Only extended ICR, but neither limited ICR nor SBR, induced intestinal insufficiency. α-Diversity was reduced in both ICR variants but not after SBR. All resections resulted in an increase in Proteobacteria. Pathobionts, such as Clostridia, Shigella, and Enterococcus, increased after SBR while Muribaculaceae, Lactobacillus, and Lachnospiraceae decreased. Limited ICR resulted in an increase of members of the Clostridium sensu stricto group, Terrisporobacter and Enterococcus and a decrease of Muribaculaceae. The increase of Enterococcus was even more pronounced after extended ICR while Muribaculaceae and Akkermansia were dramatically reduced. Both ICR variants caused a decrease in steroid biosynthesis and glycosaminoglycan degradation-associated pathways, suggesting altered bile acid transformation and mucus utilization.Extensive bowel resection can lead to short bowel syndrome and intestinal failure. Resection-induced dysbiosis may be related to the specific anatomic site of resection and influences the disease progression. Although patients with end-jejunostomy are at high risk for intestinal failure, preservation of the ileocecal valve and colon counteracts this risk. The present study investigated the role of the cecum in maintaining microbial homeostasis after different types of small bowel resection. Male C57BL6/J mice were anesthetized by intraperitoneal injection of ketamine-xylazine and received extended ileocecal resection (extended ICR), limited ileocecal resection (limited ICR), or mid-small bowel resection (SBR). Stool samples were collected before surgery and between NEW & NOTEWORTHY Resection-induced dysbiosis affects disease progression in patients with short bowel syndrome. Severe dysbiosis occurs after removal of the ileocecal valve, even in the absence of short bowel conditions, and is associated with the loss of Muribaculaceae and Akkermansia and an increase of Clostridium and Enterococcus. The preservation of the cecum should be considered in surgical therapy, and dysbiosis should be targeted based on its specific anatomical signature to improve postoperative bacterial colonization. Because the experimental short bowel model was originally established in male mice in our laboratory and to exclude possible sex-specific variations in modulation gut microbiota in the overall small sample, only male mice were used in this study. Mice were housed under conventional conditions with free access to standard chow and water. Mice were used for experiments at the age of 3–6 mo. Two days before surgery mice were separated into single cages and switched to a standard liquid diet  until the end of the experiment to prevent postoperative intestinal obstruction. As previously shown, a liquid diet has no influence on the microbial composition . Mice unday 5 as described previously  2 and 5 as previously described  was calculated as follows: (w − d)/(w − e) × 100.Stool water content was measured on the day of surgery (0d) and on the escribed . In briePOD 0) at POD 2 and at POD 5. For mice with SBR and extended ICR, stool samples were additionally collected on day 7, which were pooled with the samples on day 5 for further analysis and designated as POD 5. Stool was flash-frozen and immediately stored at −80°C until analyzed. Total DNA was extracted using ZymoBIOMICSTM DNA Miniprep Kit according to the manufacturer’s protocol  including bead-beating system to ensure unbiased lysis of bacteria.Fresh stool samples were collected on the day before surgery (2) clusters were sequenced, generating ∼25 million reads passing filter specs. Over 69.0% of the sequencing and index reads were found with a Qscore ≥ 30.The concentration of purified DNA was determined by Qubit and Nanodrop protocols and finally the amplicon PCR was started with DNA templates at a concentration of 5 ng/µL in 10 mM Tris, pH 8.5. The bacterial 16S rRNA genes were amplified using 515 F (5′-TCG-TCG-GCA-GCG-TCA-GAT-GTG-TAT-AAG-AGA-CAG-GTG-CCA-GCM-GCC-GCG-GTA-A-3′) and 806 R (5′-GTC-TCG-TGG-GCT-CGG-AGA-TGT-GTA-TAA-GAG-ACA-GGG-ACT-ACH-VGG-GTW-TCT-AAT-3′) primers targeting the V4 region. The PCR resulted in amplicon sizes of ∼390 bp. All further steps in library preparation were performed according to the Illumina “16S Metagenomic Sequencing Library Preparation” protocol and as described previously . BrieflyP values . The obtained differentially abundant OTUs were then binned into time-series groups via the fuzzy clustering method implemented in the Mfuzz package version 2.38.0  per group. Group comparisons were performed by two-way ANOVA. Tukey’s test was used to correct for multiple comparisons. Significance level of 0.05 or adjusted α (αadjust) as indicated in the figure legends was considered.Body weight, stool water content, and food intake were analyzed using GraphPad Prism 9.0 (GraphPad Software). Data are presented as means ± standard error (SE) for the indicated number of mice  at clusters A. Shanno further B.To describe the general characteristics of microbiota after the three different resection variants, we analyzed the composition of stool microbiota . Before POD 5 revealed notable differences among the three resection variants  at variants . Five davariants A. After variants B and alsvariants C, gram-pUnder physiological conditions, the colon habitats a diverse community of bacteria that are mainly anaerobic. The number of aerobic and anaerobic bacteria was stable in the feces of mice after SBR . In contPOD 2 and POD 5 are shown in POD 2 after SBR, most differentially abundant OTUs were increased and belonged to the phyla Firmicutes and Bacteroidota or Proteobacteria. At genus level, Clostridium senso stricto 1 (log2-fold-change 40), Echericha-Shigella (log2-fold-change 7), and Enterococcus (log2-fold-change 7) were increased on POD 2 after SBR  were dramatically reduced on POD 2 and POD 5 after limited ICR . In addition, OTUs belonging to the Lachnospiraceae_NK4A 136 group, Rikinella, Lactobacillus, and Bacteroides were also decreased after limited ICR. After limited ICR Clostridium sensu stricto 1 (Firmicutes) again was significantly increased (log2-fold-change 50) on POD 2 and POD 5. In addition to the appearance of Enterococcus, Terrisporobacter (both Firmicutes) significantly increased (log2-fold-change 25) on POD 2 and POD 5 after limited ICR  were increased. OTUs belonging to Muribaculaceae were strongly decreased (log2-fold-change −70 on POD 2 and POD 5) after extended ICR. In addition, extended ICR also significantly decreased the abundance of Akkermansia on POD 2  or decreased (cluster C4). Conversely, we also found clusters in the SBR samples whose abundance increased slowly until POD 2, and then either kept increasing but at a faster pace (cluster C1) or increased fast until POD 2 and then increased even faster (cluster C3). Finally, we observed two clusters, which include taxa whose abundances decreased fast until POD 2 and then either decreased further slowly (cluster C6) or stayed at similar abundances ; another also increasing until POD 2 but then keeping increasing (cluster C1); and a third, decreasing until POD 2, and then remaining stable (cluster C2). In contrast, the group of bacteria that decreased until POD 2 and then remained stable (cluster C2) was more diverse and consisted of 126 OTUs ; moderate increase until POD 2 and then decrease (cluster C3); increased abundances until POD 2 and then kept increasing although with lower fold-changes (cluster C4); decreased abundances until POD 2 and then increased moderately (cluster C2); or decreased abundance until POD 2 and then remained stable (cluster C5). This last cluster C5 was more diverse than cluster C1–C4  after the different resection variants. In line with the observation that SBR induced little changes in the colonic microbiome, functional and metabolic pathways were only marginally different on on POD 5 A.POD 2 and POD 5 and α-linolenic acid metabolism and transcription-related proteins were upregulated on POD 2 and POD 5. Pathways related to caffeine metabolism and steroid biosynthesis were up to 7.5-fold decreased after limited ICR , caffeine metabolism (6.5-fold), and glycosaminoglycan degradation  and small bowel resection (SBR) are short bowel models to study intestinal insufficiency and mucosal adaptation. We have previously shown that extended ICR induces intestinal insufficiency in mice with persisting increased stool water and weight loss , 12 thatAkkermansia muciniphila and, more recently, also Akkermansia glycaniphila have been isolated from the human intestine, the latter being found preferentially in nonmammals  were also decreased after ICR. All three genera are strong mucus degraders  and by the FORUN program (889007 to P.B.) as well as the clinician-scientist program (to J.R.) from the Rostock University Medical Center. Further funding was provided through the research project “EnErGie” and by the European Social Fund (ESF), reference: ESF/14-BM-A55-0007/18 (to P.B.), and the Ministry of Education, Science, and Culture of Mecklenburg-Vorpommern. Purchase of the Illumina MiSeq was kindly supported by the EU-EFRE  program and funds from the Rostock University Medical Center awarded to B.K.No conflicts of interest, financial or otherwise, are declared by the authors.P.B. and G.L. conceived and designed research; P.B., E.S., J.B. and M.W. performed experiments; P.B. and I.B. analyzed data; P.B., B.V., B.K., and G.L. interpreted results of experiments; P.B. and I.B. prepared figures; P.B. and I.B. drafted manuscript; I.B., J.R., G.L., and M.W. edited and revised manuscript; P.B., I.B., J.R., E.S., B.V., J.B., B.K., G.L., and M.W. approved final version of manuscript.


Insulin and IGF-1 receptors (IR and IGF1R) are highly homologous and share similar signaling systems, but each has a unique physiological role, with IR primarily regulating metabolic homeostasis and IGF1R regulating mitogenic control and growth. Here, we show that replacement of a single amino acid at position 973, just distal to the NPEY motif in the intracellular juxtamembrane region, from leucine, which is highly conserved in IRs, to phenylalanine, the highly conserved homologous residue in IGF1Rs, resulted in decreased IRS-1/PI3K/Akt/mTORC1 signaling and increased Shc/Gab1/MAPK cell cycle signaling. As a result, cells expressing L973F-IR exhibited decreased insulin-induced glucose uptake, increased cell growth, and impaired receptor internalization. Mice with knockin of the L973F-IR showed similar alterations in signaling in vivo, and this led to decreased insulin sensitivity, a modest increase in growth, and decreased weight gain when mice were challenged with a high-fat diet. Thus, leucine-973 in the juxtamembrane region of the IR acts as a crucial residue differentiating IR signaling from IGF1R signaling.  Insulin and IGF-1 mediate their pleiotropic biological effects by binding to insulin and IGF-1 receptors (IR and IGF1R) on the surface of the cell . Due to Recently, using chimeric receptors, we have demonstrated how domain differences between IR and IGF1R contribute to the distinct functions of these receptors . Thus, rINSR L973F substitution. Here, we show that substitution of phenylalanine for leucine at position 973 in the IR decreases IRS-1/PI3K/Akt/mTORC1 signaling, upregulates Shc/Gab1/MAPK signaling and cell cycle–related pathways, and decreases ligand-stimulated receptor internalization in vitro. Functionally, this leads to decreased insulin-induced glycolysis and an increased proliferation rate at the cellular level. Mice with knockin of the L973F-IR show similar signaling alterations, which lead to impaired insulin sensitivity, increases in growth, and resistance to weight gain upon a high-fat diet (HFD) challenge. Thus, leucine-973 in the +1 position following the NPEY motif in the juxtamembrane region is a key residue differentiating IR signaling from IGF1R signaling.By sequential substitution of all amino acids that differ in the juxtamembrane region of IR versus IGF1R, we have previously shown that another important sequence difference in the region surrounding the NPEY motif of IR and IGF1R may be located at position 973 just C-terminal to motif. This residue is a leucine in IR and a phenylalanine in IGF1R, and we have found that the replacement of leucine-973 in the juxtamembrane region of IR with Phe decreases IRS-1 binding and increases Shc binding. In the present study, we have explored in depth this important region of these receptors both in vitro and in vivo by generating cell lines in which we have deleted both endogenous IR and IGF1R and then reconstituted the cells with either WT human IR B isoform (WT-IR) or a mutant IR in which leucine-973 has been changed to phenylalanine (L973F-IR) as well as by creation of a knockin mouse model with an The NPEY motif in the juxtamembrane region in both IR and IGF1R is critical for recruitment of receptor substrates including IRS-1 and Shc , 17. We https://doi.org/10.1172/JCI161472DS1). To determine potential differences between WT-IR and L973F-IR in insulin signaling, we stimulated WT-IR and L973F-IR preadipocytes with 0, 0.1, 1, 10, and 100 nM insulin for 15 minutes and assessed downstream signaling. While insulin stimulation induced robust tyrosine autophosphorylation of both receptors with dose response to insulin , 49 sites were equally upregulated (category I-A) and 288 sites were equally downregulated (category II-A) in both WT-IR and L973F-IR cells in response to ligand stimulation (up- or downregulation of these sites was not significantly changed between these 2 cell lines). At the single concentration tested (100 nM), most phosphosites were regulated almost equally by both insulin and IGF-1. For example, SRSF4receptor , while Ry ligand . These omulation , D and EP < 0.05). Reactome pathway (https://reactome.org/) enrichment analysis of phosphosites upregulated more in WT-IR cells than in L973F-IR cells identified 6 pathways, including PIP3/Akt signaling and IR signaling pathways (https://www.genome.jp/kegg/pathway.html) also showed significant enrichment of proteins associated with the mTOR signaling pathway (P < 0.05). Reactome pathway analysis of these phosphosites showed enrichment of pathways associated with cell cycle, mitosis, and many SUMOylation processes . Twenty-one of these sites were downregulated by ligand stimulation to a greater extent in WT-IR cells than L973F-IR cells, including TBC1D15S201 and EIF2K4S550, which are associated with intracellular trafficking and translational control  were preferentially stimulated by WT-IR compared with L973F-IR. Similarly, many phosphosites associated with mTORC1 signaling  and several phosphosites related to PIP3-activated Akt signaling  were more highly upregulated by WT-IR than L973F-IR. On the other hand, many phosphosites on proteins associated with cell cycle and mitosis  and several phosphosites associated with MAPK signaling  were more highly upregulated by L973F-IR than WT-IR. Four phosphosites showed opposite regulation by ligand between WT-IR and L973F-IR. RICTORS1234 and RANBP2S2709 were upregulated by ligand in WT-IR cells, but downregulated by ligand in L973F-IR cells, while the converse was true for PAK4S174 and NUP153S335. Several of these changes in the phosphoproteomics were confirmed by immunoblotting using phosphosite-specific antibodies, including phosphorylation of mTORS2481 and S6S235/236, which were more highly upregulated by WT-IR than L973F-IR, while phosphorylation of c-JunS73 was more highly upregulated by L973F-IR than WT-IR , mitosis, kinesin action, and SUMOylation  was not regulated by ligand, but was significantly higher in the basal state in cells expressing WT-IR versus L973F-IR, and phosphorylation of 140 sites on 109 proteins (category III-B) was significantly higher in the basal state in L973F-IR than in WT-IR cells. The former included GRB10CCNE2S21 , A and BCCNE2S21 . This reCCNE2S21 . PathwayCCNE2S21 . On the Oylation . Thus, iP53 and P21 were not different under basal conditions between WT-IR and L973F-IR preadipocytes, they were downregulated more in L973F-IR cells than in WT-IR cells after insulin stimulation for 6 hours  and cholesterol synthesis  by insulin in WT-IR preadipocytes was severely blunted in L973F-IR preadipocytes  between male WT and L973F-IR mice, at least over the first 5 months of life . Both tyY608 and AktS473 in skeletal muscle of L973F-IR mice compared with WT control mice   . We also-IR mice . On the -IR mice , as with-IR mice , F and G-IR mice , H and I-IR mice , J and K-IR mice , L and M-IR mice , despite-IR mice . The higInsulin and IGF-1 are major regulators of metabolism and systemic growth both in vivo and in vitro . Thus, iSeveral studies have shown that the NPEY motifs in the juxtamembrane region of the IR and IGF1R have key roles in the recruitment of the immediate substrates of IR, including IRS-1/2 and Shc , 16, 17.We find that in cells, this results in a reduction in IRS-1/PI3K/Akt/mTORC1-mediated signaling with even more marked upregulation of Shc/Gab1/MAPK signaling and phosphorylation of cell cycle–related proteins. Global phosphoproteomics analysis also reveals the differences in signaling by L973F substitution, including decreased phosphorylation of proteins involved in the SUMOylation process and increased phosphorylation of proteins involved in apoptotic signaling and mRNA splicing. These signaling alterations associated with the L973F-IR result in decreased insulin-induced glycolysis and increased cell growth rate in L973F-IR cells. These data are in agreement with our recent phosphoproteomic analysis of the IR versus the IGF1R themselves . Thus, mIn addition to substrate binding, the NPEY motif in both IR and IGF1R is known to be involved in receptor internalization , 22. PreIn addition to the insulin-stimulated differences in protein phosphorylation, many phosphosites detected in the phosphoproteomics are altered under basal conditions by changing leucine at position 973 to phenylalanine. Indeed, many of the phosphosites upregulated by L973F-IR in the basal state were on proteins associated with cell cycle and mitosis. We have previously shown that, in addition to its classical signaling pathway, the unoccupied IR can exert some ligand- and tyrosine kinase–independent effects , 40. ForTo fully explore the role of the L973F mutation of the IR, we created a knockin mouse in which the normal receptor was replaced by this mutated receptor in all tissues. Previous studies have shown that enhanced IGF-1 signaling can result in increases in tissue weight and somatic growth –45. For While the L973F-IR shifts the signaling pattern from a more metabolic to a more mitogenic pattern, the effects of L973F-IR on growth in vivo were modest. This may be due to the existence of an intact IGF1R in both WT and knockin mice as well as effects from both ligands, insulin and IGF-1, which could at least partially compensate for their downstream signaling effects. Some in vivo studies have shown that blocking both insulin and IGF-1 downstream signaling by deletion of both IR and IGF1R result in obvious phenotypes, which are not obvious in single deletion of IR or IGF1R , 48. ForAltered downstream signaling by the IR with the L973F substitution is certainly in large part mediated by the decrease in IRS-1 binding/phosphorylation and increase in Shc binding/phosphorylation, as shown in this study. We have previously shown that this is based on the differences in structure of the SH domains of these two different receptor substrates . This stIn summary, we have demonstrated that a single amino acid replacement of leucine-973 in the juxtamembrane region of IR to phenylalanine, which is the equivalent residue in the IGF1R, is sufficient to lead to a decrease of IRS-1/PI3K/Akt/mTORC1 signaling and an increase of Shc/Gab1/MAPK cell cycle signaling. At the cellular level, these signaling alterations lead to decreases in insulin-induced glycolysis and increases in cell growth. Mice with knockin of the L973F-IR show similar alterations in signaling in vivo, and this leads to impaired insulin sensitivity, modest increases in growth, and decreases in weight gain on HFD. Thus, leucine-973 in the +1 position following the NPEY motif in the juxtamembrane region is a key residue differentiating IR signaling from IGF1R signaling. This study explains a big part of the differences between IR and IGF1R signaling and may provide important insights into how to modify these signaling pathways for therapy of disease.S473 , AKT pan , p-ERK1/2T202/Y204 , ERK1/2 , p-ShcY239/240 , Shc , p-Gab-1Y627 , Gab-1 , p-mTORS2481 , mTOR , p-c-JunS73 , c-Jun , p- p-S6S235/236 , S6 , p-JNKT183/Y185 , and JNK  were purchased from Cell Signaling Technology. Anti-IRβ antibody  was purchased from Santa Cruz Biotechnology Inc. Anti–p-IRS-1  antibody , anti–IRS-1 antibody , and anti-vinculin antibody (MAB3574) were purchased from MilliporeSigma. Human insulin was purchased from MilliporeSigma. Human IGF-1 was purchased from PeproTech. The human IR (B isoform) retroviral plasmid was generated previously in the lab (Antibodies against phosphorylated IRβ (p-IRβ)/IGF1Rβ , IRβ , IGF1Rβ , β-actin catalog 4970), GAPDH , p-AKT70, GAPDHIR/IGF1R DKO brown preadipocytes were obtained as previously described , 40. DKOOocyte isolation from C57BL/6 and pronucleus injections were performed at the Transgenesis Core Facility (TCF) of the Max Planck Institute (MPI) for Biology of Ageing. To prepare gRNAIR, 5 μg crRNA (GCTCACCATCACTGGCACTG) was mixed with 10 μg tracrRNA heated to 95°C for 5 minutes and then cooled down to room temperature. To exchange codon CTC of the IR encoding leucine-973 to codon TTC encoding phenylalanine-973, we performed pronucleus injections. Injection solution was prepared as follows: 20 ng/μl gRNA-IR was incubated with 20 ng/μl Cas9 protein for 15 minutes at room temperature to generate the ribonucleotide complex RNP. Subsequently, a single stranded repair template that had 100 bp homologous regions 5′ and 3′ to the modifications was added at 20 ng/μl (AAATGTCGAACAATCCATTCCTAATTTATATAGCATTTGCCTATGTCCAGAATGCCATGGGATGTTCAAGATGTTGTGTCTCTCTTCCTCCATTAGGCAGCCGGATGGGCCAATGGGGCCCCTGTATGCATCTTCAAACCCTGAGTAttTCAGTGCCAGTGATGGTGAGCATCACCTCCTTCTTTGTGGGAATCCAGAACCCAGCCCTTGGTTTTCTTTGCTATCACTGTTAAGTCAGATCTGAGGATAGGCTAGCATCACAGGG). All reagents were obtained from IDT. gRNA-mediated Cas9 double-strand break of genomic DNA between codons tyrosine-972 and leucine-973 should initiate homologous-directed repair using the ssDNA repair oligo, thereby mutating the PAM sequence, exchanging codon leucine-973 to phenylalanine-973, as well as inserting silent point mutations at codons glycine-962 and proline-963 to generate an ApaI restriction site for genotyping. Offspring were genotyped with a common PCR reaction using primers 5′-CCCTCACTTCCTCTAATTTGGACA-3′ and 5′-CACTATGTAAAGTCAAACCCAGT-3′ to result in a 658 bp fragment for both WT and L973F-IR mice. Subsequent restriction digest of PCR fragments with ApaI resulted in 141 bp and 516 bp fragments when positive for the F973 modification, whereas nonmodified WT DNA did not contain the ApaI site and thus still showed a 658 bp band upon ApaI digestion. PCR products from offspring were subcloned and Sanger sequenced and confirmed the correct codon L973F exchange in IR exon 15 as well as the ApaI site at glycine-962/proline-963. All mice were kept on a C57BL/6N background and housed at 22°C on a 12-hour-light/12-hour dark cycle with ad libitum access to water and food . HFD  was purchased from Research Diets (D-12492). For the intraperitoneal ITT, mice were fasted for 6 hours and injected with insulin at 1 U/kg/BW for male mice fed a normal diet, 0.8 U/kg/BW for female mice fed a normal diet, or 1.6 U/kg BW for male mice fed HFD. For the IPGTT, mice were fasted for 6 hours before injection of glucose at 2 g/kg/BW. For the intraperitoneal PTT, mice were fasted overnight before injection of pyruvate at 2 g/kg/BW.INSR, 5′-CGATATGGTGATGAGGAGCTGC-3′ and 5′-GTAGAAATAGGTGGGTTCCGTCCA-3′. Mouse primers used for qPCR are listed in Total RNA was isolated from cells using TRIzol reagent (Thermo Fisher Scientific). cDNA was synthesized and then quantitative PCR (qPCR) amplification was conducted with the C1000 Thermal Cycler  using iQ SYBR Green Supermix (Bio-Rad). The sequences of primers were as follows: human g for 15 minutes at 4°C and supernatants were collected. Protein concentrations were measured using the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific).WT-IR and L973F-IR preadipocytes were FBS starved for 6 hours with DMEM containing 0.1% BSA, then stimulated with insulin for 15 minutes. After stimulation, cells were washed once with ice-cold PBS and collected in RIPA buffer (MilliporeSigma) supplemented with protease and phosphatase inhibitors (BioTools). Cell lysates were then centrifuged at 20,000Proteins were transferred to polyvinylidene difluoride (PVDF) membranes. Membranes were then blocked in Starting Block T20 solution (Thermo Fisher Scientific) at room temperature for 1 hour, washed 3 times with PBS with Tween-20 (PBST), and incubated with an appropriate dilution of the primary antibody  in Starting Block T20 solution overnight at 4°C. Membranes were washed with PBST and incubated with an appropriate dilution of secondary antibody in Starting Block T20 solution for 1 hour. Sheep anti-mouse HRP-conjugated antibody  was purchased from MilliporeSigma, and goat anti-rabbit HRP-conjugated antibody  was purchased from Bio-Rad. Membranes were washed with PBST, and signals were detected using chemiluminescent HRP substrates (Thermo Fisher Scientific).2 for 1 hour. Extracellular acidification rate (ECAR) values were measured in the basal state, after injection of glucose, oligomycin and 2-deoxyglucose (2-DG). The quantitative value was normalized by the respective protein content. Brown preadipocytes were differentiated, and lipid accumulation was quantified by oil red O staining as described previously  according to the protocol of the Agilent Seahorse XF Glycolysis Stress Test Kit . Brieflyeviously .2PO4, 1 mM MgSO4, 1 mM CaCl2, 120 mM NaCl, 10 mM NaHCO3, 30 mM HEPES, pH 7.4) for 20 minutes. Cells were then treated with insulin at final concentrations of 0, 1, 10, or 100 nM for 20 minutes. Glucose uptake was assessed using 2-NBDG (Thermo Fisher Scientific) at a final concentration of 100 μM for 1 hour. After incubation, cells were washed twice with PBS and the signal read using a fluorescence plate reader at excitation of approximately 465 nm and emission of approximately 540 nm. Plasma and liver cholesterol levels were measured using Total Cholesterol Assay Kits . Plasma and liver triglyceride levels were measured using the Triglyceride Colorimetric Assay Kit .Cells were FBS starved for 6 hours with DMEM containing 0.1% BSA and incubated with KRH buffer . The MS proteomics raw data and the corresponding processing reports generated in this study have been deposited in the ProteomeXchange Consortium database  via the PRIDE .HN designed research, performed experiments, analyzed the data, and wrote the manuscript. WC, BBB, and AKG helped with experiments and reviewed and edited the manuscript. FTW generated the mouse model. NJWA and MS performed phosphoproteomic analysis. HP and JMD performed bioinformatics analysis. MM supervised phosphoproteome analysis. CRK designed research, wrote the manuscript, and supervised the project.


Emerging variants of concern (VOC) raise obstacles in shaping vaccination strategies and ending the pandemic. Vaccinated SARS-CoV-2 convalescence shapes the current immune dynamics. We analyzed the SARS-CoV-2 VOC-specific cellular and humoral response of 57 adults: 42 convalescent mRNA vaccinated patients (C+V+), 8 uninfected mRNA vaccinated (C-V+) and 7 unvaccinated convalescent individuals (C+V-). While C+V+ demonstrated a superior humoral SARS-CoV-2 response against all analyzed VOC  compared to C-V+ and C+V-, SARS-CoV-2 reactive CD4+ and CD8+ T cells, which can cross-recognize the alpha, delta and omicron VOC after infection and/or vaccination were observed in all there groups without significant differences between the groups. We observed a preserved cross-reactive C+V+ and C-V+ T cell memory. An inferior humoral response but preserved cross-reactive T cell memory in C+V- compared to C+V+ was observed, as well as an inferior humoral response but preserved cross-reactive T cell memory in C+V- compared to C-V+. Adaptive immunity generated after SARS-CoV-2 infection and vaccination leads to superior humoral immune response against VOC compared to isolated infection or vaccination. Despite the apparent loss of neutralization potential caused by viral evolution, a preserved SARS-CoV-2 reactive T cell response with a robust potential for cross-recognition of the alpha, delta and omicron VOC was detected in all studied cohorts. Our results may have implications on current vaccination strategies. The emergence of numerous VOC since the late 2020 sustains the COVID-19 pandemic and challenges our immunological and virological understanding of the SARS-CoV-2 virus, both being crucial for shaping health policies and vaccination strategies. Waning of neutralizing antibodies (NAb) 3-4 months after vaccination or infection has been documented, challenging the achievement of sterilizing immunity .Independent studies demonstrate that spike (S) mutations can lead to loss of T cell recognition or presentation of some epitopes restricted by common HLA alleles enhancing potentially immune escape –10. HoweSARS-CoV-2 immune dynamics are shaped by the immune status of different subpopulations depending on their contact with SARS-CoV-2 antigens; a) vaccinated uninfected, b) vaccinated infected, c) convalescent unvaccinated, d) uninfected unvaccinated and finally e) immunocompromised individuals. Emerging data begin to draw the cellular and humoral responses against VOC in unvaccinated convalescence, vaccinated convalescence, or vaccinated adults separately –19. HoweWe used peripheral blood mononuclear cells (PBMCs) and serological samples from 42 vaccinated convalescent COVID-19 individuals (further referred as C+V+), 8 vaccinated uninfected with SARS-CoV-2 adults (further referred as C-V+) and 7 unvaccinated convalescent (further referred as C+V-) individuals.https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Virologische_Basisdaten.html;jsessionid=93905B429A0980A796F15E1AA070EF2C.internet102?nn=13490888#doc14716546bodyText14).As we studied convalescent subjects, a direct molecular sequencing of the viral variant responsible for SARS-CoV-2 infection was not possible. Therefore, we determined the viral variants that the study participants were infected with, relying on temporal viral spreading defined by epidemiologcal trends in Germany. The SARS-CoV-2 diagnosis for the C+V+ and C+V- participants was set between June 2020 and May 2021. According to epidemiological data of the Robert Koch Institute alpha variant drove and overrepresented SARS-CoV-2 infections in Germany for the first half of 2021 . A part of the patient data was included in the research article "Increased migratory/activated CD8+ T cell and low avidity SARS-CoV-2 reactive cellular response in post-acute COVID-19 syndrome (PASC)" currently under consideration for publication. Written informed consent was obtained from all participants. Demographic and clinical characteristics are provided in As previously described , peripheex vivo is in As previously described, PBMCs were plated in 96-U-Well plates in RPMI 1640 media (Life Technologies) , 22. EacHuman IgG autoantibodies against the SARS-CoV-2 nucleocapsid (N) protein were detected using commercial ELISA kits (EUROIMMUN) according to the manufacturer’s instructions.As previously described , for theFlow cytometry data were analyzed using FlowJo version 10.6.2 (BD Biosciences); gating strategies are presented in via RT-PCR on recruitment. The C-V+ study group was seronegative for N-SARS-CoV-2 IgG, excluding an asymptomatic SARS-CoV-2 infection in the past. Most individuals 93% (n=39) experienced moderate COVID-19 during the acute phase of COVID-19 disease without need for hospitalization, whereas only 7% (n=3) were severely or critically ill and hospitalized.Our study group comprised 42 vaccinated convalescent COVID-19 individuals (further referred as C+V+), 8 vaccinated individuals without previous COVID-19 (further referred as C-V+) and 7 unvaccinated COVID-19 convalescent (further referred as C+V-) individuals. All study participants had a negative SARS-CoV-2 nasal swab tested 67% (n=28) of the C+V+ individuals received one anti-SARS-CoV-2 mRNA vaccination after the SARS-CoV-2 infection, 29% (n=12) 2 vaccinations and 4% (n=2) 3 vaccinations. All C-V+ individuals received 3 anti-SARS-CoV-2 mRNA vaccinations.The median time since COVID-19 convalescence for the C+V+ study group was 11 months (range 7-16 months). The median time since the last vaccination was 4 and 5 months for the C+V+ and C-V+ study group, respectively (range 1-8 & 2-5 months respectively). 71% (n=30) of the C+V+ study group was infected with the WT whereas 29% (n=12) with the alpha variant.The median age of the C+V+ study group was 48.5 years (range 19-68 years), whereas the control cohort was significantly younger, with a median age of 30 years . The C+V+ and C-V+ cohorts comprised of 69% (n=29) and 88% (n=7) female participants, respectively and showed no significant gender difference . The demographic and clinical characteristics of the study cohorts are presented in Up to date, humoral immunity and more concrete high titers of neutralizing antibodies are considered the pylons of protection against SARS-CoV-2 infection . TherefoA similar pattern of humoral immunity was found for the C-V+ cohort    Figure 1At last, we compared the S-reactive T cell responses among the C+V+ and C-V+ study groups for all analyzed VOCs. We stimulated overnight PBMCs with the pool of delta S mutant peptides, their corresponding position in WT pool of peptides (Dref), the pool of omicron S mutant peptides, their corresponding position in WT pool of peptides (Oref), the complete sequence of alpha S mutant or WT S-protein. First, we analyzed the frequencies of SARS-CoV-2 reactive CD4+ T cells. We found similar frequencies of WT, delta and omicron reactive CD4+ T cells, further referred as C+V-. We found significantly higher titers of NAb against all studied VOC among the C+V+ individuals compared to the C+V-     Figure 1Next, we analyzed the SARS-CoV-2 reactive cellular response among the C+V+ and C+V-. We detected WT, alpha, delta and omicron reactive CD4+ and CD8+ T cells with similar frequencies between the two cohortsFigure 4To address the interesting question of VOC cross-recognition inside each study group separately we performed a reanalysis of our data. We demonstrate similar frequencies of WT, alpha, delta and omicron CD4+ & CD8+ reactive T cells in C+V+ individuals  , 23. We As next we assessed the reactive T cell response among the C-V+ study group. In the same line with the C+V+ group, we detected similar frequencies of WT, alpha, delta and omicron reactive CD4+ and CD8+ T cells . Overall, the analysis of the C+V+ and C-V+ cohort independent from each other, revealed cross-reactive TCM, TNAIVE, TEM, TEMRA CD4+ and CD8+ memory subsets, recognizing equally all tested peptides . The patients/participants provided their written informed consent to participate in this study.KP, NB, MA and US participated in research design. KP, MK, MZ, JJ and SD participated in data curation and sample acquisition. KP and NB participated in the writing of the paper. NB, OW, TW and US participated in funding acquisition and project administration. KP, MA, TM, SP and AK participated in the performance of the research. NB, TW, OW and US contributed new reagents or analytic tools. KP, NB and MA participated in data analysis. All authors contributed to the article and approved the submitted version.This work was supported by grants of Mercator Foundation, EFRE grant for COVID.DataNet. NRW, AiF grant for EpiCov, and BMBF for NoChro (FKZ 13GW0338B).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


PMID: 36245705; PMCID: PMC9520332, authors requested to replace In the published article Mao W, Wang S, Chen R, He Y, Lu R, Zheng M. lncRNA NORAD promotes lung cancer progression by competitively binding to miR-28-3p with E2F2. Open Med. (Wars) 2022 Sep 28;17(1):1538–1549. doi: After publication, the authors found out that due to their negligence, the image of A549 cell invasion after the treatment of si-NORAD + pcDNA3.1 was wrongly used as the image of A549 cell invasion after the treatment of si-NC of The correct


Triticum aestivum L.) based production systems is citically important to maximize profitable production with minimal negative environmental impacts. We investigated the effects of different fertilizer-N  and fertilizer-K  application rates on wheat productivity, nutrient (N and K) use efficiency viz. partial factor productivity (PFPN/K), agronomic efficiency (AEN/K), physiological efficiency (PEN/K), reciprocal internal use efficiency (RIUEN/K), and profitability in terms of benefit-cost (B-C) ratio, gross returns above fertilizer cost (GRAFC) and the returns on investment (ROI) on fertilizer application. These results revealed that wheat productivity, plant growth and yield attributes, nutrients uptake and use efficiency increased significantly (p<0.05)with fertilizer-N application, although the interaction effect of N x K application was statistically non-significant (p<0.05). Fertilizer-N application at 120 kg N ha-1 (N120) increased the number of effective tillers (8.7%), grain yield (17.3%), straw yield (15.1%), total N uptake (25.1%) and total K uptake (16.1%) than the N80. Fertilizer-N application significantly increased the SPAD reading by ~4.2–10.6% with fertilizer-N application (N80-N240), compared with N0. The PFPN and PFPK increased significantly with fertilizer-N and K application in wheat. The AEN varied between 12.3 and 22.2 kg kg-1 with significantly higher value of 20.8 kg kg-1 in N120. Fertilizer-N application at higher rate (N160) significantly decreased the AEN by ~16.3% over N120. The N120treatment increased the AEK by ~52.6% than N80 treatment. Similarly the RIUEN varied between 10.6 and 25.6 kg Mg-1 grain yield, and increased significantly by ~80.2% with N120 as compared to N0 treatment. The RIUEK varied between 109 and 15.1 kg Mg-1 grain yield, and was significantly higher in N120 treatment. The significant increase in mean gross returns (MGRs) by ~17.3% and mean net returns (MNRs) by ~24.1% increased the B-C ratio by ~15.1% with N120 than the N80 treatment. Fertilizer-N application in N120 treatment increased the economic efficiency of wheat by ~24.1% and GRAFC by ~16.9%. Grain yield was significantly correlated with total N uptake , K uptake (r = 0.851**), SPAD value (r = 0.945**), green seeker reading (r = 0.956**), and the RIUEN (r = 0.910**). The artificial neural networks (ANNs) showed highly satisfactory performance in training and simulation of testing data-set on wheat grain yield. The calculated mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) for wheat were 0.0087, 0.834 and 0.052, respectively. The well trained ANNs model was capable of producing consistency for the training and testing correlation  between the predicted and actual values of wheat grain yield, which implies that ANN model succeeded in wheat grain yield prediction.The development of robust nutrient management strategies have played a crucial role in improving crop productivity, profitability and nutrient use efficiency. Therefore, the implementation of efficient nutrient management stratigies is important for food security and environmental safety. Amongst the essential plant nutrients, managing nitrogen (N) and potassium (K) in wheat ( Triticum aestivum L.) is extensively utilized in human consumption and has high rank globally among the most essential cereals grown worldwide. It accounts for ~30% of all cereal food worldwide and staple food for ~10 billion people in ~43 countries of the world [Wheat  is absorbed in large amount than any other element  and playThe apparent recovery of nutrients from applied fertilizers for cereal crops is typically low , 29. Rec3—N) to the shoots of the plant and transports it later on to the aerial plant parts, which in turn increases the activities of N [4+/NO3− ratios and K supply levels influence the yield and nutrient uptake of wheat [While extensive research has explored wheat crop response to fertilizer-N, P, and K over the years , 37 but ies of N , 42. Theies of N . In addiof wheat . Therefop<0.05) increased the number of effective tillers and non-effective tillers during 2 study years, while fertilizer-K application did not increased the number of effective tillers of wheat  with N120 compared with N0. The interaction effect of fertilizer-N and K application on yield attributes of wheat was statistically non-significant. Fertilizer-N application increased the root dry weight up to fertilizer-N application rate of 120 kg N ha-1, and thereafter there was no change in the root dry weight  with N120, compared with N0. Similarly, straw yield did not increased significantly with N160 than the N120. The fertilizer-N and K application did not significantly increase the harvest index of wheat. The interaction effect of fertilizer-N and K on wheat grain and the harvest index was non-significant. Fertilizer-K application at K90 resulted in significant increase in wheat straw yield. Wheat grain yield increased significantly up to N to N160 . Data po160 compared with N120 during the second years, but non-significantly during the first year. Data pooled for two study years revealed that grain N uptake was significantly increased with N160 than the N120. Grain-N uptake was increased by ~3.5 and 4.0-times with N120 and N160, respectively over the N0. As compared with N120, N160 resulted in ~15.5% increase in grain N uptake by wheat. The highest straw N uptake was observed with N240; although N120 and N160 increased the straw N uptake by ~2.8 and 3.1-times than the N0. The total N uptake by wheat varied between 33.3 and 158.4 kg ha-1; showing an increase of ~3.8 and 4.0-times with N120 and N160 over N0.Fertilizer-N application significantly increased the grain, straw and total (grain + straw) N uptake by wheat during the study years . Grain N160 resulted in only ~6.7% increase in total N uptake by wheat. It was important to note that fertilizer-K application did not result in significant change in total N uptake by wheat. The interaction effect of fertilizer-N and K application was statistically non-significant.These results revealed that increased fertilizer-N rate of N80-N240), compared with N0 (160) the SPAD reading increased by ~2.3%, compared with N120. Fertilizer-K application did not significantly change the SPAD reading. The green seeker value followed the similar trend to that of the SPAD reading, with no significant change due to fertilizer-K application. Fertilizer-N application significantly increased the SPAD reading by ~4.2–10.6% with fertilizer-N application . These results showed that wheat straw K uptake was significantly increased with N120; followed by non-significant change at higher fertilizer-N rates. The total K uptake followed the similar response to fertilizer-N application, with highest K uptake at N120. Data pooled for different study shows that there was non-significant difference in grain, straw and total K uptake with different rates of fertilizer-K application. Nonetheless, the interaction effect of fertilizer-N and K on K uptake by grains and straw was non-significant.Fertilizer-N application resulted in a significant increase in K uptake by grains and straw . Data poN decreased significantly with increased fertilizer-N application rate in wheat, but do not differ significantly with the application of fertilizer-K , compared with N120. The AEN varied between 12.3 and 22.2 kg kg-1 with significantly higher value of 20.8 kg kg-1 in N120. Fertilizer-N application at higher rate (N160) significantly decreased the AEN by ~16.3% over N120. The two year pooled data showed that PEN was significantly higher with N120 by ~44.6% than the N240. It was important to observe that PEN did not differ significantly among N120 and N160. The RIUEN varied between 10.6 and 25.6 kg Mg-1 grain yield, and increased significantly by ~80.2% with N120 as compared to N0 treatment. The RIUEN did not differ significantly among N120 and N160. The effect of fertilizer-K and interaction effect of fertilizer-N and K was statistically non-significant for PFPN, AEN, PEN and the RIUEN.The PFPilizer-K . Data poK increased significantly with fertilizer-N and K application in wheat (-1 increased the PFPK by 38.3 kg ha-1 (~76.9%), compared with the N0 treatment. However, the PFPK did not differ significantly among different fertilizer-N application rates (N80-N240). The PFPK was highest at K30 and decreased by ~2-times with K60 treatment. Fertilizer-N application at N120 increased the AEK by ~52.6% than N80 treatment. Similarly, K30 treatment had the highest, while the K90 had the significantly lower AEK. The PEK was highest in N160, which was ~19.8% higher than N120 treatment. The PEK did not differ significantly with fertilizer-K application at different rates. The RIUEK varied between 109 and 15.1 kg Mg-1 grain yield, and was significantly higher in N120 treatment. The effect of fertilizer-K and interaction effect of fertilizer-N and K on RIUEK of wheat crop statistically non-significant.The PFPin wheat . Fertili120 treatment compared with the N0. There was non-significant change in available-N content in soil with fertilizer-N application rates of N120, N160, N200 and N240. Fertilizer-K application had non-significant effect on available-N content in soil. Available-K content in soil was highest in N120treatment, and was ~8.3% higher than N0 . Fertilizer-N application at 120 kg N ha-1 (N120) resulted in significantly higher MNRs by ~24.1% than the N80 treatment. The B-C ratio was significantly increased by ~66.1% with N120 than the N0 treatment. The higher fertilizer-N application rates (N160-N240) resulted in ~1.4–3.4% increase in B-C ratio of wheat. The economic efficiency of wheat increase by ~24.1% with N120 than N80 treatments; however, the higher fertilizer-N application rates did not significantly increase the economic efficiency. The GRAFC varied between 835 and 1550 US$ ha-1; a significantly higher returns  were obtained under N120 than N80. The ROI of 66.9 US$ gross returns US$-1 cost were significantly higher by ~84.8% in N120 than the N240 treatment. At lower fertilizer-N application rate (N80), the ROI although increased by ~23.3%, but were statistically non-significant.The MCCIs varied between 364 US$ hain wheat . The MGRp<0.01), straw N uptake , grain K uptake , straw K uptake , total N uptake value  and total K uptake  (p<0.01), green seeker reading , RIUEN . We tested different regression models  . Wheat gn models  to improN and RIUEK and the wheat grain yield. We applied back propagation neural networks technique, self-organizing map (SOM) neighbour weight distance and ANNs consisted of several layers of neurons which are inter-connected and then the weights were assigned to those inter-connections  between the predicted and actual values of wheat grain yield, which implies that ANN model succeeded in wheat grain yield prediction. A back propagation neural network with Levenberg Marquardt algorithm was used to establish the relationship between the input variables viz. grain N uptake, straw N uptake, grain K uptake, straw K uptake, total N uptake, total K uptake, SPAD value, green seeker value, RIUEnections . The SOMp<0.05) increased the number of effective and non-effective tillers during 2 study years, while fertilizer-K application did not increased the yield attributing characters of wheat. The total number of tillers increased as a function of N application rates across all levels of K rate, but peaked up at 120 kg N ha-1. This could be major contribution of N towards cell division, elongation and enhancing the vegetative growth, and K contribute in promoting vigorous plant growth through efficient photosynthesis [The fertilizer-N application significantly , the wheat yield would not significantly increase, but there was no-significant decline. Therefore, similar to previous research [0 control. However, the amount of N absorbed by crops on crop yield is affected by genetic and environmental factors, compromising the relationship between fertilizer-N application rate and its accumulation in the crop [-1, the N utilization by plants were nearly negligible and exposed to leaching, volatilization and immobilization losses. These results illustrates that combination of 120 kg N ha-1 with 30 kg K ha-1 increased the ability of plants for capturing resources and increased dry matter accumulation. In the present study, the effect of higher dose of fertilizer–K application (K60-90) or the interaction effect of fertilizer-N and K was statistically non-significant (p<0.05). The soils of studied region in north-western India are mostly containing smectite and illitic clay minerals [-l each in alluvial plain with occasional sand dune and alluvial plain with sand dune, respectively [Fertilizer-N fluxes in agro-ecosystems are important for assessing the effectiveness for wheat yield and in determining probable environmental contamination , 52. Theresearch , these rthe crop . Unfortuthe crop . This stminerals . When K ectively .-1 as compared to higher rates of fertilizer-N application. Different rates of fertilizer-K application was showed non-significant difference in grain, straw and total K uptake. When the fertilizer-N application rate exceeds crop demand, the quantity of applied fertilizer-N used by the crops is reduced, and a larger amount of applied N remains in the soil or is lost [3—N in soil could be reduced by applying less amounts of fertilizer-N than or equal to that required for the optimal crop yield [Fertilizer-N application significantly increased the grain, straw and total N uptake by wheat during the study years up to 120 kg N ha is lost . In cont is lost . Therefoop yield , 60.80-N240), compared with N0. Viana and Kiehl [-1.The chlorophyll fluorescence parameters were used to estimate the function of photosynthetic apparatus and carbon assimilation rate due to its sensitivity, accessibility and non-intrusive features , 62. Thend Kiehl  reportednd Kiehl  assessed160-N240) significantly decreased the N use efficiencies over N120. However, the K use efficiency did not differ significantly among different fertilizer-K application rates. These results corroborate earlier research findings of highest N use efficiency at the lower rate because of less losses [-1) substantially decreased the N use efficiency compared to that at lower fertilizer-N application rate (52.5 kg N ha-1). Therefore, fertilizer-N use efficiency should be improved by farmers’ to decrease the use of high fertilizer-N rate application. Generally, NO3—N is the major source of soil N absorbed by crops [3—N [120, suggesting the ideal management for higher wheat yield in this region. The increased plant dry weight and chlorophyll content is positively correlated with photosynthesis and plant growth [Nitrogen use efficiency is represented with N recovered efficiency in the crops and has a significant impact on air and water quality, biodiversity, and human health , 68. Thes losses , 71. At s losses  and Meses losses  reporteds losses , if a uns losses , the higby crops  and the by crops . Therefoops [3—N . In our ops [3—N  and decrops [3—N , increasops [3—N , and parops [3—N . Numerouops [3—N , 83, 84,ops [3—N , 85, 86.t growth . It has t growth . The lowkharif crops and reported that these machine learning approach has out-perform simulation abilities. Shastry et al. [Increasing synchronization between N needed by the crop and fertilizer N supply is crucial for improving N use efficiency. Applying N when demand by the crop is high will not only increase yield but also N use efficiency . Ali et y et al.  comparedy et al.  reportedy et al.  reportedTypic Ustochrept sandy loam soil at the experimental farm of the Punjab Agricultural University, Ludhiana, Punjab (30°56′N and 75°52′E) in the Indo Gangetic Plains (IGPs) in the north-western region of India. The surface soil (0–15 cm) layer was non-saline  with pH1:2 = 7.40 (1:2 soil: water), Walkley and Black-C = 3.46 g kg-1, available-N = 52.9 kg ha-1; 0.5 M NaHCO3-extractable P = 17.9 mg kg-1 and 1 N NH4OAc-extractable K = 139.8 mg kg-1. The study region has a sub-tropical climate, with hot, wet summers and cold dry winters. Annual mean rainfall is ~760 mm, ~80% of which received in monsoon season extending between July and September. Mean minimum and maximum temperatures (averaged across 30 years) during wheat (November to April) are 6.7°C and 22.6°C and in rice (June to October) are 18°C and 35°C, respectively.A 2-year field experiment (2013–14 and 2014–15) on irrigated wheat was established in 2013 starting on a -1 (N0-N240), and sub-plots treatments consisted of four fertilizer-K application rates of 0, 30, 60 and 90 kg Kha-1(K0-K90). These treatments were assigned to the same experimental plots in all the years of the study.The experiment was laid out in a split plot design with three replications and consisted of six fertilizer-N application rates in main-plots and four rates of fertilizer-K rates in sub-plots. The main-plot treatments consisted of six fertilizer-N application rates of 0, 80, 120, 160, 200 and 240 kg N ha-1) and K  rates as urea (46% N) and muriate of potash (60% K2O). One-third of total fertilizer-N, and whole amount of fertilizer-P and fertilizer-K were drilled at wheat sowing each year. The remaining ~2/3rd of fertilizer-N (as per treatment) was applied in two equal split doses immediately before first irrigation at 3 weeks and second irrigation applied at 8 weeks after sowing. Wheat was irrigated (~75 mm each) at crown root initiation, maximum tillering, panicle initiation and dough stages as recommended for the crop in the region.Wheat crop received a different fertilizer-N  soil layer were collected after the completion of two years study period. Soil samples were dried in shade and were ground and sieved through 2 mm stainless steel sieve, and stored in plastic bottles until analysis. Soil samples were analyzed for available-N and K. The grain and straw samples collected at maturity were oven-dried at 65°C for 48 h to a constant weight and ground to pass through a 0.5 mm screen. The total N and K contents were determined by micro-kjeldahl method and using flame photometry methods, respectively.N/PFPK), agronomic efficiency of N and K (AEN/AEN), physiological efficiency of N and K (PEN/PEK) and the reciprocal internal use efficiency of N (RIUEN/RIUEK) were estimated using Eqs -1) and the total amount of fertilizer added (kg ha-1) using Eqs -1) in fertilizer-N and K added plots and the control (no-N/no-K) to the amount of fertilizer-N/fertilizer-K added (kg ha-1) using Eqs -1) of fertilizer N/fertilizer-K applied and the control (no-N/no-K) to that of difference in total (grain + straw) N and K uptake (kg ha-1) from fertilizer applied and the control  by grain to the biological yield   Eqs , 16.The ANNs competent of learning the data-set used during the training step, and then validate and train the network with parts of the initial data set that is used during the training step –107. TheWhere, `n`= actual number of inputs, `w`= weight of the connection of the nodes that are `I`and `j`, `x`= input from `j`and `bi`= bias. The node outputs `oi`was computed from the transfer function `fi`using weighted values .Xi’ to the weights ‘In back propagation neural network, input layer neurons distribute input ‘function .Zj’ = activationfunction, ‘∂j’= non-linear activation function used in a hidden layer and could be a hyperbolic tangent, sigmoid or logistic function. ‘P’= input number, ‘h’= symbol for hidden layer and ‘γj’= jth error term.Where, ‘The ANN forecasting model is formulated as ϕ’ is the transfer function, ‘Wji’ = weights describing connections between the ‘ith’node of the input layer and the ‘jth ’node of the hidden layer, ‘θj’ = biases related to the hidden layer, ‘th’node of the hidden layer and node of the output layer and ‘θ0’ = bias at the output layer. Therefore, to apply θ’. In the present study, ANNs provided with Levenberg–Marquardt training algorithm and hyperbolic tangent sigmoid transfer functions was used as a point of reference to examine model inputs in terms of root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE).Where, ‘-1) of the experimental data-set, ten different input layers  were used as input variables. The wheat grain yield was chosen as desired output parameter. The experimental data (pooled for two study years) were randomly divided into two sets viz. training data set (70%) and testing data set (30%).To simulate wheat grain yield (Mg ha-1), e.g., seed, fertilizers, insecticides, fungicides, herbicides, etc. and labor cost for different field operations (The mean cost of cash inputs (MCCIs) was estimated as sum of expenditure incurred for the purchase of inputs  under different treatments and minimum support price (MSP) of produce  fixed by Government of India (US$ Mg-1) (The mean gross returns (MGRs) were estimated as a product of grain yield (Mg haS$ Mg-1) .Mean net returns (MNR) were estimated as the difference in MGR and MCCI .MCCIs, MGRs and MNRs were computed by converting Indian Rupee (INR) to United States Dollar (US$), considering 1US$ = 70 INR.-1) and price of N, P and K (US$ kg-1) as per treatment (The benefit-cost (B-C) ratio was estimated as a ratio of MGRs and the MCCIs. The gross returns above the fertilizer cost (GRAFC) for wheat were estimated as the difference in between MGRs and amount (A) of N, P and K applied (kg hareatment .(N+P+K) ’represents amount of N+P+K applied and ‘price(N+P+K)’represents the market price of N+P+K. These estimations were based on market price of US$ 84.4 and 242.9Mg-1 for urea and MOP, respectively.Where, ‘A-1) from crop under different fertilizer treatments by crop duration (d)  .The returns on investment (ROI) on fertilizers were estimated as a ratio of MGRs and total cost of fertilizers using p<0.05 using IRRISTAT package [2), RMSE, MAE and MAPE were calculated using following equations  and the differences between the means of treatment were separated by the least significant difference at the level of significance  package . The corions Eqs –26. The 2) was tested using students’ T and F-test, respectively.Where, ‘n’= number of data points in the data set and ‘t’= actual output, ‘z’= predicted output. The significance of regression coefficients (slope and intercept) and coefficient of determination (RHigher N fertilizer application ensured higher crop yield and N accumulation, cause potential N losses and pollute source, but was not necessary to achieve optimal crop production. However, an increase in N supply did not affect the grain yield by increased K fertilization under sufficient available-K content in illitic soils. The higher rate of N and K fertilizer application decreased nutrient use efficiencies and fertilizer productivity. It is essential to increase NUE by reducing the input of N fertilizer and increasing the N absorption of crops, and to improve the sustainability of crop production. This study would help policy makers consider artificial neural network model and economic indices of wheat production suitable for up-scaling and large-scale adoption by smallholder farmers.


Immunoglobulin G (IgG) N-glycans have been shown to be associated with the risk of type 2 diabetes (T2D) and its risk factors. However, whether these associations reflect causal effects remain unclear. Furthermore, the associations of IgG N-glycans and inflammation are not fully understood.We examined the causal associations of IgG N-glycans with inflammation (C-reactive protein (CRP) and fibrinogen) and T2D using two-sample Mendelian randomization (MR) analysis in East Asian and European populations. Genetic variants from IgG N-glycan quantitative trait loci (QTL) data were used as instrumental variables. Two-sample MR was conducted for IgG N-glycans with inflammation  and T2D risk .P = 0.0019; and 1.013 for T2D per 1-SD higher GP13, 95% CI = 1.006–1.021; P = 0.0005. In the European population, genetically determined decreased GP9 was associated with T2D . In addition, there was suggestive evidence that genetically determined IgG N-glycans were associated with CRP in both East Asian and European populations after correcting for multiple testing, but no associations were found between IgG N-glycans and fibrinogen. There was limited evidence of heterogeneity and pleiotropy bias.After correcting for multiple testing, in the East Asian population, genetically determined IgG N-glycans were associated with a higher risk of T2D, the odds ratios (ORs) were 1.009 for T2D per 1- standard deviation (SD) higher GP5, 95% CI = 1.003–1.015; Our results provided novel genetic evidence that IgG N-glycans are causally associated with T2D.The online version contains supplementary material available at 10.1186/s10020-022-00543-z. Type 2 diabetes (T2D) is a chronic disease characterized by relative insulin deficiency and peripheral insulin resistance with a high societal burden  studies, which use genetic variants as instrumental variables for exposure, can further support causality due to their randomly allocated nature and circumvent confounding and reverse causation  in East Asian and European populations Fig. . The twoIn the East Asian population, information on genetic variants associated with IgG N-glycan was collected from IgG N-glycan quantitative trait loci (IgG N-glycan-QTL) summarized data  associated with IgG N-glycans were identified as instrumental variables (IVs). The selected SNPs were independent, namely, not in linkage disequilibrium (R2 < 0.001). Independently associated SNPs (P < 5 × 10–8) with IgG N-glycans were selected in European ancestry. Because few genetic variants were available, referring previous studies  was used to select SNPs in the East Asian population. Then, the F_statistic (beta2/se2) was applied to evaluate the strength for each SNP, and SNPs with less statistical power (F-statistics < 10) were removed to avoid weak IV bias.Independent SNPs (low linkage disequilibrium (LD), RP value threshold for 24/17 exposures (P < 0.002/0.003) was used to indicate statistical significance. P < 0.05 but above the Bonferroni corrected significance threshold was considered as suggestive evidence for a potential association. All analyses were performed with R (version 4.0.2) with the “TwoSampleMR” and “MendelianRandomization” packages.First, two-sample MR analyses were performed to disentangle the potential associations of IgG N-glycans and T2D. For MR analyses, conventional inverse variance weighting (IVW) . However, no significant effects of genetically predicted GP5 and GP22 on T2D were observed in WM and PWM estimates (Table Ps > 0.05), except GP5, GP7, and GP17 . And the results of IVW are reliable from the results of directional pleiotropy of GP9 on T2D . The MR-Egger and Cochran’s Q method detected few evidences of directional pleiotropy and heterogeneity among each GP for CRP and fibrinogen  using two-sample MR study in East Asian and European populations, respectively. The MR results showed that increased genetically predicted IgG N-glycans of GP5 and GP13 were associated with a higher risk of T2D in the East Asian population, and genetically predicted decreased GP9 was associated with a higher risk of T2D in the European population. In addition, there were suggestive associations of genetically predicted IgG N-glycans on CRP both in East Asian and European populations.Several previous observational studies have investigated that the associations between IgG N-glycans and risk of T2D  in the PhenoScanner v2. Table S3. Genetic variants used to instrument GPs in East Asian population. Table S4. Genetic variants used to instrument GPs in European population.Additional file 2: Table S1. Description of glycans structures of 24 glycan peaks. Table S6. Mendelian randomization (MR) estimates of IgG glycans with fibrinogen from different MR methods in East Asian population. Table S7. Mendelian randomization (MR) estimates of IgG glycans with CRP from different MR methods in European population.


The functional assessments in 2D and 3D cell culture assays showed that TCR-T cells mounted a polyfunctional response to the cognate HCV peptide target in tumor cell lines, including killing. Collectively, we report a solid strategy for the efficient large-scale manufacturing of TCR-T cells.Cellular immunotherapies based on T cell receptor (TCR) transfer are promising approaches for the treatment of cancer and chronic viral infections. The discovery of novel receptors is expanding considerably; however, the clinical development of TCR-T cell therapies still lags. Here we provide a pipeline for process development and clinical-scale manufacturing of TCR-T cells in academia. We utilized two TCRs specific for hepatitis C virus (HCV) as models because of their marked differences in avidity and functional profile in TCR-redirected cells. With our clinical-scale pipeline, we reproduced the functional profile associated with each TCR. Moreover, the two TCR-T cell products demonstrated similar yield, purity, transduction efficiency as well as phenotype. The TCR-T cell products had a highly reproducible yield of over 1.4 × 10 In addi bedside . ACT has bedside –5. Furth bedside , 7. ThesThe manufacturing of genetically engineered T cells (CAR or TCR) is a multistep process consisting in the isolation of mononuclear cells, activation of T cells to favor susceptibility for the subsequent genetic  engineering, expansion of genetically modified cells, product harvesting, and cryopreservation . Good ma1073–1081, and TCR-69, specific for the HLA-A2-restricted epitope NS51992–2000, respectively—to be used as proof of principle in the process development of a novel clinical-grade manufacturing protocol that will definitely have future applications for the manufacturing of TCR-T cells targeting other antigens.Our group has previously isolated TCRs targeting hepatitis C virus (HCV) antigens and has demonstrated their effectiveness in redirecting T cells from healthy donors (HD) and chronically HCV-infected patients , 20. In We performed process optimization from the research laboratory setting to clinical-grade manufacturing using the CliniMACS Prodigy system, a fully closed, automated, flexible, and user-defined platform that enables reproducible, scalable, and clinical-grade manufacturing of cell products with a single-use tubing system . Moreoven = 3) and chronically infected patient (n = 1) were collected at the Karolinska University Hospital under informed consent and isolated using Ficoll-Hypaque (GE) density-gradient centrifugation. Ethical permission was obtained from the Regional Ethical Review Board (EPN) of the Karolinska Institutet.Human peripheral blood mononuclear cells (PBMCs) from healthy blood donors , HCV NS5A , and HIV peptide SLYNTVATL are referred to as NS31073-1081 or NS51999-2000 (Immudex) were used.PBMCs and T cells were analyzed by flow cytometry (FACS) after staining with fluorochrome-conjugated monoclonal antibodies (mAb). The following antibodies were used: CD3 BUV650 (Biolegend), CD4 BV711 (Biolegend), CD8 BV570 (Biolegend), CD62L PE (BD Bioscience), CD45RO APC (BD Bioscience), anti-mouse TCRβ (mTCR) FITC (Invitrogen), CD25 PE-CF594 (BD Bioscience), CD69 PE (BD Bioscience), and PD-1 BB700 (BD Bioscience). Immune-cell composition and purity were determined using the following antibodies: CD3 BUV805 (BD bioscience), CD4 PE-Cy5.5 (Thermofisher), CD8 BV395 (BD Bioscience), CD14 BV711 (BD Bioscience), CD19 BV510 (BD Bioscience), and CD56 APC (BD Bioscience). Cell viability was determined by live and dead cell markers (Invitrogen) added freshly to each panel mix for 10 min at 4°C in the dark prior to staining with mAbs. The staining of cells was performed in 0.01M phosphate-buffered saline supplemented with 2% fetal bovine serum (FACS buffer) for 20 min at 4°C in the dark. To confirm the correct pairing and surface expression of the murine TCRs transferred into human T cells, APC-labeled HLAA*0201 dextramers refolded with HCV NS3For intracellular multicolor flow cytometry staining, TCR-transduced T cells were incubated for 6 h with the indicated stimuli. GolgiPlug and GolgiStop (BD Biosciences) were added during incubation. PMA and ionomycin (Sigma) were used as positive controls at 50 ng/ml and 1 ug/ml, respectively. The cells were then washed in FACS buffer and stained with the following: CD3 BUV650 (Biolegend), CD4 BV711 (Biolegend), CD8 BV570 (Biolegend), anti-mouse TCRβ (mTCR) FITC (Invitrogen), CD107a BUV395 (BD Biosciences), interleukin 2 (IL-2) PE (BD Biosciences), tumor necrosis factor α (TNFα) PE-Cy7 (BD Biosciences), and interferon γ (IFNγ) APC (BD Biosciences). A BD Cytofix/Cytoperm fixation/permeabilization kit was used after the staining procedure. Data acquisition was performed on a BD Symphony flow cytometer using FACS Diva Software (BD Biosciences). Data were analyzed using FlowJo 10 software.Third-generation lentiviral vectors pRRLSIN.cPPT.MSCV.WPRE harboring HCV NS3- or NS5-specific TCRs driven by the murine stem cell virus (MSCV) U3 promoter were produced as previously described by ; the par6 white blood cells per milliliter. For freezing, the cells were stored at -80°C using a freezing container  for 24 h and transferred afterwards for long-term storage in liquid nitrogen. After thawing, the cells were immediately washed in GMP-grade TexMACS medium (Miltenyi) supplemented with 1 ug/ml DNase Pulmozyme (Roche) and reformulated in 40 ml TexMACS medium. The cell suspension was transferred into a 150-ml transfer bag (Miltenyi) and connected to the installed tubing set. Activation, transduction, and expansion of T cells were performed on the CliniMACS Prodigy using Tubing set TS520 (Miltenyi), and the T cell transduction (TCT) process was chosen as the template process.Peripheral blood mononuclear cells were isolated from buffy coats by density gradient centrifugation and cryopreserved in 90% FBS and 10% dimethylsulfoxide (Sigma) at a density of 50 × 106 PBMCs in a total volume of 70 ml of TexMACs GMP medium supplemented with premium-grade human recombinant IL-2, IL-15, and IL-21 cytokines (Miltenyi). TransAct CD3/CD28 reagent kit (Miltenyi) was used for 24-h activation as recommended by the manufacturer. On the following day, the cells were transduced with lentiviral particles, at multiplicity of infection (MOI) = 5, diluted in 10 ml of TexMACs GMP medium, and 10 μg/ml Vectofusin was allocated in a 20-ml transfer bag, which was attached to the CliniMACS Prodigy by sterile welding. The vector was then automatically transferred to the culture chamber, and the vector bag was further rinsed with 20 ml of the medium to bring to a total culture volume of 100 ml. Residual TransAct and lentiviral vector were removed by an automated culture wash 24 h after incubation. The cells were then expanded for 8 days before being harvested. Sampling was performed on days 4, 7, and 8 for in-process controls, including cell count, cell viability, transduction efficiency, and phenotyping. At the end of the expansion (day 8), the cells were automatically collected in 100 ml TexMACS medium and transferred into a sterile bag. For the final cellular product, the samples were taken for flow cytometry analysis to determine the purity, T cell phenotype, transduction efficiency, and safety quality controls. Small-scale experiments were performed with the same reagents in tissue culture plates to validate parameters such as cell expansion, cell viability, transgene expression, phenotype, and functionality of the transduced T cells.On day 0, cultivation was initiated with 200 × 10®-PTS™ system, according to the manufacturer’s instructions. All samples tested with the Endosafe system used 0.05–5.0 endotoxin unit/ml sensitivity cartridges provided by Charles River. BacT/ALERT®3D microbial detection system (BioMérieux) was used to detect fungal and aerobic and anaerobic bacterial contamination. G-band karyotyping was performed by a validated G-band assay at the laboratory of Clinical Genetics in Karolinska University Hospital. A total of 25 G-banded metaphases were analyzed.Microbiological examination according to Ph. Eur. 2.6.27 was performed in the final cell product on day 8. Mycoplasma testing was performed by PCR provided by an analytical company . The endotoxin levels were measured using the Charles River EndosafeDroplet digital PCR (ddPCR) was performed using the Bio-Rad QX200 system according to the manufacturer’s protocols (Bio-Rad). The ddPCR reaction mixture consisted of 10 μl of 2 × ddPCR master mix (Bio-Rad), 60 ng genomic DNA, and 20× primers/probes mix targeting RRE (FAM), a Rev response element sequence located upstream of the MSCV promoter in the integrated lentiviral genome . Primers5 cells/well in a ratio of 1:1 with T2 cells loaded with different concentrations of NS3 and NS5 peptides . T2 cells loaded with HIV peptide  were included as a negative control. After 6 h of coculture, the intracellular content of human IL-2, TNFα, IFNγ, and CD107a in the TCR-transduced T cells was evaluated by intracellular multicolor flow cytometry staining.The TCR-transduced T cells were incubated in a U-bottom 96-well plate (Corning) with 1 × 104 cells of the indicated target cells in a ratio of E/T 1:1. PMA and ionomycin (Sigma) at 50 ng/ml and 1 ug/ml, respectively, were used as positive controls after 6 h of incubation. Supernatants were harvested after 24 h, and concentrations of human IL-2, IL-6, IL-10, IL-17, IL-4, TNFα, and IFNγ in the supernatants were analyzed by Milliplex map human high-sensitivity T cell magnetic bead panel assay (Merck) according to the manufacturer’s instructions.The T cell products were rested overnight in a culture medium without cytokine. On the next day, the cells were cocultured overnight in 24-well tissue culture plates with 10For the 2D experiments, both Lunet HCV+/HLA-A2+ and Lunet HCV+/HLA-A2- cells were cocultured with transduced or mock non-transduced T cells in different E/T ratios . Following 24 h of coincubation, the medium was replaced with luciferin solution (Promega) prior to imaging with a charge-coupled device camera. Signals from bioluminescent Lunet HCV+/HLA-A2+ and Lunet HCV+/HLA-A2- cells were analyzed with the Living Image Software, version 4.2, and IVIS Spectrum instrument . The aspartate transaminase (AST) levels in supernatants were quantified by a validated AST assay at the Clinical Chemistry Laboratory of the Karolinska University Hospital, Solna, Sweden, using the Modular P apparatus .2 incubator for 48 h for the formation of a single spheroid in each well. For the 3D tumor cell death analysis, spheroids were stained with Annexin V green reagent (1:200) (Sartorius) for 15 min at room temperature prior to the coculture experiments. The TCR-transduced T cells were seeded in a ratio of E/T at 1:1, and cell viability and cell death evaluations were performed by the acquisition of imaging green fluorescence across time using the Incucyte S3 system (Sartorius). Single pictures of each well were acquired every hour for 5 days and analyzed using Incucyte software, version 2019B.For the 3D experiments, both Lunet HCV+/HLA-A2+ and Lunet HCV+/HLA-A2- cells were stained in 1 µM Calcein-AM (Invitrogen) diluted in fresh medium for 30 min at 37°C prior to spheroid formation by seeding 30,000 cells per well in a Costar ultra-low attachment round-bottom 96-well plate (Corning). For the 3D assays, cells were cultured in a humidified 37°C, 5% COt-test was used for the comparisons between two groups. Two-way ANOVA was used to compare multiple groups. A p-value <0.05 was considered to be significant.Data are displayed as the mean ± SEM analyzed with Prism version 8.0 (GraphPad Software). Unpaired Student’s 1073 and NS51992 of HCV  and from a chronically HCV-infected patient (KS6) as described above. The cell expansion, phenotype, transduction efficiency and functionality of TCR-redirected T cells were evaluated. Lentiviral particles encoding the NS3- and NS5-specific TCRs were used, at 24 h post-activation, to transduce T cells from HLA-A2 healthy donors and a chronically HCV-infected patient with a MOI of 5.6 ± 0.42 × 106) and cell viability (92.50% ± 0.85) of the expanded T cells was observed between the healthy donors and the HCV-infected patient. A drop in cell viability was observed in both cell sources after 4 days of expansion due to the selective T cell survival after activation by Transact  and in the HCV-infected patient (48% ± 2.30) compared to 23.75% ± 1.27 and 29.35% ± 3.1 CD8+ T cells in healthy donors and the HCV-infected patient, respectively . All runs were performed using the CliniMACS Prodigy Tubing Set TS 520, which was installed on the CliniMACS Prodigy. Each individual run included PBMC isolation by Ficoll gradient followed by the indicated steps outlined in n = 3) previously tested in small-scale experiments. Transduction was performed with lentiviral particles harboring NS3- (n = 2) and NS5-specific TCRs (n = 1) added by sterile welding of the supply bag after 24 h of activation with TransAct reagent (Miltenyi). The feeding conditions were optimized to support 8 days of cell expansion by increasing the volume of media exchange. Parameters such as total cell number, cell viability, T cell activation, transduction efficiency, purity, and T cell exhaustion were evaluated.To validate our protocol on the CliniMACS Prodigy, large-scale experiments were performed using cryopreserved PBMCs from healthy donors   compared to cells from the starting material on day 0 (29.66% ± 1.45)  compared to 39.33% ± 10.11  in CD8+ T cells  and transcription factor 7 that, in humans, encodes for the T cell factor 1 (TCF1) protein . CCR7 ex1073-1081 and NS51999-2000 peptides for 6 h. As shown in To assess the functional capabilities of TCR-redirected T cells, we stimulated both NS3-specific and NS5-specific transduced T cells with T2 target cells pulsed with titrated amounts of NS3Considering the distinct functional profiles of NS3- and NS5-specific TCRs previously described , 29, we After 24 h of incubation, supernatants from cocultures at 1:1 E/T ratio of NS3- and NS5-specific TCR-T cells and Hu7/Lunet cells were used to quantify the cytokines secreted by activated T cells. Both NS3- and NS5-specific TCR-T cells secreted pro-inflammatory cytokines associated with an effector/T helper 1 (TH1) phenotype such as IFNγ, TNFα, and IL-2 in response to their target antigen, whereas cytokine secretion was hardly detectable upon coculture with control Lunet HCV+/HLA-A2- or in the absence of a stimulus . These rTo further verify the efficiency of our protocol in generating functional TCR-T cells after a large-scale production, a cytotoxicity assay was implemented against Lunet HCV+ replicon cells previously engineered to express the firefly luciferase under the HCV replicase activity , 22. LucFurthermore, supernatants from cocultures at 1:1 E/T ratio were used to quantify AST secreted by Huh-7/Lunet HCV replicon cells. A significant increase of hepatocellular AST was detected in the coculture supernatants from NS3-specific T cells coincubated with Lunet HCV+/HLA-A2+ . Furthermore, for image-based quantification of cell viability in 3D cultures, spheroids cocultured with both NS3- or NS5-specific TCR-T cells were analyzed for cell viability in 3D cultures To further examine if cell viability reduction was related to apoptosis, we performed Annexin V staining followed by fluorescence-activated cell intensity measurement using Incucyte. Concurrently with the reduced cell viability, cell apoptosis, as indicated by Annexin V green fluorescent binding cells, dramatically increased in Lunet HCV+/HLA-A2+ spheroids following the addition of NS3-specific TCR-T cells compared to the control conditions. As shown in These results altogether reinforce the differences between NS3- and NS5-specific TCR-T cells in terms of cytotoxic activity: NS3-specific TCR-T cells are prone to induce the cytolysis of target cells, while NS5-specific TCR-T cells favor a non-cytotoxic mechanism. These findings support the previously described observations regarding NS3- and NS5-redirected T cells generated in a small scale by other methodologies, such as transient mRNA transfection or retroviral transduction , 29. ThuACT, as a therapeutic approach, holds great promise for cancer therapy and chronic viral diseases. However, these therapies also face challenges in terms of a standardized, reproducible, and economically feasible manufacturing process, where safety and efficacy have to be guaranteed within multiple regulatory frameworks. Genetically engineered T cells represent a complex biological living product, where quality depends not only on donor-to-donor variation but also on the manufacturing environment and the quality of complementary raw materials and reagents .In this study, we reported for the first time the effectiveness of the lentiviral gene transfer approach to redirect human T cells with TCRs specific for two well-characterized human cytotoxic T cell epitopes with clinical relevance in hepatitis C infection –42. In oOur goal is to provide a simple, robust, and feasible manufacturing pipeline that can be used in academic settings to produce several TCR-T cell products maintaining the functional characteristics of each TCRs but providing reliable transduction efficiency, expansion, and phenotype.6 TCR+T cells/kg, which is similar to what has been used for other hepatitis-specific TCR-T cell products , which are the best candidates for a sustained response . In addifunction .As previously described, TCF1 is a key transcription factor of the Wnt signaling pathway, playing a pivotal role in peripheral T cell fate designation . Early aex vivo cell expansion process in which the cells are artificially and strongly pushed to proliferate. Therefore, given the relevance of T cell phenotype for clinical response, an in-depth and thorough characterization of TCR-transduced T cells is eagerly needed to possibly identify a more reliable panel of optimal T cell attributes for adoptive cell therapy in cancer and chronic viral infections.Despite the encouraging results in terms of the phenotype of the manufactured cells, we believe that the simple analysis of the commonly used surface markers might be difficult to interpret during the TCR-T cells were assessed for functionality and potency with multiple assays, spanning from peptide-loaded targets to HCV replicon cells, in 2D and 3D culturing conditions. Our results indicate that the cells were biologically functional and responded to the target cells in an antigen-specific manner. The observed polyfunctional profiles in response to the processed antigen support the results obtained with peptide-loaded T2 cells in which NS3-TCR activation stimulates IFNγ, IL-2, and TNFα in a dose-dependent manner, whereas NS5-specific CD8+ T cells predominantly expressed IFNγ, and no hepatocellular injury was observed. Notably, NS3-specific CD8+ cells appeared more polyfunctional than NS5-specific CD8+ cells. The ability of secreting pro-inflammatory cytokines not only is a common attribute of polyfunctional effector T lymphocytes but also has been correlated to a superior functional activity –60. Thesin vitro 2D and 3D potency assays for the development and manufacturing phases of engineered T cells. Firstly, our results show that the luciferase activity of Lunet HCV+/HLA-A2+, expressed as bioluminescence signals, decreased in a dose-dependent manner when incubated with NS3-specific TCR-T cells according to the E/T ratio. The NS5-specific TCR-T cells appeared to be less effective in controlling HCV replication, although a reduction of bioluminescence signal could still be observed in the experiments. Thus, our finding shows that both NS3- and NS5-specific TCR-T cells trigger an HLA-A2-restricted antiviral response against HCV replicon in hepatoma cell line in a 2D culture model. Moreover, we found an increase of aspartate transaminase levels in the supernatants from NS3-specific TCR-T cells and Lunet HCV+/HLA-A2+ cell cocultures, thus indicating a cytotoxic activity of NS3-specific TCR-T cells. These results reinforce the antiviral response and hepatotoxic potential of these cells as previously described by our group.We introduced We used spheroids from our target hepatoma cell line coupled with an advanced live imaging system to follow the morphology, effector cell cytotoxicity, and tumor cell apoptosis . Our finIn conclusion the present study outlines the effectiveness of an optimized protocol for the manufacturing of TCR-T cells. Our strategy resulted in the generation of sufficient numbers of viable cells with a functional performance preserved after large-scale expansion. Importantly, the relatively rapid time of expansion and culture conditions allowed the achievement of the desired CD4/CD8 ratio in the final product together with the early differentiated memory phenotype of engineered cells. Overall, these data report a feasible and promising platform for the upcoming generation of antigen-specific TCR-T cell manufacturing.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.DNS optimized protocols, designed and conducted the experiments, and wrote the manuscript. MC assisted with protocol development, flow cytometry analysis, and lentivirus production. GR conducted the experiments and drafted the manuscript. KH cloned TCRs in lentiviral vector. AKW assisted with live cell imaging assay development and analysis. PM and FG contributed to the final version of the manuscript. MM and LM edited the manuscript and provided scientific inputs. MSC supplied PBMCs from HCV chronic patient and cell lines used in the studies. VL provided the Lunet/HCV replicon cells. MS provided study oversight. MB obtained funding and assisted with the flow cytometry panel design. AP provided study oversight, obtained funding for the project, and assisted with drafting of the manuscript. All authors contributed to the article and approved the submitted version.This study was supported by the Sjöberg Foundation (AP), Region Stockholm Centrum För Innovativ Medicin , Svenska Läkaresällskapet (AP), Cancerfonden , Ruth och Richard Julins Stiftelse (AP), Vinnova project CAMP (contract no. 2017-02130) (MS), the EU-funded project ERINHA (MS), Swedish Science Council (MB and MS) and Region Stockholm ALF grant (MS), and the Deutsche Forschungsgemeinschaft  (VL).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Therefore, immunohistochemistry was used to assess PD-L1, CD8+ T-cell, and the immune activation marker Granzyme B (GrB) in PCa tissue before and under ADT. In line with previous studies, few prostate cancer tissues showed PD-L1 expression and CD8+ T-cell infiltration. However, PD-L1 expression levels on tumour cells or infiltrating immune cells above 5% generated an immune-suppressive tumour microenvironment harbouring hypofunctional CD8+ T-cells. Moreover, analysis of a longitudinal patient cohort before and under ADT revealed that ADT increased hypofunctional CD8+ T cells in the tumour area suggesting a tumour immune milieu optimal for targeting with immunotherapy.Immune checkpoint inhibitors have become a promising new therapy for cancer treatment. However, due to prostate cancer’s high heterogeneity and immune-suppressive tumour microenvironment, clinical trials with immune checkpoint inhibitors for prostate cancer resulted in low or no response. This descriptive and retrospective study investigates the influence of androgen deprivation therapy (ADT) on PD-L1 expression and CD8 Most paDue to its relatively low somatic mutation frequency and few tumour-infiltrating T cells, PCa belongs to the class of immunologically cold tumours . Therefo+ T-cells, are associated with response to checkpoint inhibitors in several tumour entities such as melanoma and ovarian carcinoma  in PCa tissue before and under ADT.As the immune milieu in the tumour microenvironment plays an essential role in responding to immune checkpoint inhibitors, a deeper understanding of the influence of modulation of the androgen receptor on the immune milieu signalling pathways is mandatory. Therefore, this descriptive and retrospective pilot study aims to analyse the influence of ADT on PD-L1 expression and CD8The patient’s cohort has previously been described in The tissue blocks were cut in serial sections of 1–2 µm thickness and deparaffinised with a BenchMark XT , followed by heat-induced epitope retrieval. The PD-L1  antibody  has been used in a 1:100 dilution for staining, followed by counterstaining with hematoxylin, dehydration, and mounting of the slides. The PD-L1 clone E1L3N is one of the most commonly used antibodies for PD-L1 and exhibited high specificity for PD-L1 testing .PD-L1-stained slides were scored for PD-L1 immune cell (IC)-positivity (percentage of tumour area covered by stained IC) and PD-L1 tumour cell (TC)-positivity (percentage of positive PD-L1 TC in the tumour area). The data was analysed by senior pathologists specialising in PD-L1 evaluation in various tumour entities. PD-L1 IC-positivity was defined as staining in granulocytes, lymphocytes, macrophages and dendritic cells of any intensity within the tumour area. PD-L1 TC-positivity was defined as membranous PD-L1 staining of any intensity in all detectable tumour cells on the slide. In addition, the combined positive score (CPS) was determined, which is calculated as the total number of PD-L1 positive TC and IC in the tumour area divided by the total number of viable TC multiplied by 100% . PD-L1 e+ cells were quantified first (red chromogen) and, in a second step, those cells that also showed GrB were counted from the CD8+ cells (brown chromogen).The immunoreactions for the T-cell population were digitised with a Panoramic Scan II , followed by a pathologist’s manual quantification of the cells. Quantification was done within the peritumoral stroma. To assess peritumoral stroma, the hot spot method was used and up to three high power fields (HPF) with the highest density of immune cells within the peritumoral stroma were chosen and analysed. Since this immunohistochemical test is a double reaction, CD8p-values of ≤0.05 were considered statistically significant. Kaplan-Meier estimate has been used for overall survival analysis. The Pearson correlation coefficient (r) has been calculated and interpreted suggested by Schober et al. for correlation analysis .Prism 9.3.1  was used for all statistical analyses. Differences between treatment groups were analysed using ordinary one-way ANOVA or Student’s t-test. analysis . All dif+, and GrB are displayed in + T-cells  cells is associated with an increase in CD8+ T-cells activity (+ T-cells activity (+ T-cells (1–4%) was associated with a significant activity increase . Kaplan-Meier survival analysis revealed no significant difference in OS for PD-L1 negative (<1%) TC patients and PD-L1 positive (≥1%) TC patients  would be a nice add on as TMB had been connected to immunotherapy response rates (This retrospective descriptive study analysed PD-L1 and CD8se rates . Moreove