcTFL1 was downregulated in pairwise low-branch vs. high-branch mutant (gII_dxhII). In Arabidopsis, TFL1 promotes inflorescence branching, whereas LFY and AP1 prevent inflorescence branching by repressing the expression of TFL1 in the floral meristem [JcTFL1, JcLFY and JcAP1 may play similar roles in controlling inflorescence architecture in Jatropha, suggesting the function of these genes may be conservative in Jatropha and Arabidopsis.According to meristem , 8, 10. Arabidopsis and rice [Jatropha ALDEHYDE OXIDASE 1 (JcAAO1), CHALCONE SYNTHASE (JcCHS), cytochrome P450, family 83, subfamily B, polypeptide 1 (JcCYP83B1), IAA carboxyl methyltransferase 1 (JcIAMT1), JcPID, JcPIN1, SMALL AUXIN UP RNA 20 (JcSAUR20), and YUCCA4 (JcYUC4) may be involved in the auxin metabolic and signaling pathways. Jatropha CYTOKININ OXIDASE/DEHYDROGENASE 3 (JcCKX3), JcCKX7, ISOPENTENYLTRANSFERASE 1 (JcIPT1), JcIPT5, JcLOG1, JcLOG3, and JcLOG5 may be involved in the cytokinin metabolic and signaling pathways. All of them were differentially expressed in inflorescences in pairwise high-branch mutant vs. WT (dxhII_ckII) or low-branch mutant vs. WT (gII_ckII) (Fold change ≥2.0 and FDR < 0.05) , JcAPT1, JcCKX3, ISOPENTENYLTRANSFERASE 5 (JcIPT5), LONELY GUY 3 (JcLOG3) and JcLOG5 involved in the cytokinin metabolic pathway, four genes JcAAO1, JcPID, JcPIN1, and JcPIN3 in the auxin biosynthetic and signaling pathways, JcSOC1, SPATULA (JcSPT) and five LncRNA genes. Among them, JcADK2, JcAPT1, JcCKX3, JcIPT5, JcLOG3, JcLOG5, JcPID, JcPIN1 and JcPIN3 were differentially expressed across different phenotypic inflorescences. The results showed that cytokinin and auxin metabolic or signaling pathways may participate in inflorescence development and may play vital roles in controlling inflorescence architecture.We constructed a gene co-expression network using the WGCNA package . In the g) and WT plants, respectively. After 6-BA treatment, more than 70% of inflorescences displayed high-branch phenotype in both g mutant and WT plants, although the growth of some inflorescence buds was arrested . These results indicate that cytokinin is an important regulator in regulating inflorescence branching in Jatropha.To validate the functions of cytokinin and auxin in inflorescence branching, we applied 6-BA (cytokinin) and 1-naphthaleneacetic acid  to the inflorescence buds of low-branch mutant  inflorescence compared to those in high-branch mutant (dxh) and WT inflorescences. These effects may cause the low-branch inflorescence phenotype of g mutant.In inflorescence development, cytokinin and auxin are essential for the formation and growth of the inflorescence branch meristem in and rice , 28. A geostasis , 55. ATPeostasis . Isopenteostasis . LOG pro in rice . In pairArabidopsis, TRYPTOPHANAMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) catalyzes the conversion from L-tryptophan (Trp) to indole-3-pyruvic acid (IPA), and YUC FMOs catalyze the oxidative decarboxylation of IPA to generate indole-3-acetic acid (IAA), both of which are the key enzymes in auxin biosynthesis [JcTAA1 and JcYUC4 was downregulated, indicating that auxin biosynthesis is decreased in low-branch (g) mutant inflorescence compared to that in high-branch (dxh) mutant inflorescence, along with the downregulated expression of JcPIN1 and JcPID whose homologous genes serve as efflux carriers in auxin polar transport in Arabidopsis [JcSAUR20, an auxin responsive gene, was downregulated, and JcIAMT1 and JcCHS were upregulated, confirming that auxin biosynthesis may be decreased in low-branch mutant (g) inflorescence. In Arabidopsis, IAMT1 encodes an IAA carboxyl methyltransferase that converts IAA to methyl-IAA ester (MeIAA); the overexpression of MeIAA causes dramatic hyponastic leaf phenotypes [CHS encodes the first enzyme in flavonoid biosynthesis that is considered an auxin transport inhibitor [JcAAO1 and JcCYP83B1 genes, which are also involved in the auxin biosynthetic signaling pathways [In ynthesis , 60. Thebidopsis , 62  and WT plants  and WT plants. These results supported that cytokinin is an important regulator and may play vital role in controlling inflorescence branching in Jatropha. Several Arabidopsis homologous genes involved in inflorescence development is significantly differentially expressed in inflorescence buds between mutants and WT plants, indicating that they participate in the regulation of inflorescence architecture in Jatropha. Based on the above results, we speculate that the change of inflorescence branching phenotype of two mutants may result from mutations at one or more loci in genome regions that contain genes involved in cytokinin metabolism and/or in inflorescence development. Our results will be helpful for elucidating the regulatory mechanism of inflorescence architecture in Jatropha.Using WGCNA, we identified several hub genes involved in the cytokinin metabolic pathway from modules highly associated with inflorescence architecture phenotypes. The application of cytokinin (6-BA) to inflorescence buds induced high-branch inflorescences both in low-branch mutant (duo xiao hua (dxh) and gynoecy (g) mutant were grown in field in the Xishuangbanna Tropical Botanical Garden (XTBG) of the Chinese Academy of Sciences  located in Mengla County, Yunnan Province, China. WT plant has a four-order branch inflorescence under normal growth conditions, occasionally a three- or five-order branch inflorescence. The dxh mutant has a high-branch inflorescence phenotype, a seven-order branch inflorescence, which was derived from a mutagenized population treated with cobalt-60 gamma rays. Its selfing progeny was selected until the stable high-branch inflorescence phenotype. The g mutant has a low-branch inflorescence phenotype, a three-order branch inflorescence, which was derived from a natural variation [The wild-type (WT), ariation . The cutg) and WT plants were selected for once treatment with 1.0 mM 6-BA solution containing 0.05% Tween-20. The 6-BA and mock solutions were sprayed onto inflorescence buds wetting them to the point of run-off, ten inflorescence buds from three to five plants per treatment. After 2–3 weeks, inflorescence phenotypes were surveyed. Seed oil content was measured by using the minispec mq-one Seed Analyzer  as described previously [To confirm the effect of cytokinin on inflorescence branching, middle stage inflorescence buds (about 0.8 cm in diameter) that growth approximately 7–10 days from occurrence of invisible inflorescence bud of low-branch mutant  and WT, respectively. In total 33 inflorescence/infructescence are surveyed in dxh and 44 ones in WT. Statistical test analysis was performed using the Welch two sample t-test in R software (https://cran.r-project.org).During the suitable period, the total flower number, female flower number, ratio of female-to-male flowers, fruit number, seed number, seed yield, weight of 100 seeds, and seed oil content per inflorescence/infructescence were surveyed in high-branch inflorescence mutant (dxh and WT plants. Inflorescence buds that growth approximately 3–4 days from occurrence of invisible inflorescence bud (about 0.4 cm in diameter) were harvested from dxh and g mutants and WT plants. Three shoot tips or inflorescence buds were pooled as one biological replicate for RNA isolation, three replicates per sample. Total RNA extraction, library construction and quality control were performed as previously described [At initial reproductive period, after removed leaves, shoot tips that can generate inflorescence meristem were harvested from escribed . Sequenchttp://www.bioinformatics.babraham.ac.uk/projects/fastqc). De novo transcriptome assembly was performed using Trinity (version 2.0.6) with default parameters [Raw reads were treated with the Fastq_clean  and asserameters , 69. In rameters .http://bioinfogp.cnb.csic.es/tools/venny/index.html). Hierarchical clustering of transcripts was performed using the pheatmap R package (version 1.0.7) (https://github.com/cran/pheatmap).The Corset (version 1.03) was used for abundance estimation of transcripts . Differehttp://plants.ensembl.org) with Evalue < 1.0E-05. Among them, 14,680 transcripts were annotated and 1526 were not found .RNA samples for qPCR are same as RNA-seq ones. The cDNA was synthesized from total RNA (1.0 μg) using a PrimeScript RT Reagent Kit , for each sample. qPCR was performed on a LightCycler 480 II  using the SYBR green I Kit (Roche), with three independent biological replicates for each sample and three technical replicates. 2(x + 1), from edgeR were applied to construct co-expression networks using the R package weighted gene correlation network analysis (WGCNA) [The raw count data of differentially expressed genes, which were transformed with Log (WGCNA) . The sof (WGCNA) .Additional file 1. Sequencing read counts, quality, and alignment statistics for 15 Jatropha samples.Additional file 2. Relationships of 15 inflorescence bud samples based on multidimensional scaling (MDS) analysis. The MDS plot is generated using plotMDS function in edgeR package. The distances between samples correspond to biological coefficient of variation (BCV) between those samples. ckI indicates the shoot tips of WT, containing ckI_1, ckI_2 and ckI_3 samples; ckII indicates the inflorescence buds of WT, containing ckII_1, ckII_2 and ckII_3 samples; dxhI indicates the shoot tips of dxh mutant, containing dxhI_1, dxhI_2 and dxhI_3 samples; dxhII indicates the inflorescence buds of dxh mutant, containing dxhII_1, dxhII_2 and dxhII_3 samples; and gII indicates the inflorescence buds of g mutant, containing gII_1, gII_2 and gII_3 samples, respectively.Additional file 3. Differentially expressed genes in inflorescences between six pairs in Jatropha. The pairwise ckII_ckI, dxhII_dxhI, dxhI_ckI, dxhII_ckII, gII_ckII and gII_dxhII indicate the same pairs shown in Fig. Additional file 4. List of differentially expressed genes identified in inflorescences between six pairs in Jatropha. The pairwise ckII_ckI, dxhII_dxhI, dxhI_ckI, dxhII_ckII, gII_ckII and gII_dxhII indicate the same pairs shown in Fig. Additional file 5. The overlap of differentially expressed genes in inflorescences between six pairs in Jatropha. The pairwise ckII_ckI, dxhII_dxhI, dxhI_ckI, dxhII_ckII, gII_ckII and gII_dxhII indicate the same pairs shown in Fig. Additional file 6. Differentially expressed genes with opposite expression patterns in inflorescences between pairwise dxhII_ckII and gII_dxhII.Additional file 7. Homologous genes involved in inflorescence development in Jatropha.Additional file 8. Homologous genes involved in the auxin and cytokinin metabolic and signaling pathways in Jatropha.Additional file 9. Validation of the expression profiles of 12 candidate genes by real-time qPCR. ckI and dxhI indicate the shoot tips of WT plants and dxh mutants; ckII, dxhII and gII indicate inflorescence buds of WT, dxh and g mutants, respectively. JcGAPDH was as the internal reference. The error bars represent SD (n = 3).Additional file 10. List of primers for qPCR validation.Additional file 11. Correlation analysis between RNA-Seq and qPCR expression data of the genes shown in Additional file Additional file 12. Weighted co-expression network and modules identified by WGCNA analysis. Each leaf in the hierarchical cluster tree represents one gene; each row and column of the heat map plot corresponds to one gene; in the heat map, light color indicate weak co-expression, and dark color indicates strong co-expression; twenty-two modules were labeled by different colors.Additional file 13. Correlation analysis of modules and phenotype traits. Each row and column represent one module; the red color represents high adjacency (positive correlation), and blue color represents low adjacency (negative correlation); red squares along the diagonal indicate the modules with similar expression patterns.Additional file 14. Gene list in MEblack and MEblue modules.Additional file 15. Application of 6-benzylaminopurine (6-BA) promotes inflorescence branching of g mutants and WT plants. (A)-(D) show the complete inflorescence, and (E)-(H) show the dissected inflorescence, respectively. (A) and (E) indicate an increased inflorescence branching treated with 6-BA and (B) and (F) display a normal inflorescence branching of g mutants with mock. (C) and (G) indicate an increase inflorescence branching treated with 6-BA and (D) and (H) display a normal inflorescence branching of WT plants with mock. The numbers in (E)-(H) represent different orders of inflorescence branching. Bar = 5.0 cm.Additional file 16. Annotation of transcripts.Additional file 17. Transcripts sequences used for the differential expression analysis.


Staphylococcus epidermidis  was examined for protein level, pleocytosis, interleukins, CCL26/Eotaxin-3, IL-5, IL-6, CCL11/Eotaxin-1, CCL3/MIP-1a, and MBP. Three measurements were performed in the study group. The first measurement was obtained at the time of shunt infection diagnosis, the second one at the time of the first sterile shunt, and the third one at the time of shunt reimplantation. In the control group, blood and CSF samples were taken once, at the time of shunt implantation.The study group involved 30 children with congenital hydrocephalus after shunt system implantation, whose procedures were complicated by In the clinical material, the highest values of eosinophils in peripheral blood and CSF pleocytosis were observed in the second measurement. It was accompanied by an increase in the majority of analyzed CSF interleukins.Staphylococcus epidermidis, the causative agent of ventriculoperitoneal shunt infection.CSF pleocytosis observed in the study group shortly after CSF sterilization is presumably related to an allergic reaction to  Staphylococcus epidermidis is the main cause of ventriculoperitoneal shunt infection [Staphylococcus aureus and Staphylococcus epidermidis are responsible for the formation of biofilm on contaminated catheters [Staphylococcus epidermidis or Staphylococcus aureus infections are based on animal models. It is uncertain whether animal models fully depicted the corresponding reactions in humans [Methicillin-resistant nfection , 19, 23.atheters . A biofiatheters . Biofilmatheters . Polysacatheters . The bioatheters . Biofilmatheters . Immunoln humans . Furthern humans .The aim of the article was to describe an immunological reaction to shunt infections in children, particularly the eosinophilic reaction. Elevated levels of eosinophils may be indicative of a latent infection or a hypersensitivity reaction to the shunt material. Inert and non-immunogenic serum proteins may adhere to shunt surfaces. This protein-silicone complex can act as an opsonin, thus stimulating an inflammatory response , 19.The material includes 30 pediatric patients admitted and operated in the Polish Mother Memorial Hospital, Łódź, Poland.S. epidermidis CSF infection were included in the study group.The study covered 30 pediatric patients . Average age of patients was 8.4 months (± 5.8). The children were hospitalized in the Polish Mother Memorial Hospital between 2010 and 2014. All children from the study group suffered from congenital hydrocephalus. The children were admitted to the hospital because of their first shunt dysfunction secondary to shunt infection. Only children with The control group was composed of 30 pediatric patients who underwent first-time ventriculoperitoneal shunt (VPS) implantation. Children who suffered from hydrocephalus due to inflammation, hemorrhage, or tumor were excluded. Additionally, all patients who could have been treated with neuroendoscopic techniques at any point of the therapy were excluded from the control group. Patient characteristics were as follows: 17 male and 13 female patients, gender ratio M/F = 1.21:1, average age 1.2 months (± 0.3).CSF analysis in the study subjects and controls included pleocytosis, protein levels, – CCL26/Eotaxin-3, CCL11/Eotaxin-1, IL-8, IL-5, IL-6, and MBP. Additionally, full blood counts were evaluated in both groups to assess absolute and relative changes in eosinophil levels accompanying changes in CSF chemokines.In the study group, CSF and blood samples were obtained three times.The first CSF samples were collected at admission (measurement I). After confirmation of infection, all patients were operated to replace VPS by external intraventricular drainage. Proper targeted antibiotic therapy was implemented, which was in every case 5 mg of vancomycin administered every 24 h intraventricularly. The average duration of antibiotic therapy was 20.2 days (SD ± 7.9 days).The first sterile CSF culture specimen was taken into consideration as the measurement II. The sterility of the CSF fluid was confirmed by two additional cultures. The antibiotic therapy was maintained until VPS reimplantation. The average time needed for normalization of CSF cytosis and protein levels was 23.8 days (SD ± 5.27 days). The third CSF sample for research purposes was taken during VPS reimplantation (measurement III).All 30 pediatric patients from the control group had CSF and blood samples taken at the time of VSP implantation (measurement control).For safety reasons, only one 5-ml CSF sample from the ventricular system was taken both in the study group and controls.All CSF specimens were stored at a temperature of − 80 °C. Prior to testing, samples were heated to − 20 °C and then to room temperature. To remove cellular components, the CSF samples were centrifuged at 2000 rpm for 10 min. The supernatant was drawn off in amount of 2.0 ml. The following quantitative determinations were performed using the ELISA assay. Ready-made standardized sets were used ). Absorbance reading of the test samples was performed using a microplate DS2 Dynex Technologies, Inc., USA reader. The test is performed using cell culture supernatants. This method is more sensitive compared to the determination in blood serum. Physiological saline was used as negative control.Absorbance values for each sample were read at the wavelength of 450 nm. Concentration values of the test samples were calculated automatically from the standard curve. Measurements in the following material were made, where the sensitivity of the test, i.e., the minimal detectable concentration, was 0.31–0.20 ng/ml.In the study group, CSF parameters, such as the levels of – CCL26/Eotaxin-3, CCL11/Eotaxin-1, IL-8, IL-5, IL-6, MBP, cytosis, and protein obtained in three measurements, were compared using variance analysis. Additionally blood morphology was checked at the same time as CSF analysis. Bonferroni post hoc analysis was used to test for significant differences between the three measurements.p < 0.05. SPSS 17.0 software was used for the entire statistical analysis.The above parameters obtained in each of the three measurements in the study group were compared with the corresponding parameters in the control group using the Friedman test (post hoc Wilcoxon test with Bonferroni correction for the number of comparisons). The Kolmogorov-Smirnov test with Lilliefors correction was used to assess the normality of distribution. The homogeneity of variances was tested with the Mauchly test. For non-homogenous variances, the Greenhouse–Geisser correction was applied. The level of statistical significance was set at 3 c/μl (± 0.67 × 103 c/μl). Variance analysis (p < 0.001) showed that it was significantly higher in comparison with the first measurement, in which the average level of eosinophils was 1.07 × 103 c/μl (± 0.12 × 103 c/μl). Finally, variance analysis (p < 0.001) indicated that the average eosinophil level measured shortly before shunt implantation was significantly lower compared to the result obtained at the time of the diagnosis of infection 0.49 × 103 c/μl (± 0.12 × 103 c/μl). In the control group, the level of eosinophils was significantly lower than that in the study group—0.17 × 103 c/μl (± 0.06 × 103 c/μl) (p < 0.001) in each measurement . The lowest level of eosinophil percentage was reached in the third measurement. The average percentage was 5.70% (± 0.67%). It was significantly lower than that in the first measurement—7.01% (± 0.69%) (p < 0.001). In the control group, eosinophil percentage measured in the blood just before shunt implantation was significantly lower than that in all measurements in the study group (p < 0.001). It was on average 3.89% (± 0.92%) .The difference between it and the rest of measurements was of statistical significance (p < 0.001). However, unlike the eosinophils, there was no statistically relevant difference between the first and the third measurements (p > 0.999). In the control group, pleocytosis was significantly lower than that in the second measurement according to the Mann–Whitney U test (p = 0.001), with an average value of 7.83 c/μl (± 6.81 c/μl). Also, in contrast to eosinophils, there were no statistically significant differences between the control group and the study group in the first and in the third measurements. Changes in median pleocytosis in the study group are shown in Fig. CSF pleocytosis revealed a similar relationship between individual measurements as the one seen for eosinophils. The highest level of pleocytosis was reached in the second measurement. The average result was 106.03 c/μl (± 145.21 c/μl). It was higher than that in the first measurement 7.90 c/μl (± 7.80 c/μl) and the third measurement 13.10 c/μl (± 19.53 c/μl). Both relationships were statistically significant according to variance analysis test , p < 0.001. According to the Mann–Whitney U test, CSF protein level was significantly lower in controls than that in the study group. It was on average 17.47 mg% (± 9.24 mg%). This value was lower in comparison with measurements I (p < 0.001), II (p < 0.001), and III (p = 0.013). Changes in median CSF protein levels in the study group in individual measurements are shown in Fig. The opposite trends were observed in the analysis of total CSF protein level. The highest level was already reached in the first measurement. It was on average 1291.63 mg% ± 497.80 mg%). In subsequent measurements, the average protein level was significantly lower. The second one was 179.83 mg% (± 83.12 mg%), 97.80 mg%Staphylococcus and Streptococcus species [Angiostrongyliasis cantonensis (~ 70% of patients) and Gnathostoma spinigerum (> 55% of patients). Other infections with a concomitant eosinophilic reaction may include different microorganisms, such as helminths, fungi, bacteria, and viruses [Staphylococcus species to form the so-called biofilms [Staphylococcus species [Shunt infection may be associated with the number of shunt revisions, patient age, manual shunt system, and exposure to surgical instruments. The overall incidence amounts to 3–15% of all implanted shunt systems , 20, 21. species . The cli species , 22. Thi species , 19, 22. species , 22 Eosi species . This re viruses , 11, 22. viruses . It is sbiofilms . As it h species , 19. Ano species . In addi species . The thi species . The sig species , 22. The species . But in  species . There i species . The ele species . The ass species . Another species . FinallyStaphylococcus epidermidis responsible for ventriculoperitoneal shunts infection.CSF pleocytosis observed in the study group shortly after CSF sterilization is presumably connected with an allergic reaction to The allergic reaction could be also responsible for absolute and relative increase of eosinophils in peripheral blood just after CSF sterilization.Staphylococcus epidermidis could make shorter process of treatment bacterial infection.Ceasing the allergic reaction to the


Background: Synergistic recruitment of muscular activities is a generally accepted mechanism for motor function control, and motor dysfunction, such as cerebral palsy (CP), destroyed the synergistic electromyography activities of muscle group for limb movement. However, very little is known how motor dysfunction of CP affects the organization of the myoelectric frequency components due to the abnormal motor unit recruiting patterns.Objectives: Exploring whether the myoelectric activity can be represented with synergistic recruitment of surface electromyography (sEMG) frequency components; evaluating the effect of CP motor dysfunction on the synergistic recruitment of sEMG oscillations.Methods: Twelve CP infants and 17 typically developed (TD) infants are recruited for self-paced crawling on hands and knees. sEMG signals have been recorded from bilateral biceps brachii (BB) and triceps brachii (TB) muscles. Multi-scale oscillations are extracted via multivariate empirical mode decomposition (MEMD), and non-negative matrix factorization (NMF) method is employed to obtain synergistic pattern of these sEMG oscillations. The coefficient curve of sEMG oscillation synergies are adopted to quantify the time-varying recruitment of BB and TB myoelectric activity during infants crawling.Results: Three patterns of sEMG oscillation synergies with specific frequency ranges are extracted in BB and TB of CP or TD infants. The contribution of low-frequency oscillation synergy of BB in CP group is significantly less than that in TD group (p < 0.05) during forward swing phase for slow contraction; however, this low-frequency oscillation synergy keep higher level during the backward swing phase crawling. For the myoelectric activities of TB, there is not enough high-frequency oscillation recruitment of sEMG for the fast contraction in propulsive phase of CP infants crawling.Conclusion: Our results reveal that, the myoelectric activities of a muscle can be manifested as sEMG oscillation synergies, and motor dysfunction of CP degrade the synergistic recruitment of sEMG oscillations due to the impaired CNS regulation and destroyed MU/muscle fiber. Our preliminary work suggests that time-varying coefficient curve of sEMG oscillation synergies is a potential index to evaluate the abnormal recruitment of electromyography activities affected by CP disorders. Cerebral palsy (CP) is a permanent movement disorder caused by brain injury in early childhood with a high prevalence of 2–3 per 1,000 live births , very liVarious features of sEMG signals have been proposed for assessing the abnormal neuromuscular functions in CP patients. The sEMG characteristics from individual muscle, including parameters in time- and frequency-domain, can be used to measure the abnormal overall sEMG activity of CP. Researchers found the changes of magnitude, frequency content and timing from sEMG signals of individuals with CP. The time- and frequency-domain parameters were also utilized to analyze symmetry, cadence, or smoothness of muscle activity for CP patients –7. On thRecent studies have demonstrated that the sEMG spectrum profile or frequency components correlated with physiological status of movement. Von et al.  reportedIt is generally accepted that multiple element synergistic organization is a fundamental strategy for motor control, and the elements can be well-organized by CNS to perform limb movement , 22. A vInspired by muscle synergy, different types of MUs might also be manifested as specific oscillation synergy patterns. In other words, the synergistic recruitment mechanism should be manifested with coordinated activation of muscle groups and of different types of MUs in individual muscles. Hence, we assumed sEMG frequency components or oscillations might also be recruited with a synergistic pattern for normal motor function, whereas motor dysfunction of CP may affect the organization patterns of oscillation components. To this end, we recorded the sEMG signals from biceps brachii (BB) and triceps brachii (TB) muscles of the upper limbs during infant crawling, extracted sEMG oscillations and analyzed their synergy patterns to explore the abnormal organization of sEMG oscillations in CP.Under the approval of children's hospital of Chongqing medical university, 17 infants with typical development  and 12 infants with cerebral palsy  were recruited in this study. Cerebral palsy infants were collected from the department of rehabilitation center in the children's hospital of Chongqing medical university. The TD infants were recruited from local child health clinics. The inclusion criteria for CP infants included: (1) all CP infants were under the age of 3 years old; (2) crawling continuously on their hands and knees during the test; (3) no other diseases that lead to motor function deficits according to the historical records. The TD infants were born at term with normal birth weight and had no neurological impairment. To make sure all subjects can crawl continuously on hands and knees, the Gross Motor Function Measure (GMFM-88) was conducted before experiments. Informed consent forms were obtained from participants' legal guardians before experiments.The infants were encouraged to crawl at their own pace from one end of a mat (360 × 120 cm) to the opposite side. Valid crawling cycle sequence requires infants to crawl continuously on hands and knees more than four cycles. Before the experiment, infants crawled on the mat several minutes to warm up.As the major activated muscles of the upper limb during crawling, bilateral BB and TB were selected for sEMG recording. After disposable surface electrodes were attached to the muscle belly and bandaged to reduce motion artifacts Figure , sEMG siTo specify the crawling phase, 14 markers were attached on the bony landmarks of the bilateral wrist, elbow, shoulder, hip, knee, ankle, the right spine scapula, and the trunk, respectively  and residual r(t), which can be described asEMD is a fully data-driven analysis approach which self-adaptively decomposes a non-linear and non-stationary signal into several intrinsic mode functions . HoweverThe IMFs obtained after MEMD analysis have the same number for each channel and orderly align scales across channels .Referred literature , we firsCHij is the ith channel of the valid sEMG signal segments for the jth subject. Here, we recorded four channel sEMG signals, and totally 29 subjects conducted the test; that is to say, i = 1, 2, 3, 4; j = 1, 2, …, 29. To reduce the mode mixing in multivariate IMFs  and the shoulder joint angle  (W (2/s2) to decide the onset of limb moving and the end moment of a crawling phase  and propulsive phase (PRP) with the minimum of time derivative of AS (wS).Kinematics data were processed with a zero-lag low-pass filter  to remove high-frequency noise. As shown in Figures l plane) . Figure ng phase . To refiAs the frequency of IMF9 is below 20 Hz and out of sEMG frequency range (20–500 Hz), the first eight IMFs are included for oscillation recruitment analysis. Envelopes of the first eight IMFs of each channel sEMG signal were extracted (Hilbert spectrum and median filtering) and segmented into cycles according to kinematics data. The envelopes were re-sampled into 200 points for each cycle. The synergies of sEMG oscillation were extracted with NMF, which decompose a non-negative matrix V into two non-negative matrixes including a base matrix W and corresponding recruitment coefficient matrix C . Here, eVm×n represents the envelopes of m IMFs (m = 8), and n is the sample number (n = 200). Each column of Wm×s represents an oscillation synergy with m weight factors (1 ≤ s ≤ m), and s is the number of synergies. Each row of Cs×n represents corresponding recruitment coefficients, which shows how each synergy is modulated over time. To maintain the modulation of information within oscillation synergies, C was normalized to its maximum values of the crawling cycle.In this study, the matrix of V and the reconstruction matrix V′ = WC for each s value (from 1 to 8)  between the original matrix  1 to 8) . VAF is Here, the selection criteria were that the mean of VAFs was larger than 95% and the increment of VAF was < 1%.t-test was applied on the recruitment coefficients for each phase. The significance level was set to 0.05. All the data were analyzed in SPSS 22.0 statistical software . In addition, Pearson's correlation coefficient (r) between any two oscillation synergies with the same order number was calculated to assess the similarities of oscillation synergy structures. Four kinds of r values were calculated between same within-groups muscles , between different within-groups muscles , between same between-groups muscles  and between different between-groups muscles .The recruitment coefficient values for each oscillation synergy were averaged over 3–4 valid cycles for each subject. For each TD infant or CP infant whose both side limbs were affected, as the symmetric movement for left and right side, the oscillation synergy and recruitment coefficient of sEMG signals recorded from right and left BB and TB muscles have been averaged firstly. In order to compare the recruitment pattern of each oscillation synergy, independent sample All of the recruited infants in this study can crawl continuously on hands and knees more than 4 valid cycles . Their hands-and-knees crawling scores were at least 44  according to GMFM. Although the crawling motor function scores of CP infants equal or even exceeded TD infants (in this study) after rehabilitation training, their motor development was indeed slower than that of TD infants at the same age. CP infants exhibited abnormal movement behavior and sEMG activities.s) was chosen as 3 according to the selection criteria above.The mean VAF values acquired in the NMF decomposition of the sEMG oscillations are shown in Figure Figure The recruitment coefficient curves of sEMG oscillation synergies are illustrated in Figure p = 0.023), and less synergy 1 or high-frequency sEMG oscillations in TB for the fast contraction in PRP crawling . During the BSP (p = 0.007) and BRP crawling (p = 0.006), CP maintained a high level of synergy3 in BB, which revealed that the sEMG oscillations with low-frequencies cannot be de-recruited effectively  and BRP (p = 0.047), there was a significantly higher activation level for synergy 2 in BB .To quantitatively evaluate the impact of CP on the recruitment pattern of oscillation synergies, the amplitude of recruitment coefficient curves was compared in the refined crawling phases of FSP, BSP, BRP, and PRP. As shown in Figure y Figure . FurtherB Figure , whereasTo deeply explore the effect of neuromuscular damage of CP on the motor regulation, this study aimed to extract and evaluate the oscillation synergy patterns from sEMG signals with MEMD and NMF during infant crawling. The present work showed that sEMG signals contained stable structures of oscillation synergy, and the motor dysfunction of CP affected the recruitment of oscillation synergies for crawling movement both in BB and TB.Crawling requires multiple skeletal muscles to participate in the regulation of limb joint flexion and extension. Muscles play different roles and their contraction patterns also vary with crawling phases. The results showed that the activation pattern of muscles can be expressed as synergistic recruitment of multi-scale sEMG oscillations. As shown in Figure Crawling is a periodic movement of flexion-extension, in which the upper limbs postures alternate with FSP, BSP, BRP, and PRP successively. Meanwhile, BB and TB exhibit alternating coordinate relaxation and contraction. During swing, BB gradually contracts to achieve forward swing of upper limbs in FSP; slow MUs are activated, and the recruitment strength of synergy 2 and synergy 3 with lower-frequency range reach a peak. However, TB presents some time delay in crawling movement and kept extension/relaxation in FSP, and then begin contraction to swing arm backward with fast developing of high-, medium-, and low-frequency oscillations, and medium- and low-frequency oscillations reached their peak activations. To perform backward swing, BB extends in BSP as slow MUs are de-recruited, and the activation of high-frequency oscillations exceeded the medium- and low-frequency ones. During stance, both BB and TB are activated to response loading period, and fast MUs are dominantly recruited accordingly to absorb the strike shock and quickly stabilize the kinematic behavior of the joint. As shown in Figure Motor dysfunction of cerebral palsy originates from brain injury leading to a series of neurological changes, such as reduced input to the CNS  and decrIn addition to the aforementioned insufficient activation of low- or medium-frequency sEMG oscillations, it also can be observed that motor dysfunction of CP is unable to de-recruit those undesired sEMG oscillations. As shown in Figures The regulation of motor function by the CNS is a synergistic organization of multiple function units, which has been widely confirmed in muscle groups. Variety of methods have been used to evaluate the intensity, spectrum or frequency component of sEMG activity. However, it is still difficult to analyze the organization patterns of different types of MUs. Multi-scale oscillation modes in sEMG signals are a combination of MU activation and organization patterns. The results of this study demonstrated that the synergistic organization of different oscillations in sEMG signals can be used to evaluate the organization of MUs. In fact, sEMG frequency components are related to physiological state and have been applied to assess motor function under different conditions , 13, 14.The results of this study showed that three stable multi-scale oscillation synergies might be underlying intrinsic structure of EMG activity during crawling. The coefficient curves can further reveal the abnormal MU activation patterns during crawling in CP. Some researchers have found that motor dysfunction of CP manifested as abnormal entropy of multi-scale oscillations of sEMG activities in CP, and a major peripheral cause of these abnormalities is abnormal MU recruitment , 16. ThiThis is the first time to adopt the synergistic mechanism of motor function to characterize the recruitment pattern of sEMG oscillations. The present results reveal that, the myoelectric activities of a muscle can be manifested as sEMG oscillation synergies with different frequency ranges, and motor dysfunction of CP degrade the synergistic recruitment of sEMG oscillations due to the impaired CNS regulation and destroyed MU/muscle fiber. Our preliminary work suggests that, the synergistic organization for motor control can be manifested rather than muscle group, there are oscillation synergies in sEMG signals. Also, the time-varying coefficient curve of sEMG oscillation synergies is a potential index to evaluate the abnormal recruitment of different types of MUs affected by CP disorders. In future work, we would further investigate the sEMG oscillation synergies in other muscles of upper and lower limbs, and the body size of test sample should be enlarged to verify the influence of CP on the synergistic recruitment of sEMG oscillations.This study is under the approval of children's hospital of Chongqing medical university, and all the tests are conducted in the department of rehabilitation center, children's hospital of Chongqing medical university.ZG analyzed the data and signals. ZG, LC, and WH drafted and revised the work. XW, NX, WJ, and WH interpreted the data. ZG, QX, and YL collected the data. XW and WH proposed the research topic. WH organized the data collection, signal processing, and manuscript draft.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD) can only be confirmed by abnormal protease-resistant prion protein accumulation in post-mortem brain tissue. The relationships between sCJD and cerebrospinal fluid (CSF) proteins such as 14–3-3, tau, and α-synuclein (a-syn) have been investigated for their potential value in pre-mortem diagnosis. Recently, deep-learning (DL) methods have attracted attention in neurodegenerative disease research. We established DL-aided pre-mortem diagnostic methods for CJD using multiple CSF biomarkers to improve their discriminatory sensitivity and specificity. Enzyme-linked immunosorbent assays were performed on phospho-tau (p-tau), total-tau (t-tau), a-syn, and β-amyloid (1–42), and western blot analysis was performed for 14–3-3 protein from CSF samples of 49 sCJD and 256 non-CJD Korean patients, respectively. The deep neural network structure comprised one input, five hidden, and one output layers, with 20, 40, 30, 20 and 12 hidden unit numbers per hidden layer, respectively. The best performing DL model demonstrated 90.38% accuracy, 83.33% sensitivity, and 92.5% specificity for the three-protein combination of t-tau, p-tau, and a-syn, and all other patients in a separate CSF set (n = 15) with other neuronal diseases were correctly predicted to not have CJD. Thus, DL-aided pre-mortem diagnosis may provide a suitable tool for discriminating CJD patients from non-CJD patients. Sc), thus affecting the central nervous system [Creutzfeldt-Jakob disease (CJD) is the most common human prion disease, which is characterized by the abnormal accumulation of misfolded prion protein  assay, which is a prion protein conversion assay that allows for the detection of the abnormal amyloid form of PrP, and has been reported to exhibit high sensitivity and specificity for sCJD in the range of 76.5–97% and 99–100%, respectively –23.Machine learning (ML) and deep learning (DL), which are subfields of AI, are powerful tools for extracting patterns and characteristics from big data using neural networks –26. In cThe aims of the present study were to establish a pre-mortem diagnostic method using a DL approach, which would (1) facilitate diagnostic decision making for CJD, (2) improve accuracy compared to conventional pre-mortem diagnostic methods using CSF protein markers, and (3) help to identify more CJD-related CSF biomarkers as landmarks. We then tested the ability of the established DL technique to discriminate CJD patients from non-CJD patients based on detection levels of the key CSF biomarkers 14–3-3, a-syn, amyloid beta (Aβ), t-tau, and p-tau.We collected CSF samples from 49 patients with sCJD (5 definite and 44 probable) and 11 with possible sCJD, and 256 non-CJD patients  ascertained through routine surveillance by the Korea National Institute of Health (KNIH) according to diagnostic criteria . SequencThis study was approved by the Institutional Review Board (IRB) of the Korea Centers for Disease Control and Prevention (IRB No. 2017–03-09-C-A), and all the experiments were performed in accordance with relevant guidelines of the IRB. Written informed consent was obtained from the patients or their legal guardians.The 14–3-3 protein levels in the CSF samples from the patients were determined by western blot analysis as previously described . QuantitTo standardize the quantitative data of protein levels for the different candidate biomarkers, a positive band of 14–3-3 protein in the western blot was given a score of 2, whereas a negative or weakly positive finding was given a score of 1. When the a-syn or Aβ concentration was below the detection limit of the ELISA kits , the case was given a score of 1.To resolve the detrimental effect of imbalanced data on the performance of DL algorithms, we adopted an ‘oversampling’ approach –38. Overhttp://keras.io) neural network library and the TensorFlow (https://www.tensorflow.org) software library were used for deep neural network (DNN) construction. Specifically, we used a multi-layer feed-forward artificial neural network with the standard back-propagation algorithm to perform binary classification [ML analysis was performed using Waikato Environment for Knowledge Analysis 3.8.2 (WEKA) . Evaluatfication ,41. For The best DNN structure consisted of one input, five hidden, and one output layers, with 20, 40, 30, 20 and 12 hidden unit numbers of each hidden layer, respectively. Ultimately, two DNNs were used to discriminate between CJD and non-CJD patients. All of the layers were subjected to a kernel initializer with the ‘random_normal’ option for normalization of each layer. ReLu ,43 was uAccuracy = (TP + TN)/(TP + TN + FP + FN)Sensitivity = TP/(TP + FN)Specificity = TN/(TN + FP)The performance of the ML and DL was evaluated according to the quantitative parameters of the true positive (TP), true negative (TN), false positive (FP), and false negative (FN) rates, which were then used to calculate the accuracy, sensitivity, and specificity according to the following equations:The area under the receiver operating characteristic curve (AUC) was calculated to determine the best model.Cross-validation estimation was performed using the oversampled dataset which used in ML and DL analysis to determine the predictive performance of the model and for tuning hyper-parameters as described previously ,48. In bThe concentrations of six CSF markers  in 5 definite, 44 probable, 11 possible CJD patients, and 256 non-CJD patients, which were determined using ELISA and western blotting, are summarized in Supplementary Table 1. A correlation heat map among the six biomarkers and sCJD patients, except for patients with possible CJD and non-CJD patients, is presented in The highest diagnostic specificity in non-CJD patients was 81.6% using t-tau, and in neuronal diseases patients was 93.33% using a-syn level or t-tau combination test with p/t-tau ratio. The diagnostic sensitivity in possible CJD patients using the a-syn protein was lower than that of other proteins in these patients. The concentration of t-tau, p-tau and a-syn of the test set_B are described in Supplementary Table 1.The performance of each classifier is described in To improve the discrimination and identify potential ‘landmark CSF markers’ for discriminating between CJD and non-CJD patients, the structure of the best-performing model described above was used for analysis with two- or three-variable combinations. As shown in At present, sCJD can only be diagnosed with certainty after a patient is deceased, based on histological examination of the brain tissue. Analysis of protein biomarkers related to CJD has proven to be a potentially useful alternative pre-mortem diagnosis method. The 14–3-3 protein has been reported to be a biomarker for rapid progressive neurodegenerative disorders, including CJD. In our data, analysis for CSF 14–3-3 revealed a dependency on age; the sensitivity was higher in definite and probable sCJD cases than in possible sCJD cases. However, the sensitivity and specificity of CSF 14–3-3 in sCJD cases were found to be lower than those reported previously ,52 but wThe specificities of tau and a-syn analysis in neuronal disease patients, which were used as test set_B, were higher (86.67%–93.33%) than these values in the non-CJD group (74.61%–80.86%). The possibility of misdiagnosis due to similarities of symptoms could not be excluded in some cases in the non-CJD group. However, the protein concentration patterns of the non-CJD group significantly differed from those of the sCJD cases.Here, we performed ML and DL-based analysis using combination of CSF markers as a pre-mortem diagnostic method. Our initial ML and DL model had an imbalanced learning problem owing to the lower number of CSF samples from CJD patients than that from non-CJD patients, which would result in a dominant influence of the major group on the analysis. We chose to use an oversampling method rather than an under-sampling method to resolve this imbalance and avoid losing information on the larger group (non-CJD) after drastic reduction to balance the ratio between the numbers of sCJD and non-CJD cases. In particular, an ensemble of DNNs using ELISA data of t-tau, p-tau, and a-syn outperformed  the diagnostic performance of diagnostic performance of any single CSF marker described in Sc in CSF samples directly, showing high diagnostic specificity [Sc concentration in each CSF sample. Thus, cases in which the PrPSc concentration in a CSF sample is below the detection limit of the RT-QuIC assay, the DL-aided discrimination method could be an alternative pre-mortem CJD diagnosis method.RT-QuIC analysis has been used to detect PrPcificity ,21,56. HDespite the good performances of the models developed in this study, the discrimination between CJD and non-CJD patients was not completely accurate. We consider the following limitations of the proposed method that may have contributed to this result. First, noise among samples might have been derived from misdiagnosis for cases in which the symptoms of CJD are misinterpreted, since they are similar to those of other neurodegenerative disorders ,58. SecoAlthough the DL-aided discrimination model warrants further improvement in performance and classification accuracy using stacked sample sizes via further ELISA data collection and/or extended analysis with other biomarkers for use as a pre-mortem diagnostic method, the DL-based model has several advantages for clinical application. First, it can easily handle large amounts of medical data. Second, CJD and non-CJD patients can be discriminated rapidly (within one or two days). Third, the results can be obtained consistently and reproducibly without requiring a specialist to conduct the laboratory tests. Overall, our findings could help to facilitate clinical decision-making.


Triticeae tribe that provide essential grains for the human diet. Investigation of the genes and alleles that underpin domestication‐related traits has provided valuable insights into the molecular regulation of inflorescence development of the Triticeae, and further investigation of modified forms of architecture are proving to be equally fruitful. The identified genes are involved in diverse biological processes, including transcriptional regulation, hormone biosynthesis and metabolism, post‐transcriptional and post‐translational regulation, which alter inflorescence architecture by modifying the development and fertility of lateral organs, called spikelets and florets. Recent advances in sequencing capabilities and the generation of mutant populations are accelerating the identification of genes that influence inflorescence development, which is important given that genetic variation for this trait promises to be a valuable resource for optimizing grain production. This review assesses recent advances in our understanding of the genes controlling inflorescence development in wheat and barley, with the aim of highlighting the importance of improvements in developmental biology for optimizing the agronomic performance of staple crop plants.Modifications of inflorescence architecture have been crucial for the successful domestication of wheat and barley, which are central members of the  Triticeae tribe, including the staple crops of wheat and barley. We focus on the key domestication related traits, and recent studies that have used modified forms of inflorescence architecture to identify genes regulating spikelet and floret development.© 2018 Institute of Botany, Chinese Academy of SciencesThis review summarizes the recent advances on the genetic regulation of inflorescence architecture in the  Scott A. BodenEdited by: Thorsten Schnurbusch, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), GermanyTriticeae tribe, which includes the important cereals bread wheat (Triticum aestivum), durum wheat (T. turgidum), barley (Hordeum vulgare) and rye , provides a significant proportion of global nutrition. The grains of these important crops are produced on a structure called the inflorescence   leading to extreme suppression of lateral spikelet fertility caused by a missense mutation that is predicted to prolong VRS1 protein function through later stages of inflorescence development  domain transcription factor   with TB1 homologues in wheat, maize, rice, and Brachypodium distachyon shows that the Int‐c.a allele is less evolutionarily conserved than the int‐c.b allele, suggesting that six‐rowed barley contains a deleterious Vrs5/Int‐c allele with reduced function  biosynthesis genes, which is thought to contribute to the delay in inflorescence development observed in vrs2 mutants  from the grain, relative to the non‐free‐threshing ancestral wheat lines, including emmer (T. dicoccoides Körn.) and einkorn (T. boeoticum Boiss.) that carry the q allele. The Q allele also prevents grain loss that occurs in emmer and einkorn due to brittle inflorescences that shatter into spikelets at maturity  binding site. The effects of the Q gene are dosage dependent, with increased transcript levels being associated with corresponding levels of inflorescence compactness and reduced plant height , in combination with yeast two hybrid screen and a firefly luciferase complementation imaging assay, showed that Q protein is likely to function as a transcriptional co‐repressor in partnership with TaTPL  gene has demonstrated that its activity has a major impact on inflorescence density, with Zeo1.b plants having inflorescences twice as dense as wild‐type plants. The responsible genomic region was narrowed to a gene encoding a transcription factor with two AP2 DNA‐binding domains, in addition to a miR172‐binding site, and was therefore named as HvAP2. The mutation in HvAP2 that increased density of the inflorescence was concluded to be in the miR172 binding site, which reduced the cleavage efficiency of HvAP2. Interestingly, the authors showed that miR172 appears to function predominantly during the early stages of inflorescence development, but not in the later developmental stages, indicating a critical role during the transition from spikelet formation to awn initiation and internode elongation  transcription factor, which is homologous to the FRIZZY PANICLE (FZP) and BRANCED SILKLESS (Bd1) genes of rice and maize, respectively  and COMPOSITUM 2 (COM2) genes of tetraploid wheat and barley mutants, respectively, facilitate development of inflorescence‐like structures at rachis nodes where a spikelet typically forms, suggesting that BH1 and COM2 function is required for the axillary meristems to obtain a spikelet identity  , which is a pseudo‐response regulator that regulates photoperiod responsive flowering pathways in wheat and barley , which is a central integrator of flowering that promotes flowering under inductive photoperiods by activating expression of meristem identity genes within the shoot apical meristem  acts downstream of Ppd‐1 to influence spikelet number, with loss of FT‐B1 resulting in increased spikelet number, in a thermally‐responsive manner  function in wheat, which facilitates paired spikelet development, in a dosage dependent manner, by interacting with FT1 and reducing FT1‐dependent activation of spikelet meristem identity genes  extending the period between completion of floret primordia development and initiation of floret degeneration, and (ii) optimizing assimilate distribution to spikelets and florets, which is supported by floret fertility being associated with ovary size at anthesis  and VEGETATIVE TO REPRODUCTIVE TRNASITION2 (VRT2) that are repressed during the transition, and genes including SQUAMOSA PROMOTER BINDING‐LIKE PROTEIN4 (SPL4), KNOTTED1 (KN1) and SUPPRESSOR OF CONSTANS1 (SOC1) that were activated  were also upregulated during the floral transition; interestingly, these genes were among those mis‐expressed in vrs3 and vrs2 mutants , SEP3, PISTILLATA (PI) and APETALA3 (AP3), as well as MADS box transcription factors, including VERNALIZATION1 (VRN1), BM3 and BM8 , and were upregulated in SAMs of barley lines that contain null alleles for EARLY FLOWERING3 , WFZP, LAX PANICLE1 (LAX1) and TERMINAL FLOWER1 (TFL1) as genes whose expression was associated significantly with spikelet number , which encodes the barley DELLA protein that controls GA‐dependent growth responses (Chandler et al. Sln1 revealed amino acids that specifically control size of the shoot apical meristem and the number of florets that form on a barley inflorescence. This illustrates the possibility to improve yield‐related traits by an advanced understanding of gene function (Chandler and Harding Q gene in wheat and VRS1 protein in the deficiens mutant indicates that post‐transcriptional and post‐translational regulation of gene and protein activity plays an important role during inflorescence development, which could be an important area of future research (Debernardi et al. The opportunity to benefit from an improved understanding of protein function has been demonstrated through analysis of Vrs1‐5 genes in barley also presents an opportunity to investigate the broader role of row‐type genes during inflorescence and grain development by combining alleles to make double or triple mutant lines (Zwirek et al. vrs3 allele into the cultivar Morex, which contains the six‐rowed Vrs1 and Vrs5 alleles, improved uniformity of grain size by increasing the width and area of grains produced by the lateral spikelets (Bull et al. Vrs genes and their contribution to key agronomic traits. Similarly, comparative analysis of the transcriptome data from the vrs mutants may help identify downstream genes that are commonly affected by the six‐rowed alleles, which may help uncover more about the molecular regulation of spikelet architecture (Bull et al. Identification of the Vrs5/TB1 facilitates development of the lateral spikelets, whereas in wheat, increased dosage of TB1 promotes formation of secondary spikelets, which could be interpreted to mean that Vrs5/TB1 suppresses axillary spikelet development in barley but promotes more elaborate branching in wheat (Ramsay et al. Vrs5/TB1 promotes meristem dormancy, which influences the transition of meristem determinacy and outgrowth of lateral organs. In this scenario, an increased dosage of TB1 in wheat suppresses the transition of a lateral branch meristem into a spikelet meristem to facilitate development of a short branch composed of two spikelets, whereas in barley, reduced function of Vrs5/TB1 disrupts the dormancy of the lateral spikelet primordia to facilitate development and growth of fertile lateral spikelets.The genetic relatedness of wheat and barley, in combination with the altered inflorescence and spikelet meristem determinacy of these two species, provides a unique opportunity to determine the genes and biological processes that contribute to the diverse inflorescence architecture of cereals. For example, in barley, reduced function of Vrs1 and HOX2, will advance our understanding of the genetic regulation of inflorescence development within each species, while also contributing to our knowledge about the biological processes that contribute to the diverse architectures of wheat and barley (Komatsuda et al. Vrs4 as a homologue of RAMOSA2, which has a well‐characterized role in regulating inflorescence architecture in maize (Bortiri et al. Similar comparisons of reciprocal gene function in wheat and barley, such as Triticeae. This research is now being extended to investigate the genetic basis of modified inflorescence architectures, and further research that uses new genomic and mutant resources promises to provide valuable insights into the genes that control spikelet and floret development. Continued investigation of the genetic regulation of inflorescence architecture in the Triticeae promises to be a rich area of research to pursue fundamental knowledge about plant reproductive development, while also providing valuable insights that can be used by breeders to optimize key yield‐related traits for increased grain production in wheat and barley.In conclusion, analysis of the genes that underpin key domestication‐related traits of inflorescence architecture in barley and wheat has contributed significantly to our understanding of the molecular processes that regulate inflorescence development in the


Gait disturbances are typical of persons with idiopathic normal pressure hydrocephalus (iNPH) without signs distinctive from other neurodegenerative and vascular conditions. Cerebrospinal fluid tap-test (CSF-TT) is expected to improve the motor performance of iNPH patients and is a prognostic indicator in their surgical management. This observational prospective study aims to determine which spatio-temporal gait parameter(s), measured during instrumented motor tests, and clinical scale(s) may provide a relevant contribution in the evaluation of motor performance pre vs. post CSF-TT on iNPH patients with and without important vascular encephalopathy.Seventy-six patients  were assessed before, and 24 and 72 h after the CSF-TT by a timed up and go test (TUG) and an 18 m walking test (18 mW) instrumented using inertial sensors. Tinetti Gait, Tinetti Balance, Gait Status Scale, and Grading Scale were fulfilled before and 72 h after the CSF-TT. Stride length, cadence and total time were selected as the outcome measures. Statistical models with mixed effects were implemented to determine the relevant contribution to response variables of each quantitative gait parameter and clinical scales.From baseline to 72 h post CSF-TT patients improved significantly by increasing cadence in 18 mW and TUG (on average of 1.7 and 2.4 strides/min respectively) and stride length in 18 mW (on average of 3.1 cm). A significant reduction of gait apraxia was reflected by modifications in double support duration and in coordination index.Tinetti Gait, Tinetti Balance and Gait Status Scale were able to explain part of the variability of response variables not covered by instrumental data, especially in TUG. Grading Scale revealed the highest affinity with TUG total time and cadence when considering clinical scales alone.Patients with iNPH and an associated vascular encephalopathy showed worst performances compared to pure iNPH but without statistical significance. Gait improvement following CSF-TT was comparable in the two groups. Overall these results suggest that, in order to augment CSF-TT accuracy, is key to assess the gait pattern by analyzing the main spatio-temporal parameters and set post evaluation at 72 h.Approved by ethics committee: CE 14131 23/02/2015. Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by chronic ventricular dilation, normal cerebrospinal fluid (CSF) pressure and the triad of symptoms: gait apraxia, urinary incontinence, and cognitive deficits . TreatinStill, the diagnosis of iNPH is complicated due to the considerable variability in its clinical presentation and course. Following current consensus guidelines, iNPH should be diagnosed from clinical history, physical examination, and brain imaging , 4, 5. PThe gait of iNPH patients is usually described as bradykinetic, shuffling, unstable on turning and with reduced walking speed . BesidesSupplementary prognostic tests, e.g., CSF tap-test (CSF-TT), have been used to attain a higher specificity and sensitivity for diagnosing iNPH and for predicting shunt response , 9. The Instrumented gait analysis may conversely be a crucial tool to augment CSF-TT accuracy allowing to objectively assess the improvements through a precise measure of the gait pattern . Among dJust a few studies investigated the effects of CSF-TT through an instrumented gait analysis. Among these, Stolze et al. in a study involving 10 iNPH patients, reported gait speed and stride length as the most responsive parameters in a pre- vs. 24 h post-CSF-TT comparison, whereas cadence and balance remained unaffected . More reGait changes after CSF-TT is a transient phenomenon, but literature does not offer an agreement about when it is the time point where the maximal modification can be expected . SeveralThe aim of this paper was threefold: i) to determine the contribution of gait analysis data obtained using IMUs and clinical scales on assessing pre vs. post-CSF-TT modifications in motor performance, ii) to determine the influence of the association between iNPH and vascular encephalopathy on CSF-TT outcomes, and iii) to evaluate whether CSF-TT effect on gait performance is more relevant after 24 or 72 h.This observational prospective study was conducted between May 2015 to May 2018 in the Institute of Neurological Sciences (IRCCS) of Bologna, a national referral neurological and neurosurgical inpatient facility. Population eligible for inclusion in the study consisted of subjects: i) aged over 50 years old, ii) presenting at least one of the symptoms of the iNPH clinical triad , and iiiWhite matter changes were quantified on neuroimages with the Age-Related White Matters Changes (ARWMC) scale . In thisThis study was approved by the local ethics committee of the health service of Bologna, reference CE 14131 23/02/2015, and was conducted in agreement with principles of good clinical practice. All participants gave their written consent to participation according to the declaration of Helsinki.The CSF-TT consisted in the removal of 30–40 ml of CSF using a 20-gauge spinal needle in lateral supine position.Gait was assessed by TUG being the standard motor test in studies involving iNPH patients to assess balance and mobility , and by The TUG and 18 mW were instrumented using mGAIT . In particular, three inertial sensors equipped with a triaxial accelerometer  and a triaxial gyroscope  and with a sampling rate of 100 Hz were wore two on the shoes and one on the lower trunk . The senGait data were processed in real-time. At the end of tests the app provided the following parameters for analysis: i) test total time, ii) gait speed, iii) stride length, iv) cadence, v) phases of the gait cycle , vi) phase coordination index (PCI) as a measure of gait coordination . The truAt baseline and T72 h the following clinical scales were fulfilled: 1) Grading Scale, 2) Tinetti, 3) Gait Status Scale. For Grading Scale and Gait Status Scale, higher scores indicate more impaired motor abilities. Tinetti consists of: i) a balance section , assessing 9 items scored out of 16 points, ii) a gait section (Tinetti Gait), assessing 8 items scored out of 12 points, and iii) a combined score (Tinetti) of 28 points as a result of the sum of the previous two. Higher scores mean less impaired motor abilities.Following what observed by Hollman et al. , in ordeWith the goal of reducing measurement error, averaging of repeated measurements is common practice when analyzing outcomes in clinical research. However this procedure also removes useful information . Furtherhttps://www.r-project.org/). Backward elimination is a stepwise procedure that consists in including all the candidate variables to fit the statistical model and that, at each step, deletes the regressor (if any) whose loss gives most statistically insignificant deterioration to the fit of the reduced model, until no further variables can be deleted without a statistically significant loss of fit. Eq. 1 reports the complete model from which started the analysis of spatio-temporal gait parameters as regressors to the three response variables:In this study, linear models with mixed effects were implemented using backward elimination for each of the three main responsive variables using R  on the i-th subject; β0 is the constant term, β1Ti is the term that models the trend of PerformanceMeasure along the three time points t. This model also includes an occasional-specific random intercept for each subject bit0, that takes into account possible correlations among the three test repetitions on same t.In order to evaluate the contribution of clinical scales in addition to gait analysis parameters, to the three models reported in Eq. 1, the scores of Gait Status Scale, Tinetti Balance, Tinetti Gait, Tinetti, and Grading Scale were added, and the ones relative to T24 h were removed (Eq. 2). Proceeding likewise for Eq. 1, final fitting of the regression models was carried with backward elimination.Equation 2: Complete linear model with mixed effects used to determine effect of CSF during instrumented TUG and 18 mW using spatio-temporal gait parameters and clinical scales scores as regressorsSubscripts apply as in Eq. 1.Finally, with the aim of analyzing the behavior of clinical rating scales alone with respect to responsive variables, a linear mixed model was realized using scores of clinical scales as the only predictors (Eq. 3).Equation 3: Complete linear model with mixed effects used to determine effect of CSF-TT using clinical scales scores as regressorsSubscripts apply as in Eq. 1.The contribution of each term on the right side of the three former equations, in the attempt to explain the variance of the three responsive variables on the left side, has been processed by the linear mixed models and eliminated just in case the deterioration to the fit of the reduced model was statistically insignificant.Among the 151 persons with suspicion of iNPH referred at IRCCS Institute, 76 patients received a diagnosis of iNPH. Fifty-six were p-iNPH forms whereas 20 were v-iNPH. Table 2) and 20 v-iNPH (mean age (standard deviation): 76.7 (3.1) years; BMI: 25.1 (4.0) kg/m2). These groups differed significantly in terms of mean age  and mean BMI ; age and BMI were therefore included in the regression model to study their possible differential effect on performance (Eq. 1).Patients unable to walk at baseline were excluded from the following analyses. Final dataset consisted of 45 p-iNPH (mean age (standard deviation): 73.9 (5.0) years; BMI: 28.1 (3.8) kg/mA total of 585 trials were acquired using mGAIT. Few of these trials were not completed either because patients lost focus on the task to accomplish or because they were too demanding from the physical point of view and were excluded from following analysis Table . Three hp < 0.01) and T72 h (p < 0.001), for total time just at T72 h (p < 0.05), whereas stride length modifications were statistically not relevant. The 18 mW revealed both for stride length and cadence an improvement at T24 h  and at T72 h (p < 0.05 in both cases), however total time never showed the time effect as significant. Belonging to p-iNPH or v-iNPH did not provide a relevant contribution to explain any of the outcome measures. However, values obtained disclosed on average a decreased performance of v-iNPH subjects compared to p-iNPH subjects, with a trend towards significance in 18 mW where v-iNPH showed on average an increase of 2 s on test total time.Table p < 0.001) across the two motor tests, where to its unitary increment corresponded an average decrease of stride length (of 1.6 cm in TUG and 1.9 cm in 18 mW), and cadence (of 0.3 in TUG and 0.4 strides/min in 18 mW) and, on average, an increase of total time (of 0.6 s in TUG and 1.2 s in 18 mW). The time to complete TUG was also explained by duration of sit-to-stand and stand-to-sit phases. As well, the 18 mW was predicted both by the duration of double support and PCI.The change in stride length, cadence and total time measured with TUG, other than pre vs. post comparison, was mostly predicted by the reduction of the duration of double support, the number of turning steps, and the value of PCI. In particular, double support duration showed a high statistical significance  when the inter-subject variability alone is considered (Table p > 0.3) showing how overall variability at baseline, T24 h and T72 h did not differ. Also on 18 mW homoscedasticity is present along time for cadence but not for stride length and total time, testifying how from baseline to T72 h the variability changed. Finally, considering the time-subject interaction the homoscedasticity is always present both for TUG and 18 mW except for the outcome total time in TUG (p < 0.05).The homoscedasticity of random effects is never present p < 0.00 when theThe clinical scales were fulfilled on 56 p-INPH and 20 v-iNPH patients. However, in few cases patients were not able to perform clinical test tasks; Table Table Considering the results of TUG, reported in Table When considering cadence in 18 mW results Table , all scap < 0.001).Same considerations as for the model described by Eq. 1 can be applied here. In the interaction time-subject the homoscedasticity is always present both for TUG and 18 mW except for the outcome total time in TUG (The contribution of clinical rating scales alone to explain responsive variables, as detailed in Eq. 3, is reported in Table This observational cohort study is one of the largest monocentric studies carried out so far on idiopathic normal pressure hydrocephalus, a complex and often misdiagnosed syndrome. In this study, out of 151 patients with suspected hydrocephalus from brain imaging and at least one symptom of the classical triad, 76 were diagnosed as iNPH by a clinical multidisciplinary team following a standardized protocol.Motor performance was measured using inertial sensors which allowed to instrument the TUG and the 18 mW tests without affecting the clinical routine. More so, IMUs allowed to measure gait parameters such as the duration of the double support phase and the PCI that are directly related to typical disturbances of iNPH as the presence of magnetic gait and of apraxia. Cadence, stride length and total time, being three main complimentary components of locomotion, were selected as response variables of statistical models implemented to assess modifications caused by CSF-TT, hence to establish and quantify its effect on symptoms improvement. The choice to use a 18 mW allowed the stress the locomotor abilities of patients, but the use of the more standard 10 mW would have allowed a broader opportunity of comparisons with the literature and in future studies might be preferred.Comparing gait analysis results obtained in the TUG test at baseline and post-CSF-TT, on average, as showed in Fig. Considering clinical scores analyzed in addition to instrumental measures as in Eq. 2 (results in Table Tinetti Gait, Tinetti Balance and Gait Status Scale in TUG provided a contribution more relevant with respect to stand-up time and turning steps in total time, and to PCI in stride length and cadence. This result can be probably ascribed to their capability of assessing a broad spectrum of top-down components of the motor repertoire necessary to execute the TUG. On the contrary, Tinetti global score and Grading Scale when analyzed with instrumental data were never selected for model fitting, revealing their inability to unveil undisclosed aspects of performance. Overall, the fact that some clinical scales in the statistical model of Eq. 2 provided a contribution more relevant with respect to gait analysis parameters also suggests that other instrumental data, obtained from inertial sensors or other devices, might be considered in order to fully describe pre vs post-CSF-TT modifications of motor performance just in terms of objective data.Grading Scale on the other hand, in the model with clinical scales alone, was the only scale found significant for cadence and total time in TUG, demonstrating its ability to explain the majority of the variability of these two outcome measures to the detriment of other clinical scales.When analysing the variance of statistical model residuals relative to the interaction between time and subjects, the homoscedasticity is always present except for the total time in TUG Table . This lav-iNPH patients showed on average a reduced performance compared to p-iNPH in all the different observations but without reaching the statistical significance. Contrary to authors expectations, important vascular encephalopathy present in persons with v-iNPH was not a factor causing a different post-CSF-TT course. This result might be partially explained by the fact that the high individual variability modeled with the random intercept captured only part of the variability ascribed to the two iNPH groups. On the other hand, this result suggests that vascular encephalopathy is not a comorbidity limiting the improvement of gait following CSF-TT. In the present study, the ARWMC was dichotomized in order to ease the clinical interpretation of the results. However, including this variable into the statistical models themselves as fixed effect might increase the variance explained and turn out to be a significant predictor of the responsive variables.When comparing different post-CSF-TT assessment times, the better performances were recorded 72 h after the CSF-TT. This finding is clearly visible in the radar plots of Fig. Inertial sensors used to instrument motor tests on iNPH patients allowed to assess changes on performances due to CSF-TT without affecting the clinical routine and unveiling aspects of locomotion and postural transfers not accessible simply using clinical observations or clinical scales. On average, patients improved the performance from baseline to post-CSF-TT particularly increasing cadence in 18 mW and TUG and stride length in 18 mW. More so, the use of data from inertial sensors and mixed effects models allowed to show how the improvement was significant especially in those gait parameters reflecting a decrease in apraxia such as the reduction of double support duration and the increase of coordination.Tinetti Gait, Tinetti Balance and Gait Status Scale were the scales able, better than others, to address part of the variability of response variables not explained by sensor data. Additionally, these scales in TUG provided a contribution more relevant with respect to stand-up time and turning steps in total time, and to PCI in stride length and cadence, showing the capability to assess components of the motor repertoire not appropriately addressed by gait parameters. On the other hand, when considering clinical scales alone, Grading Scale was the scale with highest affinity in explaining TUG total time and cadence.v-iNPH patients compared to p-iNPH showed worst performances in all evaluations but without reaching statistical significance. This comorbidity was not a factor causing a different post-CSF-TT course by limiting gait improvement.Maximal increase in outcome measures occurred the third day after the CSF-TT, revealing how this interval should be the considered as the best spot to assess CSF-TT efficacy in iNPH.In conclusion, the results obtained in this study suggest that it is possible to improve the assessment of effectiveness of the CSF-TT by including the instrumented evaluation of spatio-temporal gait parameters and setting the time for post-CSF-TT evaluation at 72 h.


Background: CSF protein concentrations vary greatly among individuals. Accounting for brain volume may lower the variance and increase the diagnostic value of CSF protein concentrations.Objective: To determine the relation between CSF protein concentrations and brain volume.Methods: Brain volumes  derived from brain MRI and CSF protein concentrations  of 29 control patients and 497 patients with clinically isolated syndrome or multiple sclerosis were studied.Finding: We found significant positive correlations of CSF protein concentrations with intracranial, gray matter, and white matter volumes. None of the correlations remained significant after correction for age and sex.Conclusion: Accounting for brain volume derived from brain MRI is unlikely to improve the diagnostic value of protein concentrations in CSF. Cerebrospinal fluid (CSF) analysis is supportive of the diagnosis of many neurological diseases. CSF protein concentrations constitute a mainstay of CSF analysis. Despite age- and sex-dependent cut-offs –4, consihttp://dbm.neuro.uni-jena.de), an extension of SPM12 software . TIV was estimated by a ‘reverse brain mask method' .The study was approved by the local ethics committee of the medical faculty of the Technical University of Munich. Written informed consent was obtained. We selected patients, who received brain MRI and lumbar puncture, from our in-house database. As a surrogate of a healthy subjects, we firstly reviewed medical records for patients with transient symptoms  but without a severe or chronic neurological disorder. Based on these strict criteria, we could only include 29 adult patients  as control patients (CP). Given this relatively small number, we secondly selected patients with clinically isolated syndrome (CIS) or multiple sclerosis (MS) aged between 18 and 60 years resulting in a group of 497 patients . We chose this population, because the suspicion of MS usually prompts performing both cranial MRI and lumbar puncture in clinical setting. Therefore, we could assemble a relatively homogenous and large group of patients with both MRI and CSF data. This approach seemed justified, since total protein levels are normal in 75 percent of MS patients with mild elevation in the remainder  = 6.99; albumin in mg/L, 318 ± 122 vs. 233 ± 100, t(524) = 8.39; albumin CSF/serum ratio, 6.8 ± 2.4 vs. 5.3 ± 2.4, t(524) = 6.41; all p < 0.001]. As expected . Although CP were significantly younger than CIS/MS patients , none of the CSF protein concentrations significantly differed between the two groups . With regard to brain volumes, we could replicate well-known associations: men had larger TIV than women [independent-samples t-test; 1578 ± 141 vs. 1415 ± 136 ml, t(524) = 12.42, p < 0.001); GM volume negatively correlated with age  every patient in clinical routine and go along with differences in both CSF protein concentration and brain volumes. Therefore, we felt that an association of CSF protein concentration and brain volumes, potentially meaningful in clinical routine, should remain significant after correction for both age and sex.Accordingly, after having failed to demonstrate a relationship of brain volumes and CSF protein concentrations beyond that explained by age and sex in as many as 526 subjects, we conclude that accounting for individual brain volumes is unlikely to considerably decrease the variability of CSF protein concentrations and, hence, to increase their diagnostic value.The study was approved by the local ethics committee of the medical faculty of the Technical University of Munich.AW and MM contributed to the conception and design of the study. AW, SG, VP, TK, JK, CZ, BH, and MM participated in the acquisition and analysis of data. AW and MM contributed to drafting the text or preparing the tables.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.