Forsythia suspensa has generally been used to clear heat and detoxify in traditional Korean and Chinese medicine. Oxaliplatin is a first-line treatment chemotherapeutic agent for advanced colorectal cancer, but it induces peripheral neuropathy as an adverse side effect affecting the treatment regimen and the patient’s quality of life. The present study was conducted to evaluate the neuroprotective effects of an aqueous extract of F. suspensa fruits (EFSF) on oxaliplatin-induced peripheral neuropathy.The dried fruits of The chemical components from EFSF were characterized and quantified using the ultra-high performance liquid chromatography-diode array detector system. The cytotoxicities of anticancer drugs in cancer cells and PC12 cells were assessed by the Ez-Cytox viability assay. To measure the in vitro neurotoxicity, the neurite outgrowth was analyzed in the primary dorsal root ganglion (DRG) cells, and neural PC12 cells that were differentiated with nerve growth factor. To evaluate the in vivo neuroprotective activity, the von Frey test was performed in six-week-old male mice (C57BL/6) receiving EFSF (60–600 mg/kg) in the presence of 20–30 mg/kg cumulative doses of oxaliplatin. Thereafter, the mice were euthanized for immunohistochemical staining analysis with an antibody against PGP9.5.EFSF attenuated the cytotoxic activities of the various anticancer drugs in neural PC12 cells, but did not affect the anticancer activity of oxaliplatin in human cancer cells. Oxaliplatin remarkably induced neurotoxicities including cytotoxicity and the inhibited neurite outgrowth of DRG and neural PC12 cells. However, the co-treatment of EFSF (100 μg/ml) with oxaliplatin completely reversed the oxaliplatin-induced neurotoxicity. Forsythoside A, the major component of EFSF, also exerted remarkable neuroprotective effects against the oxaliplatin-induced neurotoxicity. In addition, EFSF (60–200 mg/kg) significantly alleviated the oxaliplatin-induced mechanical allodynia and loss of intra-epidermal nerve fiber to the levels of the vehicle control in the mouse peripheral neuropathy model.EFSF could be considered a useful herbal medicine for the treatment of peripheral neuropathy in cancer patients receiving chemotherapy with oxaliplatin. Forsythiae suspensa [F. suspensa fruit have protective activities against hepatic injury as well as antibacterial, antiviral, anti-inflammatory, and anti-allergy activities [F. suspensa contains various phytochemicals including phenylethanoid glycosides, lignans, flavonoids, terpenes, and volatile oils [F. suspensa fruit were identified as forsythoside A (FSA), phillyrin and rutin, and their contents were 2.9, 0.205, and 0.16% on average, respectively [, exerted many protective effects such as the anti-inflammatory, antioxidant, antibacterial, antiviral, and anti-allergic effects [F. suspensa fruit exerted neuroprotective effects on rotenone-induced neurotoxicity in PC12 cells as well as in a rotenone-induced neurodegenerative rat model through antioxidant and anti-inflammatory activities, suggesting its application in the treatment of Parkinson’s disease [F. suspensa or FSA on chemotherapy-induced peripheral neuropathy (CIPN) is not known yet.Forsythiae Fructus is listed in the Korean pharmacopoeia as “Yeon-gyo”  and in tsuspensa , 4. It htivities –7. F. suile oils –10. It hectively , 12. The effects –16. Rece disease . HoweverAnticancer drugs such as, taxanes, platinum compounds, vinca alkaloids, and proteasome inhibitors are known to be highly toxic to sensory neurons . CIPN isBecause the mechanisms underlying acute and chronic CIPN are still unclear, there are no agents showing efficacy in the prevention or treatment of CIPN. To date, antidepressants, anticonvulsants and chemoprotectants including amifostine, nimodipine and neurotropin are used for symptomatic management of CIPN. However, many treatments are still in the experimental stage and there are not enough clinical evidences to confirm their efficacy –31. TherF. suspensa fruits (EFSF), this study was conducted and showed that the EFSF exerted a neuroprotective potential against OIPN; in both in vitro neuronal differentiated PC12  cells and in vivo oxaliplatin-induced neuropathic mouse models. Its major component, FSA, also showed a neuroprotective potential against oxaliplatin-induced neurotoxicity in the neural PC12 cells.In our preliminary screening to develop a novel drug that alleviates neurotoxicity, we found effective materials to relieve OIPN from the library of medicinal herb extracts. In order to assess the neuroprotective effect of the aqueous extracts of For ultra-high performance liquid chromatography (UHPLC) analysis, analytical-grade formic acid and UHPLC grade solvents were obtained from Fisher Scientific Ltd. . FSA as an authentic standard chemical (STD) was purchased from ChemFaces , and its chemical purity was > 98% according to the manufacturer’s information sheet. Oxaliplatin, bortezomib and amifostine were purchased from TOCRIS Bioscience , Cell Signaling Technology  and Santa Cruz Biotechnology , respectively. Cisplatin, paclitaxel, docetaxel, and vincristine were purchased from Sigma-Aldrich Co . Recombinant rat nerve growth factor (NGF) and N2 supplement were purchased from R&D systems  and Thermo Fisher Scientific , respectively. A rabbit antibody against PGP9.5 and a goat anti-rabbit IgG Alexa Flour 488-labeled antibody were purchased from Millipore  and Abcam , respectively.F. suspensa were supplied from Kwangmyung-dang Medicinal Herbs Co. , and their morphology was carefully validated by Dr. Goya Choi Herbal Research Specialized Center, Korea Institute of Oriental Medicine (KIOM), Republic of Korea. A voucher specimen (KIOM010016) was deposited in the Clinical Medicine Division of KIOM. The herb materials were extracted as previously described [The dried fruits of escribed . BrieflyR) and specific DAD spectrum pattern of each peak in the EFSF with those of FSA in parallel. The acquired chromatographic data were analyzed by the Agilent OpenLAB CDS software.For a quality control of EFSF, the components of EFSF were analyzed using an UHPLC-diode array detector (DAD) system  equipped with an analytical column  maintained at 30 °C. The EFSF (2 mg/ml) and STD of FSA (0.1 mg/ml) were dissolved in 50% (v/v) methanol in water. The EFSF or STD was separated by using a sequential gradient mobile phase system from 90% of 0.1% formic acid (A) and 10% of acetonitrile (B) to 65% A and 35% B within 40 min at a flow rate of 0.17 ml/min. The eluent signals were monitored with a DAD at 330 nm. Each component from EFSF was verified by comparing the retention time (t# R8820NK) were purchased from Cell Applications, Inc. . PC12, rat adrenal gland pheochromocytoma cells were cultured in a collagen type I-coated culture dish  with DMEM supplemented with 10% horse serum and 5% fetal bovine serum (FBS). According to the manufacture’s instruction, DRG cells were cultured at a density of 2 × 103 cells/well in the Poly-D-Lysine (PDL)-coated 96 well plate with Rat Ganglion Neuron Culture Medium. For neuronal differentiation of the PC12, the cells were plated in a collagen type IV-coated multi-plate (Corning) at the density of 2.5 × 103 cells for a 96 well plate or 1.25 × 104 cells for a 24 well plate. After 24 h, the culture medium was replaced with differentiation medium (DM) consisting DMEM, 100 ng/ml NGF, 1% N2 supplement, and 0.5% FBS, and incubated for 4 days.PC12 (CRL-1721), A549 (CCL-185), and HCT-116 cells (CCL-247) were purchased from the American Type Culture Collection . Rat dorsal root ganglion neurons  with RPMI medium supplemented with 10% FBS. The effect of EFSF on the values of the half maximal inhibitory concentration (IC50) of oxaliplatin was assessed in cancer cells co-treated with oxaliplatin (0–250 μM) and EFSF (0–100 μg/ml) for 48 h, and the IC50 values were determined using the SoftMax Pro 7.0 software  automatically.For the cell viability assay, neural PC12 cells were exposed to the indicated concentrations of EFSF, FSA, each anticancer drug, or a combination of each anticancer drug with EFSF or FSA for 48 h. Amifostine was used as a positive control. Cell viability was assessed using the Ez-Cytox viability assay kit . Human cancer cells, A549 (lung cancer) and HCT-116 (colon cancer) cells were cultured in 96-well plates (5 × 104 cells/well) were cultured in DM with a combination of oxaliplatin (200 nM) and EFSF (0–100 μg/ml), FSA (0–40 μM) or amifostine (0.5 mM). The neurite outgrowth was observed under a phase contrast bright-field inverted microscope . Digitalized morphometric images of the fields containing more than 20 cells were captured and used for the determination of the length and number of neurites per cells. The cells bearing neurite that had at least one neurite with a length longer than the diameter of the cell body were calculated as a percentage of the total of counted cells. Total neurite lengths were measured by tracing the length of the neurites using the MetaMorph image software (Molecular Devices).Neurite outgrowth in PC12 and DRG cells were analyzed as described previously . To inve4 cells) were cultured with growth factor-containing media in the PDL pre-coated Millicell inserts, and treated with the indicated concentrations of EFSF in the presence or absence of oxaliplatin (5 μM). After 7 days of the culture, the cells were fixed with − 20 °C methanol for 20 min at room temperature and then, the neurites were stained with the Neurite Stain Solution for 30 min. The extended neurites on the underside of the insert membrane were visualized using inverted microscope. To extract the stained neurites, cell bodies were removed with cotton swab and then the stain was extracted on Parafilm using Extraction Buffer for 10 min at room temperature. Each extract was transferred to 96 well plate and quantified neurite extension on a multi-plate reader at 562 nm.The neurite outgrowth assay in DRG cells was conducted using the Neurite Outgrowth Assay Kit . Briefly, the DRG cells  of KIOM.Six-week-old male mice (C57BL/6) were supplied by OrientBio, Inc. . During the entire experimental periods, the mice were housed under a specific-pathogen-free laboratory animal care facility , and received food and water ad libitumn = 6) daily received oral administration of 0.5% Na-CMC (OIPN model group), or three doses of 60, 200 or 600 mg/kg EFSF (treatment group) throughout the experimental period, respectively. The neuroprotective effect of EFSF was confirmed by measuring the response rate to mechanical stimuli in another neuropathic animal model. Oxaliplatin (10 mg/kg in 5% dextrose) was i.p. injected into experimental mice once a week, for 2 weeks , and then the animals were divided into 2 groups. Each group (n = 6) received a daily oral administration of EFSF (250 mg/kg) or 0.5% CMC solution for 3 weeks. Forsythiae Fructus has been used at 3–15 g that was a daily dosage for anti-inflammatory and detoxifying treatment [To generate the chronic OIPN model, the mice received an intraperitoneal (i.p.) injection of 5% dextrose solution (vehicle) or oxaliplatin (5 mg/kg in 5% dextrose) twice a week, for 3 weeks . After 3 weeks from the first injection, the vehicle group received a peroral (p.o.) administration of 0.5% Na-carboxymethyl cellulose (CMC) solution throughout the experimental period. To determine the optimal effective dose of EFSF in the behavior test, oxaliplatin-administered mice were randomly divided into 4 groups. Each group  equipped with a von Frey-type 0.5 mm diameter filament. The mechanical stimuli were applied perpendicularly on to the mid-plantar of the hind paw with a gradual increase in the force  until the mouse withdrew its hind paw. The test was performed on both sides of the hind paw and repeated 5 times with an interval of 5 min between each test cycle. The withdrawal threshold force was defined as the force (g), at which the mouse withdrew its paw.To measure the responses rates of the mouse to the external stimuli, a von Frey monofilament with a bending force of 0.16 or 0.4  was applied to the mid-plantar surface of the hind paw, 6 times for 3 s with an interval of 10 s between stimulations. The test was performed in 3 cycles with an interval of 15–20 min between each test cycle. The responses such as rapid and sudden lifting, shaking or licking were counted as a positive response. The response rate was calculated as the percentage of positive responses from a total of 6 trials in each cycle. After the final test, the animals were anesthetized by i.p. injection of a pentobarbital solution (50 mg/kg) followed by transcardinal perfusion of 4% paraformaldehyde (PFA).The hind footpads were removed from the mice and fixed in 4% PFA. The PFA-fixed tissues were embedded in paraffin, sectioned at a 4 μm thickness, and mounted on silane-coated slides . After deparaffinization, intra-epidermal nerve fiber (IENF) was immunostained with a primary rabbit antibody against PGP9.5 (1: 200) at 4 °C overnight. After incubation with the secondary antibody labeled with Alexa Flour 488 for 1 h at room temperature, the slides were covered with a mounting medium . The photographed images under a fluorescence microscope  were analyzed with image software . To quantify the nociceptive IENF density, the numbers of nerve fibers that cross the dermal/epidermal junction were counted from 3 randomly chosen fields for each slide and the length of the epidermis within each field was measured. The density was calculated as the value of the IENF numbers divided by the length (mm) in the intra-epidermis.Statistically significant differences in the averages among the experimental groups were determined by conducting one- or two-way analysis of variance (ANOVA) according to the experimental design. Tukey’s post hoc multiple comparisons test was done to compare the significant differences between the treatment and vehicle groups. All statistical analyses were performed using the SigmaPlot 13.0 software .F. suspensa fruits with 26.1% yield, and its drug extract ratio was 4:1. The components of the EFSF were analyzed using the UHPLC-DAD. To determine the major components of the EFSF, its UHPLC chromatogram was scanned and compared to the STD peak of FSA which has been described as a marker component of Forsythiae Fructus in the Korea and Chinese Pharmacopoeia [R = 11.85, upper) and FSA  was perfectly matched in the chromatograms. Its content was determined as 124.98 ± 0.13 mg/g based on the calibration curve from 0.5 μg/ml to 0.2 mg/ml of the peak area in the STD chromatogram  for a further 48 h. EFSF did not significantly change the cell viability of the neural PC12 cells at a range from 0 to 100 μg/ml, but significantly decreased it at concentrations above 200 μg/ml EFSF  and the total lengths of the neuritis (44.3 ± 8.3%) compared with the untreated vehicle. EFSF significantly attenuated the oxaliplatin-induced neurotoxicity, which was dose-dependent. Moreover, EFSF at dose of 100 μg/ml completely alleviated the oxaliplatin-induced neurotoxicity based on both the number of cells bearing neurites and the total neurite lengths  or amifostine (0.5 mM), and cultured for 72 h in DM. The PC12 cells were differentiated to neural cells which exhibited extensive neurites sprouting out from the cell bodies as seen in the untreated vehicle of Fig. ritis 44. ± 8.3% cTo investigate the effect of the FSA, the major component of EFSF on the viability of neural cells, the PC12 cells were differentiated in DM for 96 h and then, treated with the indicated concentrations of FSA (0–80 μM) for 48 h. FSA alone did not change the viability of the neural PC12 cells at all the tested concentrations  received daily EFSF  or 0.5% (w/v) Na-CMC solution. As shown in Fig. To determine the effective dose of EFSF for the neuroprotective effect in OIPN, mice were administered 5 mg/kg, 6 times over 3 weeks . The mice exhibiting mechanical hypersensitivity in the von Frey test were divided into 4 groups. Each group . There was no body weight change in the EFSF treatment group compared with the oxaliplatin-only treatment group during the experiment Fig. c. The reWe next investigated whether oxaliplatin can reduce the density of innervated nociceptive nerve fibers in the distal foot skin, which is a common lesion related to chemotherapy-induced neuropathies . To asseIn our preliminary screening to find a novel drug for the treatment of CIPN, we found biologically active candidates to relieve CIPN from traditionally used medicinal herb extracts. In the present study, we demonstrated the neuroprotective effects of EFSF on OIPN; EFSF alleviated oxaliplatin-induced neurotoxicity which was observed both in vitro neurotoxicity model using the neural PC12 cells and in vivo OIPN mouse model. In addition, we also found that FSA, a major component of EFSF, could protect the neurotoxicity against oxaliplatin. Taken together, our results suggest that EFSF and FSA are useful for relieving OIPN and could be a possible candidate to develop a new supportive drug for the cancer patients receiving oxaliplatin treatment.To examine whether EFSF can protect against the chemotherapy-induced neurotoxicity, we first performed a cell viability assay with neural PC12 cells after co-treatment with EFSF and anticancer drugs, including oxaliplatin, cisplatin, docetaxel, paclitaxel, vincristine, and bortezomib. All the anticancer drugs tested induced cytotoxicity in the neural PC12 cells; EFSF treatment effectively attenuated the anticancer drug-induced cytotoxicity of neural PC12 cells. Among them, oxaliplatin induced a potent neurotoxicity, showing a remarkable decrease in the cell viability as well as neuronal differentiation of the neural PC12 cells based on the number of cells bearing neurites and the total length of neurites. EFSF attenuated the oxaliplatin-induced neurotoxicity in a dose-dependent manner; a high dose of EFSF (100 μg/ml) could protect almost completely the neural PC12 cells from the oxaliplatin-induced neurotoxicity. Because there is a correlation between accumulation of oxaliplatin in DRG neurons and neurotoxicity, DRG is a primary target of oxaliplatin-mediated peripheral neurotoxicity , 39. In Forsythia viridissima and Forsythia suspensa have been used as Forsythiae Fructus [Forsythia, but the constituents of their dried fruits were different; The major components of Forsythia suspensa fruits were arctiin, matairesinol, and arctigenin, while the major component of Forsythia viridissima fruits was forsythoside A [Forsythia viridissima fruits (EFVF) has neuroprotective effects against OIPN, and its major components arctiin and arctigenin attenuated the oxaliplatin-induced neurotoxicity [F. suspensa could exert neuroprotective effects against OIPN.In traditional Korean medicine, both dried fruits of  Fructus . It has hoside A , 2. In ptoxicity . TherefoF. suspensa has antioxidant and anti-inflammatory properties [F. suspensa or FSA has neuroprotective effects against neurodegenerative diseases such as Parkinson’s disease [Several studies have demonstrated that operties , 40, andoperties , 14. Fur disease , Alzheim disease , learnin disease , and cer disease . Until rOxaliplatin has a very narrow therapeutic window because of the adverse side effects such as peripheral neuropathy and diarrhea , 44. It F. suspensa and its major component, FSA both possess anti-inflammatory and anti-oxidant properties [F. suspensa and FSA against oxaliplatin-induced neurotoxicity, the effect of ESFS or FSA on changes in apoptotic signaling pathways, mitochondrial function, membrane receptors, and release of cytokines and chemokines should be investigated as a further study.The exact mechanisms underlying the development of OIPN are not yet fully understood; however, it seems that alterations in mitochondria, membrane receptors, ion channels, and inflammatory mediators such as cytokines and chemokines leading to neuroinflammation, oxidative stress, mitochondrial dysfunction, and axonal degeneration are likely involved in the pathogenesis of OIPN , 50. Manoperties , 14, it Because adjuvant drugs may affect the antitumor activity of anticancer drugs, in general, the drug-drug interactions between the cancer drug and supportive drug to be co-administered should be evaluated during the development of cancer supportive drugs. The present study showed that EFSF did not have any negative effect on the antitumor activity profiles of oxaliplatin at least in human colorectal (HCT-116) and lung cancer (A549) cells. Therefore, it can be expected that EFSF may exert a neuroprotective effect against OIPN without affecting the anti-tumor effect of oxaliplatin itself. In order to develop EFSF as a therapeutic agent for OIPN, further studies on the precise molecular mechanisms of EFSF underlying the development of OIPN, and on the herb-drug interaction should be preceded.The present study showed that EFSF could alleviate oxaliplatin-induced neurotoxicity in vitro and peripheral neuropathy in vivo suggesting that it could be a starting material to develop a potential functional food ingredient or a supportive drug for managing of cancer patients receiving chemotherapy with oxaliplatin.


Scylla paramamosain) is a euryhaline and commercially important species. MiRNAs participate in the regulation of many physiological activities.The mud crab , glycosaminoglycan degradation (ko00531), and galactose metabolism (ko00052).The miRNA transcriptome of the gills of S. paramamosain regulated osmotic pressure and energy balance by regulating target genes to adapt to a sudden changes in salinity. These results provided a basis for further investigations of miRNA-modulating networks underlying the osmoregulation of S. paramamosain.The online version of this article (10.1186/s12864-018-4981-6) contains supplementary material, which is available to authorized users. Scylla paramamosain (Crustacea: Decapoda: Portunidae: Syclla De Hann) is widely distributed along the coasts of southern China and other Indo-Pacific countries [S. paramamosain is becoming an important farmed fish along the southeast coast of China [S. paramamosain. Previous studies have revealed that crustaceans regulate hemolymph osmotic pressure mainly by adapting to changes in salinity through ion channels [The commercially important mud crab ountries , 43, 47.of China , 28. Mudof China . Salinitof China , 33. Altchannels .Small noncoding ribonucleic acid (snRNA), which include microRNA (miRNA), small interfering RNA (siRNA), and Piwi-associated RNA (piRNA), has been isolated from a wide variety of plant and mammalian cells. snRNA is involved in various biological and cellular processes by targeting specific miRNAs for degradation or translational repression , 21, 48.Oreochromis niloticus [Oncorhynchus mykiss [Cyprinus carpio [Crassostrea gigas [Chlamys farreri [Daphnia magna [Marsupenaeus japonicus [Litopenaeus vannamei [Eriocheir sinensis [S. paramamosain [Portunus trituberculatus [MiRNAs participate in the regulation of many physiological activities , includiiloticus , Oncorhys mykiss , Cyprinus carpio , Crassosea gigas , and Chl farreri . A largeia magna , Marsupeaponicus , Litopenvannamei , Eriochesinensis , S. paramamosain , and Porrculatus , have beS. paramamosain to reveal the adaptive mechanisms in response to sudden salinity drop under normal conditions  and stress conditions caused by a sudden drop in salinity (3‰) [S. paramamosain was examined under normal conditions  and stress conditions caused by a sudden drop in salinity (3‰) in this study. These results provide a basis for further investigations of miRNA-modulation of networks underlying osmoregulation of S. paramamosain.In our previous study, transcriptomic analysis was conducted on the gills (an important organ in osmoregulation of marine crustaceans) of ity (3‰) . The funity (3‰)  allow foA total of 300 randomly selected crabs with an average body weight of ~ 30 g were selected and maintained in a natural water environment with a salinity of 23‰ and a temperature of ~ 20 °C. The crabs were randomly assigned to one of six groups of 50 animals each and housed in six cement pools under identical physical and chemical conditions. The salinity of the seawater for three of the groups was adjusted to 3‰ from 23‰, and then decreased to 20‰. These three groups were defined as the LS  group. The other three groups were defined as the CK groups, where the salinity of seawater was maintained at 23‰. All other conditions were the same as the LS group.According to , there wS. paramamosain gills tissues with TRIzol reagent , as recommended by the manufacturer.Total RNA was extracted from RNA fragments, 18–30 bases in length, were isolated from total RNA extracted from gills of three individual mud crabs as one sample after being separated through 15% denaturing gels to net three samples from each group. Then, sRNAs were excised from the gel and sequentially ligated to 3′- and 5′-adapters. After each ligation step, sRNAs were separated in 15% denaturing gels. The final purified ligation products were reversely transcribed into complementary DNA (cDNA) using reverse transcriptase . The first strand cDNA was PCR amplified using Phusion* DNA polymerase (Finnzymes Oy). The purified DNA fragments were used for clustering and sequencing using the Illumina Hiseq 4000 sequencing system , which was performed by BGI Diagnosis Technology Co., Ltd. .http://rfam.xfam.org//) for annotation. The tags annotated as tRNA, rRNA, small nucleolar RNA (snoRNA), and snRNA were discarded. Considering that there was no available information of the S. paramamosain genome, the remaining small RNA tags were compared to known miRNAs from all metazoan species in the miRBase 21.0 database (http://www.mirbase.org/) to identify conserved miRNAs. Only perfect matches were considered as conserved miRNAs. Tags that were not aligned to the miRBase database were used to predict novel miRNAs. The miREvo evolutionary analysis platform for next-generation sequencing and mirdeep2 software package were used to predict novel miRNAs by exploring the secondary structure, the Dicer cleavage site, and the minimum free energy of the former unannotated small RNA tags that could be mapped to reference sequences. Q_value < 0.001 and |log2 (foldchange) | > 1 were set as thresholds to identify significantly differential expression of miRNAs.Raw data (raw tags) in the FASTQ format were first processed using self-written Perl and Python scripts . In this step, clean data (clean tags) were processed by removing low-quality tags containing ploy-N, with 5′ primer contaminants, without 3′ primers or the insert tag, and with ploy A or T or G or C from the raw data. At the same time, the Q20, Q30, and GC contents of the raw data were calculated. Then, the length of sRNA tags within a certain range from clean tags was determined for downstream analysis. All clean tags were searched against the Rfam database  [https://blast.ncbi.nlm.nih.gov/). Afterward, gene ontology (GO) analysis of the target genes was performed using the Gene Ontology Enrichment Analysis Software Toolkit   were con3501735) , miRandaGOEAST/; ).-ΔΔCT method was employed in the analysis of relative quantification. Significant differences were examined by paired t-test in which p value< 0.01 and p value< 0.01 was considered to be statistically significant.MiRNAs expression levels were assayed by quantitative realtime PCR (qPCR) using a SYBR primescript™ miRNA RT-PCR kit (TaKaRa). Total RNA was isolated from the gills of mud crabs in the LS groups at 120 h after a sudden drop in salinity from 23‰ to 3‰ using RNAiso Plus total RNA extraction reagent (TaKaRa), while total RNA was isolated at 120 h from crabs in the CK groups maintained at a salinity of 23‰. The cDNA was synthesized using the Perfect Real Time version of the PrimerScript™ RT reagent kit with gDNA Eraser  (TaKaRa) according to the manufacturer’s instructions. The 18S rRNA gene was selected as an internal control. Primers used in this study are listed in Table To identify miRNAs of the mud crab in response to a sudden drop in salinity, small RNA libraries derived from the CK and LS groups were constructed and sequenced using the BGIseq-500 Next Generation Sequencing Platform. Raw tags were obtained from the three CK groups and three LS groups, respectively Table . After r_1 was the most accumulated miRNA, with a total of 11,848,942 tags from the CK and LS libraries . While the least abundant miRNA in the two libraries was miR-7 (1157 tags in the CK group and 6374 in the LS group)  of variable abundances. MiR-100-5pS. paramamosain were matched against the miRNAs of Portunus trituberculatus. The salinity regulation -related miRNAs in gills included mir_7 (known), novel_mir1, novel_mir4, and novel_mir8.A total of 43 novel miRNAs were identified in the CK and LS libraries, and displayed unequal expression levels | > 1), indicated that a total of 18 miRNAs were differentially expressed small RNAs (DESs), with 10 miRNAs up-regulated and eight down-regulated (Table 2.Fold_change = 6.542014656) and the most down-regulated miRNA was novel_mir45 (log2 Fold_change = − 6.093703464). Among the 18 miRNAs, the most abundant miRNAs were novel_mir7, novel_mir5, and miR-7 with 87,809, 80,241, and 7531 tags detected between the CK and LS libraries, respectively . Mud crabs are mainly distributed throughout estuary areas with large changes in salinity. During the rainy season, the salinity of farm ponds greatly vary, which can adversely affect the culture of S. paramamosain, resulting in sever economic losses. Because S. paramamosain is a euryhaline species, its sensitivity to sudden changes of salinity is often overlooked. This study preliminarily explored the adaptive mechanism of S. paramamosain to a sudden drop in salinity via changes in miRNA profiles of the gills. It is worth noting that the gills of S. paramamosain in the LS group had adapted to the change in salinity to 3‰ for 120 h.Most crustaceans live in aquatic environments and are very sensitive to chemical changes in water. Changes in water salinity directly affect the growth, survival rate, and reproduction of crustaceans, which are mainly related to changes in osmotic pressure and ion concentrations in body fluids. Artificial breeding environment restrictions  and desalinization will lead to environmental salinity-induced stress. A rapid change in salinity due to heavy rainfall and mass water exchange will cause acute stress, while long-term decrease in salinity of an estuary can cause chronic stress, although crustaceans can adapt to such low-salt environments. Most euryhaline crustaceans can maintain internal homeostasis. The internal balance mechanisms (compensatory reactions) of euryhaline crustaceans can maintain homeostasis in response to a sudden change in salinity. This process can be simplified as a change from “stress” to “adaptation” without “failure.” However, high-intensity salinity stress may result in serious adverse reactions of crustaceans, including reduced production, morbidity, or even death. S. paramamosain was altered to equilibrate changes in exoteric osmotic pressure. Besides, we also identified pathways closely associated with energy metabolism, such as starch and sucrose metabolism (ko00500), glycosaminoglycan degradation (ko00531), and galactose metabolism (ko00052), among others  and in response to a sudden drop in salinity (3‰). The results of this study identified seven known miRNAs and 43 novel miRNAs, with 18 DESs . A total of 14,951 DESs of target genes were obtained by miRNA target gene prediction. GO functional classification of differentially expressed miRNAs target genes that were the most strongly affected in the gills of S. paramamosain in response to a sudden drop in salinity from 23‰ to 3‰ indicated that 578 genes were associated with cellular processes, 523 with metabolic processes, and 422 with single-organism processes. KEGG pathway analysis of differentially expressed miRNAs target genes showed that most of the identified pathways were associated with metabolism, including 14 pathways related to amino acid metabolism, which plays an important role in osmoregulation. Besides, several pathways were associated with energy metabolism, such as starch and sucrose metabolism (ko00500), glycosaminoglycan degradation (ko00531), and galactose metabolism (ko00052), among others. The above pathways reveal that S. paramamosain regulates osmotic pressure and energy balance by regulating target genes to adapt to a sudden change in salinity from 23‰ to 3‰. This article for the first time preliminarily studied the adaptation mechanisms of S. paramamosain to a sudden drop in salinity. Furthermore, some novel miRNAs were discovered, which paves the way for further in-depth exploration on salinity adaptation of S. paramamosain.Although Additional file 1:Table S1. Differentially expressed miRNAs. Table S2. Gene expression of 18 miRNAs for the comparison of CK and LS groups according to qPCR analysis. Table S3. KEGG pathway annotation and classification. (DOCX 60 kb)


Chronic Obstructive Pulmonary Disease (COPD) is a progressive disease. Preventing deterioration of health status is therefore an important therapy goal.  Clinically Important Differences ((M)CIDs) are used to interpret changes observed. It remains unclear whether (M)CIDs are similar for both deterioration and improvement in health status. This study investigates and compares these clinical thresholds for three widely-used questionnaires.Data were retrospectively analysed from an inhouse 3-week pulmonary rehabilitation (PR) randomised controlled trial in the German Klinik Bad Reichenhall (study 1), and observational research in Dutch primary and secondary routine clinical practice (RCP) (study 2).Patients with COPD aged ≥18 years (study 1) and aged ≥40 years (study 2) without respiratory comorbidities were included for analysis.The COPD Assessment Test (CAT), Clinical COPD Questionnaire (CCQ) and St George’s Respiratory Questionnaire (SGRQ) were completed at baseline and at 3, 6 and 12 months. A Global Rating of Change scale was added at follow-up. Anchor-based and distribution-based methods were used to determine clinically relevant thresholds.In total, 451 patients were included from PR and 207 from RCP. MCIDs for deterioration ranged from 1.30 to 4.21 (CAT), from 0.19 to 0.66 (CCQ), and from 2.75 to 7.53 (SGRQ). MCIDs for improvement ranged from −3.78 to −1.53 (CAT), from −0.50 to −0.19 (CCQ), and from −9.20 to −2.76 (SGRQ). Thresholds for moderate improvement versus deterioration ranged from −5.02 to −3.29 vs 3.89 to 8.14 (CAT), from −0.90 to −0.72 vs 0.42 to 1.23 (CCQ), and from −15.85 to −13.63 vs 7.46 to 9.30 (SGRQ).MCID ranges for improvement and deterioration on the CAT, CCQ and SGRQ were somewhat similar. However, estimates for moderate and large change varied and were inconsistent. Thresholds differed between study settings.Routine Inspiratory Muscle Training within COPD Rehabilitation trial: #DRKS00004609; MCID study: #UMCG201500447. Our study is the first dedicated investigation of  clinically important differences ((M)CIDs) for deterioration on chronic obstructive pulmonary disease (COPD) health status tools in comparison with thresholds for improvement.Our study used a combination of anchor-based and distribution-based methods to determine clinically relevant thresholds for both deterioration and improvement.Our study investigated clinically relevant thresholds in two different study settings—pulmonary rehabilitation (PR) and routine clinical practice (RCP)—by using data from various follow-up periods to minimise the possible impact of the recall period.Our study included a limited number of patients with deterioration after PR and during RCP, and a limited number of patients indicating moderate and large change in health status.Our study resulted in broad ranges and wide CIs for (M)CIDs of COPD health status tools, requiring possibly larger sample sizes for more accuracy.The use of health status questionnaires is recommended by the Global initiative for Chronic Obstructive Lung Disease (GOLD) for the assessment, evaluation and management of patients with chronic obstructive pulmonary disease (COPD).‘the smallest difference in score, which patients perceive as beneficial and which would mandate a change in the patient’s management’.Various studies have examined clinically relevant thresholds for change on the CAT, CCQ and SGRQ in order to be able to evaluate and interpret treatment effects.Most clinical studies that determine the MCID of patient-reported outcomes (PROs) are executed in the context of an intervention such as pharmacotherapy or pulmonary rehabilitation (PR). This usually results in an improvement in the patients’ health-related quality of life (HRQoL). MCIDs for improvement have thus been investigated; however, there is a lack of evidence for the MCIDs for deterioration.In COPD health status, the estimated MCID for the CAT score is 2.00–3.00 units,This study was a retrospective analysis of data obtained from two prospective clinical trials. Study 1 was a secondary analysis of a subsample from the Routine Inspiratory Muscle Training within COPD Rehabilitation (RIMTCORE) real-life randomised controlled trial in the Klinik Bad Reichenhall, Center for Rehabilitation, Pulmonology and Orthopedics in Germany.Study 2 (MCID study) was an observational trial of patients with COPD GOLD I–IV aged ≥40 years without other respiratory comorbidities or alpha-1-antitrypsin deficiency. Patients were recruited from Dutch primary and secondary RCP between September 2015 and September 2016. Patients were approached via multiple general practices, hospitals and the Dutch patient lung federation.In both studies, patients and the public have not actively been involved during the design of the study nor in the assessment of the burden. Summary results are disseminated to participating patients after completion.Patients in study 1 participated in an intensive, 3-week, full-day inpatient PR programme tailored to the patient’s individual needs. Details have been presented previously.The primary outcomes selected from both prospective studies for this retrospective analysis were the CAT , CCQ (weekly version) and SGRQ (monthly version). In study 1, these questionnaires were collected at baseline, at PR discharge and during follow-up at 3, 6, 9 and 12 months. Baseline and discharge measurements were taken in the clinic, where patients were blinded to their baseline scores. Follow-up questionnaires were sent by mail. In study 2, all questionnaires were sent by mail and scored at home at baseline and at 3, 6 and 12 months. For this retrospective analysis, baseline and follow-up scores at 3, 6 and 12 months were included, to allow for sufficient time for deterioration in HRQoL, to include various time periods of measurement and to allow for comparison between both study settings.very much worse to very much better and 0 equalling no change.The CAT is an eight-item, one-dimensional scale with item scores ranging 0–5  and a total score summing up to a maximum of 40.no change; scores of ±2 and ±3 represented a minimal improvement/deterioration; scores of ±4 and ±5 were summarised as a moderate improvement/deterioration; and scores of ±6 and ±7 indicated a large improvement/deterioration.All change scores for the total scores of the CAT, CCQ and SGRQ were calculated as the difference between baseline and the respective follow-up visit . Negative change on all questionnaires represented improvement, and positive change deterioration. First, in the anchor-based approach, changes on the health status instruments were classified using the corresponding score on the GRC. Scores of 0 and ±1 on the GRC indicated 2 tests depending on the variable characteristic and/or normality of distribution. Health status change scores were all calculated in comparison with baseline. Follow-up scores were compared with baseline to test for significance of change using paired t-tests verifying normality of distribution.Data analysis was performed using SPSS V.24.0. Descriptives were evaluated at baseline for either frequencies with percentages (%), mean with SD or median with range. This was depending on the variable characteristics and/or normality of distribution. Health status data on the CCQ, CAT and SGRQ were evaluated at baseline (T0), 3 months (T3), 6 months (T6) and after 12 months (T12). Normality of distribution was verified using skewness and kurtosis. Values between −1 and +1 were considered indicative for normality. Data were checked for floor and ceiling effects, defined as over 15% of patients scoring in the lowest and highest 10% of the maximum scale range.response shift. Next, participants were categorised according to their GRC score at each follow-up. Mean changes (95% CI) for each respective category were determined to define thresholds for clinically relevant change. Significance of change for each GRC class at the respective follow-up visit was compared with baseline and assessed with paired t-tests verifying normality of the data. Last, the 0.5 SD of the change score was determined for patients with improved and deteriorating health status change scores separately at each follow-up. Thresholds were compared between both study settings (PR vs RCP).In order to determine clinically relevant thresholds for change, first correlations between the GRC and the CCQ, CAT and SGRQ were assessed using Pearson or Spearman correlation coefficients depending on normality of distribution. Correlations needed to be ≥0.30 (preferably ≥0.50) to be eligible as anchor.An absolute overall weighted mean MCID estimate for both improvement and deterioration was calculated at the end by multiplying the number of observations (n) at each follow-up visit times the MCID estimate for that period. The sum was divided by the total number of observations. Anchor-based and distribution-based approaches had similar weights. Estimates for improvement and deterioration were compared visually in a plot.Study 1 included 451 patients with completed baseline data .12 35 DuThere were no significant baseline differences between completers and non-completers of the 12-month follow-up in both studies, except that significantly more women (28.4%) compared with men (10.0%) did not complete the follow-up during RCP. Significant differences in age, forced expiratory volume in 1 s percentage predicted (FEV1%pred) and health status were observed between both studies .improved health status scores (negative change) at T12 after PR, compared with 44%–47% during RCP  were included (pairwise deletion). Floor and ceiling effects were negligible. Mean health status baseline scores were significantly different for PR and RCP . Overallring RCP . After Pring RCP . For RCPring RCP .There were no baseline differences in terms of age, gender and GOLD classification between patients with improved health status and those who deteriorated at T12 in both studies. Patients with a worse (read higher) CAT, CCQ or SGRQ baseline score prior to PR had significantly more improved health status after 1 year. Patients who improved during RCP had a significantly better baseline FEV1%pred.Significant correlations between the health status change scores and the GRC ranged, respectively, for study 1 from −0.33 to −0.41 (CAT), from −0.42 to −0.47 (CCQ), and from −0.48 to −0.54 (SGRQ) . These rweighted MCIDs for improvement and deterioration on the CAT were, respectively, −2.51 vs 2.76 during PR, and −2.49 vs 1.65 during RCP. These thresholds for improvement and deterioration on the CCQ were, respectively, −0.40 vs 0.43 during PR and −0.33 vs 0.30 during RCP. MCIDs for the SGRQ were, respectively, −6.74 vs 5.31 during PR and −4.06 vs 4.78 during RCP for improvement and deterioration. Estimates for minimal clinically important improvement and deterioration were overall somewhat similar; however, absolute MCIDs differed between PR and RCP. Thresholds for moderate and large improvement and deterioration differed from each other, as well as between study settings.Using both anchor-based and distribution-based methods, the et alet alet al and de Vet et alLittle evidence exists whether MCIDs for improvement are similar for deterioration. matched with estimates found in other studies.(−2.51 in PR and −2.49 in RCP) seemed somewhat comparable with the ones for deterioration (2.76 in PR and 1.65 in RCP) in the current study, except for deterioration during RCP. As CAT allows only integer scores,(−4.23 in PR) and deterioration (7.06 in PR and 3.89 in RCP) turned out less similar. The number of patients moderately deteriorating was low and differences were observed between both study settings. Moderate change might be experienced with a change on the CAT score of four to seven points. Two previous studies suggested that a cut-off point of four points was identified for acute HRQoL deterioration in clinical practice.The ranges found in this study for the MCID of the CAT (−0.50 to −0.19) and deterioration (0.19–0.66) overlapped each other in absolute sense, indicating that estimates for improvement and deterioration may be similar. However, differences were noted between PR (±0.40) and RCP (±0.30) for both minimal improvement and deterioration. These estimates for the MCID matched with earlier evidence.Regarding the CCQ, the MCID ranges found for both improvement (−9.20 to −2.76) and deterioration (2.75–7.53) on the SGRQ overlapped each other, although more variation was present here. A change of approximately four to seven points for both improvement and deterioration seemed to be the minimal clinically important threshold in the current study. The MCID for improvement during PR (−6.74) was larger than for deterioration (5.31); however, CIs for deterioration were wide. Estimates for the thresholds during RCP (4–5 points) were smaller compared with PR (5–7 points). Moreover, the distribution-based estimates turned out smaller than the anchor-based estimates, lowering the absolute weighted MCIDs. Thresholds for moderate improvement and deterioration in the current study were not very similar, ranging absolutely from 7.46 to 16.06 points. Estimates for clinically relevant large HRQoL improvement on the SGRQ ranged from −20 to −18 points for PR and RC, but too few patients were included to draw valid conclusions.Minimal thresholds for improvement et alet al was based on a study using patient preference-based techniques in COPD by applying a five-point patients’ judgement of treatment efficacy . This MCID of four points was valid for the group of patients that experienced effective treatment. In addition, a clinicians’ five-point GRC was scored, resulting in an MCID of four points. Clinicians’ and patients’ ratings are however not necessarily similar.The SGRQ MCID matched to some extent with previous results.This retrospective analysis of two prospective studies was the first to investigate clinically relevant thresholds for minimal, moderate and large changes in COPD health status comparing both improvement and deterioration using a triangulation of both anchor-based and distribution-based methods. There were sufficient correlations between the GRC and respective health status questionnaires as required,Although this is the first study to investigate thresholds for clinically relevant deterioration, still a limited number of patients indicated deterioration in HRQoL after PR and during RCP. This is a major limitation lowering the statistical power of the analysis, especially since sample size calculations were not based on the separate GRC categories. A second limitation is that the found thresholds demonstrate broad ranges with wide CIs, limiting its accuracy and requiring a larger sample size than our current studies had. Third, it should be taken into account that anchor-based and distribution-based approaches each has its own relevance, either based on clinical retrospective assessments or statistical parameters. It is recommended to combine both methods in measuring an instrument’s MCIDPatients with COPD tend to have worsening HRQoL over time; hence, MCIDs for deterioration have an important implication for clinical practice.minimal improvement and deterioration. Thresholds for, respectively, moderate and large changes should be further explored, but could approximately be in the range of, respectively, 4–5 and 5–6 for CAT, 0.80 and 1.00 for CCQ, and 10–15 points and 15–20 points for SGRQ.Determining deterioration in HRQoL is of importance, since one needs to differentiate between real worsening of patients’ status and random variations. In this study, estimates for clinically relevant thresholds for improvement and deterioration were somewhat similar, but differed between PR and RCP. We would recommend using cut-points of CAT ≥3 (intervention), CAT ≥2 (RCP), CCQ ≥0.40 (intervention), CCQ ≥0.30 (RCP), SGRQ ≥6 (intervention) and SGRQ ≥5 (RCP) for both


In clinical practice, discrimination between central nervous system (CNS) infections in patients with systemic lupus erythematosus (SLE) and neuropsychiatric lupus erythematosus (NPSLE) could be urgent and critical yet extremely challenging. Given this, this study aimed to investigate the clinical features and outcomes of infections in the CNS in patients with SLE and to establish a simplified scoring system for guiding the discrimination of CNS infections from NPSLE.A total of 95 patients who were identified as having CNS infections among 8491 SLE patients between January 1992 and January 2018 were included in this retrospective study. NPSLE patients admitted at the same period were randomly selected for comparison. Key factors either clinically valuable or statistically significant for discriminating CNS infections from NPSLE were integrated to build a simplified scoring system. Another group of 22 SLE patients complicated with suspected newly onset of CNS infections or NPSLE admitted after January 2018 was enrolled to verify the utility of the scoring system.P < 0.05), exhibited more fever  and polymorphonuclear leukocyte leukocytosis in the cerebrospinal fluid (CSF) , and had significantly decreased CSF glucose , whereas hypocomplementemia seemed to be a strong hint of NPSLE . A simplified scoring system integrated with 8 key factors was established for guiding clinical differential diagnosis. By setting the cutoff value at 4 and verifying in a group of SLE patients complicated with newly occurred suspected CNS infection or NPSLE, a sensitivity of 85.7% and specificity of 93.3% with the area under the curve (AUC) being 0.93 (95%CI 0.80–1.00) were obtained.Sixty-three positive pathogens were identified in 59 patients of the total 95 CNS infection cases. Compared with the NPSLE group, the CNS infections group had a longer disease duration  contains supplementary material, which is available to authorized users. Systemic lupus erythematosus (SLE) is a typical autoimmune disorder characterized by widespread immune deregulation, resulting in systemic inflammation and multi-organ impairments. Immunosuppressive agents, including glucocorticoids (GCs) and disease-modifying antirheumatic drugs (DMARDs), are the main therapeutic tools but may increase the risk of severe infections –4. InfecTo better understand and manage CNS infections in patients with SLE, we conducted this study in 8491 SLE in-patients admitted in the past 26 years to Peking Union Medical College Hospital (PUMCH), which is the tertiary referral center in China. In this study, we aim to not only identify the clinical features and etiology of CNS infections, but also provide the diagnostic clues for discriminating CNS infections from NPSLE among SLE patients. To our knowledge, this is the largest cohort study in this field to date and may provide practical guidance for clinicians to distinguish these two severe and confusing complications.PUMCH in-patient register database system was used for two-step screening electronically. First, we screened 8491 in-patients with a final diagnosis of “systemic lupus erythematosus” who were consecutively admitted to PUMCH from January 1992 to January 2018. Then, to identify probable cases of CNS infections, we searched the patient records for keywords including the following: “central nervous system infection,” “intracranial infection,” “encephalitis,” “meningitis,” “meningoencephalitis,” and “brain abscess.” To identify probable cases of NPSLE, we searched the patient records for keywords including the following: “lupus encephalopathy” and “neuropsychiatric lupus.” Patients with NPSLE would constitute the pool of candidates for the control group. Ninety-five SLE patients were confirmed to have CNS infections according to the criteria mentioned below. An equal number of NPSLE patients were randomly selected, using a computational algorithm that matched the age and gender. Medical records of these cases were reviewed, and those lacked key information were removed from the study. Relevant information was collected, and uncertain cases were discussed by a multiple disciplinary team (MDT) consisting of two rheumatologists, one specialist of infectious diseases, one radiologist, and one neurologist. If the MDT could not come to a consensus on a particular case, that case would be excluded from the study. If a patient in the NPSLE group had a concurrent infection, they were also excluded from the study. Further details of the screening process are shown in Additional file Mycobacterium tuberculosis DNA detection by PCR. Antibodies against viruses and parasites, such as Cysticercus cellulosae, were detected in cases as needed. Neuroimaging, such as magnetic resonance imaging (MRI), was conducted for all cases without contraindications. Otherwise, computed tomography (CT) scans were performed.The medical records of these patients were systematically reviewed and evaluated by the MDT, and all clinical data was collected. Follow-up clinical evaluations were conducted in all available patients, to update the case outcomes. Demographic features, medical history, clinical manifestations, laboratory findings, previous treatments history including the use of GCs and DMARDs, and systemic lupus erythematosus disease activity index 2000 (SLEDAI-2K) at the onset of CNS infection or NPSLE were recorded and presented in Table A simplified scoring system comprising 8 items was established for guiding clinical practice. Seventy-five out of 95 cases (79%) among the CNS infections group and the NPSLE group were integrated to determine the risk factors. Four factors were concluded from a univariate analysis and fixed by further multivariate logistic stepwise regression with the cutoff values decided by the receiver operating characteristic (ROC) curve. The MDT then voted on the other items, and four criteria for the diagnosis of CNS infection vs. NPSLE, based on extensive clinical experience, were selected and cutoff values determined.The scoring system was verified in the remaining 20 cases (21%). Sensitivity and specificity were calculated, and the scoring system was optimized. The scoring system was then applied to 22 SLE patients who were admitted to PUMCH after January 2018, with a recent onset of neuropsychiatric symptoms, yet uncertain diagnosis of CNS infection or NPSLE. The final clinical diagnosis was traced and then compared to the predicted diagnosis based on our scoring model. Positive and negative predictive values were calculated for accuracy evaluation of prejudgement.χ2 test), Student t, and Mann-Whitney tests were used to compare the categorical data, numerical data with a normal distribution, and numerical data without a normal distribution, respectively. Data with a normal distribution are displayed with the mean and standard deviation (SD). Non-parametrially distributed data are represented as the median (interquartile range [IQR]). A univariate analysis was performed to determine the variables associated with CNS infections compared with NPSLE and factors associated with mortality. A multivariate logistic stepwise regression was performed with variables with P value less than 0.05 in univariate analysis, a stepwise forward method used likelihood ratio test (LR) was used for variables entering the model. The ROC curve was utilized to find the cutoff values of variables with statistical significance for optimal event discrimination. Survival analysis was performed to compare the prognosis of the two groups using the Kaplan-Meier method calculated by log-rank test. The Statistical Package for the Social Sciences 20.0  was used for all data analysis. A P value less than 0.05 was considered statistically significant.The chi-square (P < 0.001). The median time interval from the onset of neuropsychiatric symptom to the diagnosis of CNS infections was 9.0 days (IQR 2.0–36.0 days)  were identified as having CNS infections, which is similar to what has been previously reported in the literature of 0.54–2.25% –13. The P < 0.001). The daily dose of prednisone or equivalent in the past 6 months in the CNS infections group was much higher than that in the NPSLE group . Sixty-seven (70.5%) patients in the CNS infections group had received at least one DMARD (including cyclophosphamide (CTX), mycophenolate mofetil (MMF), methotrexate, cyclosporin, tacrolimus, azathioprine, hydroxychloroquine, and leflunomide) in the past 6 months, in contrast to 36 (37.9%) patients in the NPSLE group (P < 0.001)   and 47 (51.1%) having extremely high ICP (> 300 mmH2O), compared to 50.5% and 9.5%, respectively, in the NPSLE group (both P < 0.001). The median WBC count in the CSF and the proportion of polymorphonuclear (PMN) leukocyte were both expected higher in the CNS infections group than those in the NPSLE group . Also, the CSF protein levels were elevated  remarkably, and the glucose level decreased  significantly in the CNS infections group than in the NPSLE group , headache (89.5%), and acute confusional state 51.6%), all of which occurred more frequently than those in the NPSLE group , followed by Cryptococcus in18 patients (30.5%) and mycobacteria in 11 patients (18.6%). Among the bacterial infections, the top 3 species were Listeria monocytogenes in 10 patients (16.9%), Nocardia asteroides in 4 patients (6.8%), and staphylococci in 3 patients (5.1%). Two patients (3.4%) were identified as having viral meningoencephalitis: one was confirmed to have Epstein-Barr virus (EBV) meningoencephalitis with the evidence of high copies of EBV DNA in the CSF; the other was found to have high titers of anti-herpes simplex virus-IgM in the CSF. One patient (1.7%) was diagnosed with cerebral cysticercosis, based on the positive anti-Cysticercus cellulosae antibody both in CSF and serum. Detailed pathogenic information for these patients was shown in Fig. Etiological tests identified 63 well-defined pathogens in 59 patients 62.1%), with 4 patients having been detected 2 pathogens at the same time. Common %, with 4P < 0.05)  were lost to follow-up. Similarly, 19 patients 20%) in the NPSLE group were lost to follow-up. Thirty patients (31.6%) in the CNS infections group died during the follow-up, and 26 patients (86.7%) died within the first year due to respiratory failure or cerebral hernia. Fourteen patients (14.7%) in the NPSLE group died. Both the total and 1-year mortality rates of the CNS infections group were significantly higher than those of the NPSLE group , cryptococcal (n = 18), and mycobacterial (n = 11) infections. Patients with bacterial or mycobacterial infections tended to manifest more consciousness disturbance  and meningeal irritation signs , compared to cryptococcal infections , more frequent pyrexia , and PMN leukocytosis in the CSF  but significantly decreased CSF glucose . Together, these results may be used as clues to distinguish CNS infections from NPSLE. Conversely, the existence of hypocomplementemia seemed to be a strong suggestive index of NPSLE over CNS infections  . With the cutoff value of 4, a sensitivity of 85% and a specificity of 85.0% with the AUC being 0.93 (95%CI 0.86–1.00) can be obtained for discriminating CNS infections from NPSLE  with a recent onset of neuropsychiatric symptoms with suspected CNS infection or NPSLE, who were admitted to PUMCH after January 2018. Patients in this cohort were scored using the SSS-8, and possible diagnosis was predicted according to SSS-8. Their final clinical diagnosis and etiology findings were traced and compared with the SSS-8 prejudgment. In brief, seven patients were confirmed to be definitive CNS infection with etiology evidence obtained later; detailed information is exhibited in Table We then verified SSS-8 in a group of SLE patients , high-copy TB DNA (two patients), and culture (three patients). Mycobacterium tuberculosis is a type of intracellular bacteria. Impaired cell-mediated immunity, especially defects in the macrophages, renders susceptibility in SLE patients [L. monocytogenes was the major pathogen identified in the bacterial infection subgroup. Patients with Gram-negative bacteria infection had the worst outcome, with a mortality rate of 83.3%. Fifty percent of them died within 10 days after diagnosis, and the remaining 33.3% of patients died within 1 month.In our cohort,  reports , 13. Comome Fig. b, probabpatients . L. monoIdentifying biomarkers to assist the prompt diagnosis of infections and distinguish infections from a SLE flare is essential for preventing poor outcomes , 24, 25.n = 75) and NPSLE (n = 75) via multivariate regression and ROC analysis, as well as suggestions made by a multiple disciplinary team, we generated an 8-item simplified scoring system, called SSS-8. The 8 items were a long disease duration (≥ 1 year), fever (> 37.3 °C), absence of hypocomplementemia and super high intracranial pressure (≥ 300 mmH2O), CSF leukocytosis (WBC ≥ 20/μL), PMN predominance in CSF (≥ 0.5%), increased protein level (≥ 0.905 g/L), and/or decreased glucose level (≤ 2.2 mmol/L) in CSF. The presence of each item was assigned 1 point, and patients who scored 4 points or above were considered as more inclined to CNS infections. This scoring system was first verified in the remaining 20 cases of the retrospective SLE cohort and obtained an AUC of 0.93 (95%CI 0.86–1.00) with a sensitivity and specificity for modal of 85.0% and 85.0%, respectively. We then further verified the SSS-8 in a small group of SLE patients with a recent onset of neuropsychiatric symptoms and undetermined diagnosis of CNS infection or NPSLE. Their final clinical diagnosis was recorded and compared to their predicted diagnosis using the SSS-8 scale. Our SSS-8 scale evaluation predicted 6/7 patients had CNS infections, and these cases were confirmed with etiologic evidence and/or clinical decision. Further, the SSS-8 predicted 14/15 patients had non-CNS infections and turned out to have the final clinical diagnosis of NPSLE. However, team with limited number of experts, this scoring system does have some shortcomings: it is generated from a limited sample, and each case was discussed among a multidisciplinary team. Also, CSF lab tests are not sensitive for brain abscess which is not uncommon in CNS infections in SLE. Further verification in a large prospective cohort and optimization with better predictive markers or cutoff values are necessary before the widespread use of this rubric.We also aimed to construct a simplified and practical evaluation system to help prompt differentiation between these 2 severe and confusing complications, for doctors treating patients with SLE. By integrating 79% SLE patients with CNS infections Additional file 2:The prevalence rate of CNS infections with SLE vs. NPSLE. (PDF 278 kb)Additional file 3:The change of etiology of 59 SLE patients with CNS infections with a 5-year interval frame. (PDF 350 kb)Additional file 4:CNS infections in SLE patients with different etiology findings. (PDF 66 kb)


Vigna radiata) (LE), (iv) green manure (Sesbania aculeata) (GM), (v) farmyard manure (FYM), (vi) wheat stubble (WS), and (vii) rice stubble (RS). Maximum C input to soil (as the percentage of C assimilated in the system) was in GM (36%) followed by RS (34%), WS (33%), LE (24%), and FYM (21%) compared to O (15%) and F (15%). Total C input to soil had a direct effect on soil C stock, soil C fractions (maximum in VLc and LLc), yet the responses in terms of biological yield were controlled by the quality of the biomass  incorporated. Legume-based biomass inputs accrued most benefits for soil C sequestration and biological productivity.Major nutrient management systems for rice-wheat cropping were compared for their potential to credit organic carbon (C) to the soil, its fractionation into active  and passive  pools, and crop yield responses. A ten-year long experiment was used to study effects of: (i) no inputs , (ii) 100% inorganic fertilizers (F) compared to reduced fertilizers inputs (55%) supplemented with biomass incorporation from (iii) opportunity legume crop ( Whereas at global scale increasing soil C has been recognized as a major strategy for curtailing increased carbon dioxide (CO2) levels in earth’s atmosphere7, at the farm level increasing soil C is crucial for sustaining the quality and productivity of soil8. In the Indo-Gangetic plain, cultivated lands are under intensive pressure to meet the food demand of the exploding population of India. The plain is one of the most intensively cultivated areas in the world, feeding 50% of India’s population with only 13% share in the total geographical area9. Rice (Oryza sativa) in late summer/monsoon season followed by wheat (Triticum aestivum) in the winter season is the major cropping system with highly intensive soil and crop management operations11. The alluvial soils of the region have fairly high annual productivity in terms of the C assimilated from the atmosphere into crop biomass, both above and below the ground12.Soil carbon (C) is not only considered as the most logical sink for atmospheric CO8. Nutrient management through fertilizers is a key operation in crop production. Yet the indiscriminate or sole use of inorganic fertilizers has led to the deterioration of soil health. Rice-wheat systems are highly intensive cropping systems, in terms of energy requirement and nutrient removal, in South Asia. Therefore, integrated nutrient management (INM) practices with the combined use of inorganic and organic fertilizers/manures have long been advocated to farmers with a goal to improve soil health and ecosystem services. With time, different nutrient and carbon management systems have evolved namely, green manuring with Sesbania aculeata, use of legumes as opportunity crops after wheat harvest and before rice transplanting, incorporation of farmyard manure, and practice of retaining and incorporating crop residues into the soil. Though the C inputs in these managements may be different along with differences in the quality of organic matter added, each one of them has evolved as a complete package of practices for crop nutrient management and sustainable crop production. In green manuring, a legume crop (Sesbania aculeata) is taken up during the lean period between wheat harvest and rice planting. Similarly, green gram (Vigna radiata) can be accommodated as an opportunity crop after wheat harvest and before rice transplanting and its biomass can be incorporated into the soil. More recently, cereal crop residue/stubble retention and its incorporation into soil have been advocated to the farmers to avoid burning of crop stubble and residues, so as to build up soil C and to curtail air pollution in the region. While the quantitative differences in organic matter inputs into the soil  are anticipated to result in differences in soil C, the qualitative differences  might play role in C fractionation in soil. Carbon fractionation into active and passive fractions has an important role in C sequestration in soil13.While the C assimilated in the above-ground biomass largely leaves farm gate in the form of grain and straw harvest, the C added to soil as root biomass and rhizodeposition or as soil amendment stays longer, depending upon the soil management. The soil C contributes to nutrient enrichment of the soil, their availability to crop plants and soil quality improvement. Increase in soil C can be linked to many other improved ecosystem functionset al.13 reported that inorganic fertilizers are able to just maintain the soil organic C content, while inorganic fertilizers plus organics increased soil organic C in rice-wheat systems. In rice-wheat system, soil organic C concentration in surface 0.6 m was higher (1.8–6.2 g kg−1) in FYM-treated soils compared with 1.7–5.3 g kg−1 in NPK, and 0.9–3.0 g kg−1 in unfertilized plots14. Ghosh et al.15 studied the effect of organic and inorganic amendments on soil carbon sequestration potential in long term fertility experiment (19 years) in the plains of eastern India and reported that cultivation without organic amendments depleted total C content by 39–43% when compared with the addition of organic amendments. Wei et al.16 also suggested that crop straw incorporation with chemical N, P, K fertilizers is a better soil fertilization practice in the light sandy loam soil of the Huang-Huai-Hai Plain of China compared to their sole use. Effects of C returned to the soil in the form of wheat straw, farmyard manure, green manure, rice straw, etc. on soil organic C, grain yield, physical properties, organic matter and total N content of the soil, total organic C and plant growth have been thoroughly investigated22. So far, the notion is that organic matter recycling or biomass incorporation into the soil in intensively managed agricultural systems is driven by the net inputs of organic matter only. Therefore, most studies on residue-based or organically managed systems fall short of relating C management to the quality of organic matter inputs and their biological responses, especially in intensive rice-wheat systems.Several studies have evaluated the inherent benefits of such management practices in terms of nutrient supply and carbon sequestration. Yet, long-term side by side comparisons of these systems in terms of total C balance including, C assimilated, C retained/incorporated in the soil, and changes in active and passive fractions of soil C are lacking. Most importantly, biological responses of these unique C balances have often been overlooked under these nutrient management systems, particularly in terms of qualitative and quantitative differences in organic matter added. Majumdar The aim of this study was to budget C assimilation, C input into soil, partitioning of this C into active and passive soil C fractions, determining organic C sequestration potential of these management practices, and relating changes in these parameters to organic matter quality, net inputs and also their biological responses, over a long-term period in rice-wheat cropping system.−1) followed by LE (18.6 Mg ha−1), F (16.2 Mg ha−1), FYM (14.0 Mg ha−1), WS (13.5 Mg ha−1), RS (13.3 Mg ha−1), and O (6.3 Mg ha−1)  followed by WS (4.5 Mg ha−1), RS (4.5 Mg ha−1), LE (4.4 Mg ha−1), FYM (3.0 Mg ha−1), F (2.5 Mg ha−1) and O (0.9 Mg ha−1). The C input into the soil as the percentage of C assimilated in the system was maximum in GM (36%) and least in O and F (15%).Budgeting total plant assimilated C and C-input into soil, revealed that the maximum C was assimilated in GM  treatments in the surface 0.15 m soil Table . In geneSignificantly higher carbon sequestration potential (CSP) was noted for FYM, GM and WS management, for shallower depths (0–0.15 m) Fig. . For lowVigna radiata) biomass incorporation (LE) and green manuring (GM) matched or even exceeded F management after 5–6 years. Thus, there was a breakeven period of ~ 5 years for organic amended management compared to F. Significant correlations were observed between C input and above ground biomass yield in all management but the degree of response varied for rice and wheat crop  was in GM (green manure) followed by LE (Legume crop biomass incorporation), WS (wheat stubble retention), RS (rice stubble retention), F (100% inorganic fertilizers), and O (no fertilizers), in the decreasing order.Six major integrated nutrient management (INM) systems practiced in Indo-Gangetic plain were budgeted for carbon (C) assimilation, C input into soil and soil C sequestration over a 10 year period. Overall, the results suggested that the differences in soil carbon fractionation (active and passive pools) were driven by net inputs of C as well as the quality of biomass added in each management. The less labile (LLc) and the very labile (VLc) fractions were the most contributed to and there was hardly any change in non-labile fractions with increased inputs of C. The key differences in C inputs into the soil under these nutrient management systems were due to the above ground additions of organic matter. The maximum C input (Sesbania aculeata) biomass incorporated into the soil. Second highest C inputs were in case of legume opportunity crop , and crop residues . Though the net C inputs into the soil were similar in these three managements, LE biomass has narrower C:N ratio compared to crop residues   Table . FYM clo27. Thus, it could be concluded that most organic amendments and organic matter additions remained concentrated in 0.15 m depth despite tillage operations. Similar observations have been noted by Guo et al.28. It is also possible that because organic inputs were incorporated into the soil during puddling for rice transplanting, they being lighter fractions in a soil-water puddle would tend to concentrate at the surface. The tillage (dry plowing) for wheat sowing is not as intensive as puddling to mix the organic matter any further down.Soil organic C stock was higher in the surface 0.15 m. The decrease was almost 50% in the lower 0.15–0.30 m soil depth despite the fact that the soil disturbance with tillage as deep as 20 cm, which was done in these managements using a power tiller can be expected to move organic matter deeper. Both rice and wheat crops have maximum root biomass concentrated in 0.15 m soil depthet al.29 had similar observations wherein manure and legume-based systems had higher storage of soil carbon and nitrogen despite no quantitative differences in C inputs. The qualitative differences  contributed to differences in soil organic C stocks, thus Farmyard manure (FYM) based management involving the input of highly decomposed organic matter, with more stable C components, not only resulted in higher total C stock but also most of it was in less labile fraction (LLc). Legume-based managements  also had higher organic C stock at all depths. This disproves the conventional notion that biomass quality in agricultural systems may not play a significant role in C storage in soil.Of the total soil organic carbon, active fractions (VLc and Lc) constituted almost 50% and are liable to be easily lost. But no significant differences were noted in the passive fractions (LLc and NLc) due to management, yet the LLc and the NLc were the most significant fractions in case of LE, GM, and FYM. Since these are the biomasses with low C:N ratio Table  or decom30.While both high C input and high biomass N (as in GM) benefited crop productivity in rice crop, right from the early establishment of these systems, in case of wheat crop, break-even period for integrated nutrient management  and F (100% inorganic fertilizer) was much longer. Even for the rice crop, in case of LE and FYM, the breakeven period with F was 7–8 years. Rice is primarily a low land crop and therefore water is no constraint, ensuring an adequate nutrient release and availability to plant. But in case of the wheat crop where mostly water-limited conditions prevail, nutrient release and their availability to plants may be limited, especially in the integrated managementSesbania and Vigna are nutrient rich  biomasses and under water-sufficient conditions, as in case of rice crop, favored sufficient release of nutrients  during decomposition. Averagely, Sesbania had 2.7% (w/w) and Vigna had 1.7% (w/w) nitrogen which provided around 141.8 and 87.9 Kg N ha−1, respectively, via incorporation of their biomass under GM and LE management, respectively. Therefore, perhaps there was no N limitation in these systems. Nitrogen limitation has been noted to be a major constraint for C decomposition process. Carbon decomposition has been found to increase with a decrease in the initial C:N ratio of the organic matter/substrate31. Nitrogen poor materials have been demonstrated to provide more-efficient N use and less-efficient C use than the N rich substrates.Farmers relate the benefits of any management practice to the responses in terms of yield. Many farmers in the region take land on lease, and their interest, therefore, is more in getting immediate economic gains rather than having a long-term interest in soil health. Unless C input into the soil is related to the gains in productivity, such practices would be hard to sell to farmers. Evaluation of such responses (C-input effects on crop yields) for intensive agricultural systems is rare. For rice crop, the biological yield correlated positively with C inputs into the soil except for GM and LE, wherein increased C input into soil did not reflect in terms of any benefit in yield. Both In wheat crop too, all managements responded to C inputs into the soil in terms of increase in biological yield except GM and LE. But, the slope of fit, which is an indicator of change in yield per unit change (increase in this case) in C input into soil increased. Besides in wheat season, RS was also non-responsive. Under water-limited conditions (as in wheat), dissolution and movement of nutrients to plant roots is restricted. Rice stubble has better N concentration than wheat stubble, and therefore, perhaps, it also provided an advantage during wheat growth when water (as well as nutrient availability) is a constraint, compared to rice season. Therefore, the advantages obtained under water-sufficient conditions (as in rice) may not be applicable under water-deficient conditions (as in wheat). It also seemed that the responses of C input to soil were both chemical and physical otherwise FYM would have responded the same way as RS. It was also evident that the responses in terms of biomass yield per unit C input to soil decreased as the total C inputs to soil increased. O, F and FYM were the most responsive managements (under any condition) to C inputs into soil, indicating that such management would benefit most, at farmer’s level, from intervention leading to increased organic matter incorporation into the soil. These were the management with low C input to soil. Crop residue management and nutrient management programs should be targeted at this group of farmers. The second group was that of crop residues  wherein responses were very moderate. These systems had only a marginal increase in crop productivity with each increment of C input, perhaps due to N limitations since cereal crop residues are low in N and more recalcitrant type of organic material. The third class included the management wherein succulent type, low C: N ratio and N rich materials were added . These systems showed no response in water sufficient conditions (rice crop) and very little response under water-limited conditions (wheat crop), precisely pointing to the fact that the nitrogen availability could be a major limitation along with quantitative C inputs for any integrated nutrient management or crop residue management program to succeed.Vigna as opportunity crop between rice and wheat and its biomass incorporation) and GM (green manure crop Sesbania biomass incorporation) based management had high biomass incorporation into the soil, yet these materials also had high N and narrow C:N ratio. RS (rice stubble retention) and WS (wheat stubble retention) systems had lower C inputs as well as wider C:N ratio. Legume-based systems indicated higher benefits in terms of C sequestration. FYM constituted decomposed organic matter compared to others. In terms of above ground biomass yield of rice, GM outperformed other managements right from the start, and LE and FYM had a break-even period of around 4–5 years compared to 100% inorganic fertilizer based management (F). For wheat crop, all managements compared to F had a break-even period of 6–7 years. Nitrogen availability indeed played a significant role. Both Sesbania and Vigna are high nitrogen (low C:N ratio) crops. Increase in biological yield with increased C input/incorporation worked for high C:N ratio biomass incorporation, but yield under low C:N ratio biomass incorporation based system  remained unresponsive to changes in C input to soil C. Hence, not only quantitative C inputs, but also nutrient (particularly nitrogen) contributions through organic matter played important role. Legume-based management systems  are, therefore, the best management options for rice-wheat systems in Indo-Gangetic plain of India to enhance crops productivity and soil C sequestration.Our study revealed that the fractionation of incorporated carbon (C) under an integrated nutrient management practice for the rice-wheat system was driven by both quantitative as well as qualitative differences in the C inputs to the soil. LE . The experimental area lies in a semi-arid sub-tropical climate zone with very hot summers and cool winters. The mean annual precipitation is 750 mm.A field experiment on integrated nutrient management in rice-wheat systems was initiated in 2005 on a soil with sandy loam texture at ICAR-Central Soil Salinity Research Institute (CSSRI), Karnal, India, located at 29.43°N and 76.58°E. The treatments were laid in 5 m × 4 m plots with four replications in completely randomized blocks. At the initiation of experiment the soils recorded a pH of 8.5, soil organic carbon equal to 2.1 g kgVigna radiata) as opportunity crop, GM-green manuring (Sesbania aculeata), FYM- farmyard manure incorporation, WS- wheat stubble retention and RS-rice stubble retention, compared to ‘100% inorganic fertilizers only’ (F) and ‘no fertilizer at all’ (O) treatment. The treatment details are provided in Table Oryza sativa L.) in the summer followed by wheat (Triticum aestivum L.) in the winter season. In all treatments, during rice season, the soil was dry tilled to incorporate the organic amendments into the soil at the start of the first week of July, and then puddled-in towards the end of the first week of July, every year. Both operations were done using power tiller. One-month-old seedlings of var. Pusa 44 were transplanted at recommended row spacing (20 cm). In wheat season, soils were first dry-tilled using power tiller and then hand-pulled plough was used to sow the seeds of var. HD2967 at recommended row spacing (15 cm). Wherever applicable nitrogen fertilizer applications were in 3 equal splits at t = 0, 21 and 42 days after transplanting (rice)/sowing (wheat). For nitrogen, phosphorus, and potassium fertilization urea, diammonium phosphate (DAP) and muriate of potash (MOP), respectively, were used at the time of transplanting/sowing. The recommended rates of inorganic fertilizers were 180, 26, and 42 Kg ha−1 for N, P and K, respectively, for both crops. Besides only in F treatment, ZnSO4 was also applied as micronutrient fertilizer at the recommended rate of 7 Kg ha−1 at the time of transplanting/sowing. Rice was transplanted in July and harvested in the last week of October, and wheat was sown in the second week of November and harvested in the last week of March, every year. In rice, fields were flooded for pudding and thereafter ~10 cm of standing water on the surface was maintained for first one month. For the second month, ~5 cm of surface flooding was maintained with irrigation every penultimate day, and for the third month, irrigations were given on aweekly basis and the soils were only saturated, with no standing water on the soil surface. Two weeks before harvesting irrigations were stopped. For wheat crop, 3–4 surface irrigations were given at around 1 month interval. These are standard irrigation management practices for rice-wheat systems in the region.With the treatments imposed for 10 years, the soil carbon fractions were determined in 2015, after harvesting of wheat crop. The study included seven nutrient management treatments in total: five treatments with reduced (55%) inorganic fertilizer doses in combination with organic sources namely, LE- legume (Following management schedules were followed for different treatments:O: Rice followed by wheat was grown without any inorganic fertilizers or organic inputs.1. F: Rice followed by wheat was grown with full recommended inorganic fertilizer input (N:P:K:Zn = 180:26:42:7 Kg ha−1). No organic inputs were provided.2. LE: Legume (LE), Vigna radiata, was grown in the summer lean period between wheat and rice as an “opportunity crop”. The Vigna seeds were sown in the first week of May, after wheat harvest. In the first week of July (after ~ 60 days of sowing) pods were harvested and the remaining plant biomass was incorporated into the soil, before rice transplanting.3. GM: A green manure crop, Sesbania aculeata, was grown in the lean period between wheat and rice. The green manure crop was sown on or around 20th of May every year after wheat harvest. After 35–40 days of sowing, the green manure crop was incorporated into the soil, before rice transplanting.4. FYM: Farmyard manure (FYM) at the rate of 10 Mg ha−1 was incorporated in the soil just before transplanting of rice.5. WS: 30 cm standing stubble was retained at the time of harvesting of wheat. It was dry-plowed into the soil before rice transplanting in the first week of July.6. RS: 30 cm standing stubble was retained at the time of harvesting of rice. It was dry-plowed into soil at the time of wheat sowing in 2nd week of November.7. Soil samples for carbon determinations were drawn after wheat harvest. Samples were air-dried and sieved (0.5 mm) for further analysis. Plant samples were taken at the harvest of rice and wheat crops for C, N determinations and other chemical analyses. Sampling was done for all organic amendments for determination of total C incorporated at the time of amendment application.34. In this method, 2 grams of sieved (0.5 mm) soil sample was taken in 250 ml conical flask. 10 ml of 1 N K2Cr2O7 and 20 ml of concentrated H2SO4 was added in the conical flasks. 100 ml of distilled water was added followed by 10 drops of diphenylamine indicator and 0.5 g of NaF. Excess of 1 N K2Cr2O7 was back titrated against N/2 ferrous ammonium sulfate. A blank was simultaneously run and soil organic C was calculated. Total carbon (TC) content of the soil samples was determined by dry combustion method using CHNS Elemental analyzer . Different fractions of soil organic C comprising very labile, labile, less labile and non-labile  were determined by oxidation with 12 N, 18 N and 24 N H2SO4 . Very labile (VLc) fraction was determined by reaction with 12 N H2SO4; labile carbon (Lc) was determined by calculating the difference in oxidizable C determined with 18 N and 12 N H2SO4 (18 N H2SO4 minus 12 N H2SO4); the less labile (LLc) fraction was determined by calculating the difference in oxidizable organic C extracted with 24 N and 18 N H2SO4. Non-labile (NLc) fraction was calculated as the difference between total oxidizable carbon and oxidizable carbon determined with 24 N H2SO4. VLc and Lc make an active pool of carbon while LLc and NLc make a passive pool of carbon32.Oxidizable organic C in soil was determined by modified Walkley and Black’s rapid titration methodTotal soil organic C stock was calculated using the following relation:−1 soil, bulk density in Mg m−3, depth in m and soil organic C stock in kg m−2.where, the soil C content is given in g C kg3 was used to determine bulk density35.Metallic cores of known volume (v) were used to measure the soil bulk density. Soil samples were taken at the depth of 0–0.15 m, and 0.15–0.30 m, after the wheat harvest. Samples were oven dried at 105 °C for 24 h to obtain the dry weight of soil (w). The ratio of w and v in g/cm36:Carbon sequestration potential (CSP) was determined for different soil depths  by measuring the soil organic C for respective depth using following equationAbove ground biomass yield was measured in terms of total above ground crop biomass at the end of each season. The total above ground biomass was separated into grain and straw yield for each treatment and replications.th cropping cycle) and 2014–2015 (10th cropping cycle), and its empirical relation with above ground biomass/straw was used to calculate coarse root biomass for rest of the years. Rhizodeposition was calculated using the estimates given by Jones et al.37 according to which 27% of C allocated to roots roughly accounts for rhizodeposition in cereals and grasses. The total C content of grain, straw and root biomass was determined with CHNS elemental analyzer  for the conversion of total mass to C content. C incorporated into the soil was calculated annually by measuring the entire C added to the soil in a treatment during full cropping cycle in the form of root biomass (including rhizodeposition), crop residue retained (and incorporated), Vigna (opportunity crop) biomass incorporated, Sesbania (green manure) biomass incorporated, and ex-situ additions. Ex-situ addition included C added to the soil through farmyard manure in FYM treatment.Plant assimilated C was calculated for each crop for each season from 2005–2015 based on the above and below ground biomass accumulated and its equivalent in C. Root biomass for rice and wheat plants was measured only in 2013–2014 . The weighted least-square method was used in Origin v8.5  to apply linear regression between the measured parameters. The graphical representations were drawn using Origin v8.5 software. All tests were performed at a significance level of 0.05.Statistical analysis of variance (ANOVA) was used to test all parameters. Separation of means was done by Tukey’s honestly significant difference testSupplementary Information