We combine information from the binding free energy calculations, molecular docking, and molecular dynamics simulations to investigate the interactions of both aptamers with TNF-α. The results reveal that the RNA aptamer has a more stable structure relative to the DNA aptamer. Interaction of aptamers with TNF-α does not have any negative effect on its structure. The results of molecular docking and molecular dynamics simulations suggest that the RNA aptamer has a stronger interaction with the protein. Also, these findings illustrate that basic residues of TNF-α establish more atomic contacts with the aptamers compared to acidic or pH-neutral ones. Furthermore, binding energy calculations show that the interaction of the RNA aptamer with TNF-α is thermodynamically more favorable. In total, the findings of this study indicate that the RNA aptamer is a more suitable candidate for using as an apta-biosensor of TNF-α and, therefore, of greater potential use for the diagnosis of blood infections. Also, this study provides more information about aptamer-protein interactions and increases our understanding of this phenomenon.Interest in the design and manufacture of RNA and DNA aptamers as apta-biosensors for the early diagnosis of blood infections and other inflammatory conditions has increased considerably in recent years. The practical utility of these aptamers depends on the detailed knowledge about the putative interactions with their target proteins. Therefore, understanding the aptamer-protein interactions at the atomic scale can offer significant insights into the optimal apta-biosensor design. In this study, we consider one RNA and one DNA aptamer that were previously used as apta-biosensors for detecting the infection biomarker protein TNF- Patiγ) , and tumγ) [α) –11.α is one of the most promising candidates [α (TNF-α) is an important proinflammatory cytokine that contributes to acute phase reaction. Although TNF-α can be secreted by many cell types such as NK cells eosinophils, neurons, CD4+ lymphocytes, neutrophils, and mast cells, it is secreted primarily by macrophages [α is a subordinate member of the TNF superfamily which embodies different types of transmembrane proteins with a homology domain [α is secreted after cleavage of a 76-residue peptide from the amino terminus of the prohormone and the mature protein contains single intramolecular disulfide bridge [α to be a trimer in solution [α subunit is a β-sheet sandwich constructed almost entirely of antiparallel β-strands.The multiple proinflammatory cytokines are identified as possible biomarkers of blood infection , and TNFndidates , as its ndidates . Tumor nrophages . TNF-α iy domain . Mature e bridge . Previousolution , 15. Thesolution , 17. Theα in sepsis, many bioassays have been targeting its molecular structure with various probes to reveal its presence in serum [α, including fluorescence immunoassay, enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, and time-resolved immune-fluorometric assay, is, thanks to a number of commonly used traditional immunoassays, easy to detect and quantify [Due to the known involvement of TNF-in serum . TNF-α, quantify , 20. Nevα targeting. Aptamers are actually recognized as high-affinity and high-specificity biomolecule binding agents. These oligonucleotides are characterized by their modifiability and their potential to introduce affinity and signal transducing moieties into the same molecule. Aptasensors with analyte capturing and signal transducing potential have already been addressed in the literature [Aptamers are single-stranded DNA or RNA oligonucleotides that have been developed as powerful and reasonably priced alternatives to traditional antibodies for TNF-terature , 22. Detterature , 24.Analytical and numerical methods can provide further insight into observed biologically oriented experiments or biological phenomenon, which are difficult to study experimentally –29. Amonα, with aptamer candidates (DNA and RNA) via molecular dynamics (MD) method. For this purpose, two-dimensional (2D) and three-dimensional (3D) structures of aptamers were calculated and were optimized through a 200 ns MD simulation. In the next step, the interactions of these aptamers with different sides of the TNF-α protein were investigated using molecular docking and MD simulations and binding free energy calculations. The results of this study provide useful information for identifying an aptasensor with high selectivity and affinity to TNF-α.In this study, we investigate the interactions of TNF-α. The structure of TNF-α was obtained from the RCSB database (PDB id: 1TNF) [α were modeled by the SWISS-MODEL web tool and, then, simulated for 200 ns [α [In this study, we studied the interactions of two DNA and RNA aptamers with TNF-d: 1TNF) . The misr 200 ns , 34. On 00 ns [α , 36. The25-mer DNA: 5′-TGGTGGATGGCGCAGTCGGCGACAA-3′.28-mer RNA: 5′-GGAGUAUCUGAUGACAAUUCGGAGCUCC-3′.α conformation.The secondary structures of DNA and RNA aptamers were predicted by the use of the Mfold  web servIn order to obtain the basic information about the possible binding locations of aptamers to protein, we performed molecular shape complementarity docking using the PatchDock  web servAll the simulations in the present investigation were performed via the GROMACS 5.1.4 package . Also, tThe interactions between the protein (nonpolar and polar) can be determine via the binding free-energy evaluation and other biological macromolecules. The binding free-energy was calculated by using the MM-PBSA method and the g_mmpbsa tool –58.Gnonpolar) and the polar (∆Gpolar) interaction free-energy differences, the overall binding free-energy (∆G) was obtained as the following:Gpolar and ∆Gnonpolar are given byBy adding the nonpolar (∆Gps and ∆Gnps are the difference of the polar and nonpolar solvation energies, respectively. Also, ∆GvdW  is the difference of the energy related to the van der Waals interactions, and ∆Gelec stands for the difference of the energy associated with the electrostatic interactions. 500 snapshots taken from the last 100 ns of each aptamer-protein complex simulation were used in these binding free-energy calculations.where ∆α [G energy of folding for DNA and RNA aptamers is -4.81 kcal/mol and -10.6 kcal/mol, respectively. Many previous computational studies used the RMSD as a parameter to illustrate the equilibration of the system. Hence, in order to investigate the stability of conformations arrived at by our MD simulations, the RMSD value was computed for C-α in TNF-α and the backbone atoms of aptamers. The resulting RMSD time trajectories are illustrated in α, due to their structural features that make them more flexible than proteins [Based on the previous studies, we selected two aptamers that have specific interactions with TNF-α , 36. Theα  web servα  web servproteins .G energy of folding. In total, the RNA aptamer has a more stable structure than the DNA aptamer. Also, previous experimental works have shown that the RNA folded structure has more stability than the single-strand DNA folded structure [In tructure . Furthertructure  conductetructure  conductetructure –58.α in terms of identifying the possible binding locations of aptamers to the protein, we performed molecular docking computations using the PatchDock server. Many previous studies have used the PatchDock server to investigate the interaction of nucleic acids with proteins [α, RNA aptamer, and DNA aptamer were extracted from the last snapshot of the prior MD simulations and used for performing docking computations. For each RNA-protein and DNA-protein complex, we selected two clusters with a higher score relative to other clusters. More detailed information from the docking computation results is shown in α than the DNA clusters. The RNA aptamer had more interface area with TNF-α, which shows that more nucleotides of the aptamer are in the direct contacts with protein. Also, the RNA aptamer had higher binding energy with TNF-α than the DNA aptamer. The results of docking calculations are in agreement with previous experimental studies that have illustrated the RNA molecules to have stronger interactions with proteins due to the Ribose carbohydrate in their backbone [To investigate further the interactions of aptamers with TNF-proteins –65. The backbone , 67.α, but aptamers in cluster 2 interacted with one chain only. This is probably why the aptamers in cluster 2 had a smaller interface area with TNF-α relative to the aptamers in cluster 1.As shown in α interactions.The atomic coordinates of aptamer-protein complexes obtained by molecular docking calculations were used as initial conditions for subsequent molecular dynamics simulations of 200 ns duration to help refine further our understanding of aptamer-TNF-α on the structural stability of the complexes they formed, the RMSD values of each entity were computed during their interactions over 200 ns MD simulation trajectories. First, we studied the fluctuations of the TNF-α structure during interactions with aptamers. As shown in α had no major effect on the structure of the protein. For each interaction pair, the RMSD value of three TNF-α chains was calculated separately, and the average value was reported. All interaction pairs reached stable states after about 15 ns, and the fluctuations of TNF-α structure in all simulation systems were almost equal and in the range of 0.2 nm to 0.4 nm. Hence, we can conclude that bound aptamers to the protein did not have any major effect on the structure of TNF-α. These findings are in line with other experimental and computational studies [To investigating the effects of the conformational fluctuations of aptamers and TNF- studies , 71.α was also calculated. The RMSD was computed for only the backbone atoms of the aptamers. The results show that interactions with TNF-α reduced the structural fluctuations of the RNA aptamer (α are stronger, and as a result, the structural fluctuations of the aptamer are reduced. For instance, the fluctuations of RNA aptamer in the TR1 system are lower than the fluctuation of the RNA aptamer in the TR2 system (Furthermore, the RMSD value of aptamers during interactions with TNF- aptamer . In RNA-2 system , because2 system . When th2 system .α, the contact numbers between aptamers and protein were calculated during the simulation trajectories (α than the DNA aptamer. Also, the RNA aptamer in the TR1 system had the highest number of contacts between all simulation systems (For explaining the affinity binding of aptamers to TNF-ectories . Furtherectories . As show systems . These f systems .α that have in the interactions with aptamers. Previous investigations indicate that in the interactions with anionic molecules such as antimicrobial peptides and nucleic acids the basic residues in the proteins play a major role [α had higher numbers of contacts with the RNA and DNA aptamers. These findings also provide the insight that RNA aptamer interacted more strongly with TNF-α compared to DNA ones due to the more polar and less basic nature of the residues in the latter, while the number of aptamer contacts with TNF-α was comparable in both cases.Moreover, the results of the contact number analyses have shown the significant role of the basic residues of TNF-jor role , 73. In α and have a higher number of contacts which are in line with results of our molecular docking computations (α. Taken together, the number of contacts, free energy, and docking, all support the conclusion of stronger interactions with RNA. Our simulation findings are therefore congruent with the results of the previous experimental studies demonstrating the feasibility of using RNA aptamers as apta-biosensors tailored to bind target proteins with high specificity and at very low concentrations [To provide a better understanding of aptamer-protein complexes, the graphical representation of complexes at the end of the simulation was illustrated utations . In totatrations , 74.α via the g_mmpbsa tool (α and the negatively charged nucleotides. The strongest electrostatic energy was found in TR1 and the weakest one in TD2. The polar solvation energy was positive in all the simulations. In total, by taking into account the total binding energy as a parameter to represent the strength of aptamer-protein complexes, the TR1 was the strongest complex and TD2 was the weakest. The results of these binding free energy calculations are in close agreement with the previous results and confirm that the RNA aptamer had stronger interactions with TNF-α than the DNA aptamer.Previous investigations have revealed that electrostatic interactions play a key role in biological macromolecule interactions, especially when these have opposite charges , 75–77. bsa tool , the nonα at the atomic scale by binding free energy calculations, molecular docking, and MD simulations. It was observed that the folding process of the RNA aptamer had more negative ΔG energy than the folding process of the DNA aptamer. Furthermore, the results of molecular docking calculations showed that the RNA aptamer had stronger interactions with TNF-α and got a higher score relative to the DNA aptamer. Computational structural analyses illustrated that during interactions, the aptamers did not have any negative effect on the TNF-α structure. Furthermore, the structural fluctuations of aptamers were reduced during interactions with the protein. The results of binding free energy calculations and MD simulations showed that the RNA aptamer had stronger interactions with protein than the DNA aptamer. The results revealed that basic residues of TNF-α had more contacts at the atomic scale with aptamer relative to other residue types. RNA aptamers, in turn, created more contacts with protein and thermodynamically had more favorable binding energy with TNF-α. Collectively, these findings illustrated that RNA aptamers are a more suitable candidate, compared to DNA aptamers, to use for constructing an apta-biosensor for sensing the presence of TNF-α in a biological sample, which is in agreement with previous experimental studies [In this study, we investigated the interactions of RNA and DNA aptamers with TNF- studies . It is a


When a yeast cell runs out of fuel, it can increase the flux through a central metabolic pathway by simply changing the location of an enzyme. Related research article Rogers S, Hariri H, Wood NE, Speer NO, Henne WM. 2021. Glucose restriction drives spatial reorganization of mevalonate metabolism. eLife10:e62591. doi: 10.7554/eLife.62591No matter what you do for a living, organizing your workspace will help you to work efficiently. One way to do this is to have a place for everything – be it a piece of equipment in your lab or a file on your computer – but if you are lucky enough to have a job that involves performing a number of different tasks, it will help to have everything organized so that you can easily reconfigure your workspace for the task at hand.Saccharomyces cerevisiae. This structure is known as the nucleus vacuole junction or NVJ . Collectively, this shows that HMG-CoA reductase partitioning is beneficial for the cell.But how can it be useful to move an enzyme to an organelle contact site? Other enzymes involved in sterol synthesis do not move to the NVJ, indicating that the enhanced flux is not a product of substrate channeling (enzymes passing intermediary products in a pathway directly to one another without releasing them into solution). Instead, Rogers et al. found that when several molecules of HMG-CoA reductase are in close proximity, the performance of the enzyme seems to improve. To demonstrate this in vivo, they generated a mutant version of HMG-CoA reductase fused to a fluorescent protein that forms tetramers to artificially force enzyme molecules to be in close proximity. In mutant cells unable to accumulate HMG-CoA reductase at the NVJ, expressing this enzyme variant had two effects: flux through the mevalonate pathway was restored, and growth was efficiently resumed once glucose was resupplied.The NVJ is anything but a random site for placing a sterol metabolism enzyme. Ever since this contact site was discovered, many researchers have studied its role. Two decades of collaborative effort have revealed that the NVJ is involved in multiple processes related to the metabolism, transport, and storage of lipids , and tha


PHF6, a highly conserved epigenetic transcriptional regulator that is important for neurodevelopment and hematopoiesis. PHF6 serves as a tumor suppressor protein, with PHF6 mutations and deletions often implicated in the development of T-lymphoblastic leukemia and less frequently in acute myeloid leukemia and other myeloid neoplasms. PHF6 inactivation appears to be an early event in T-lymphoblastic leukemogenesis, requiring cooperating events, including NOTCH1 mutations or overexpression of TLX1 and TLX3 for full disease development. In contrast, PHF6 mutations tend to occur later in myeloid malignancies, are frequently accompanied by RUNX1 mutations, and are often associated with disease progression. Moreover, PHF6 appears to play a role in lineage plasticity within hematopoietic malignancies, with PHF6 mutations commonly present in mixed phenotype acute leukemias with a predilection for T-lineage marker expression. Due to conflicting data, the prognostic significance of PHF6 mutations remains unclear, with a subset of studies showing no significant difference in outcomes compared to malignancies with wild-type PHF6, and other studies showing inferior outcomes in certain patients with mutated PHF6. Future studies are necessary to elucidate the role PHF6 plays in development of T-lymphoblastic leukemia, progression of myeloid malignancies, and its overall prognostic significance in hematopoietic neoplasms.Next generation sequencing has uncovered several genes with associated mutations in hematologic malignancies that can serve as potential biomarkers of disease. Keeping abreast of these genes is therefore of paramount importance in the field of hematology. This review focuses on  PHF6), is a highly conserved, 365 amino acid, 41kDa protein, that was first identified in the X-linked neurodevelopmental disorder, Börjeson-Forssman-Lehmann syndrome (BFLS)  finger proteins consist of a family of epigenetic regulators that bind to a variety of targets, including both post-translationally modified and unmodified histones . The PHDe (BFLS) , 3. PHF6sequence Figure 1sequence , 4–6. Exopoiesis , 7, 8.PHF6 in general development, PHF6-homozygous knockout mice die perinatally  stem and progenitor cell-enriched populations, specifically the heterogeneous progenitor cell population (HPC-1), with an enrichment in cycling forms  complex, including CHD4, HDAC1, and Rbb4 , thereby suppressing UBF-mediated rRNA transcription , with fewer cases identified in acute myeloid leukemia (AML), and rarer cases identified in pre-malignant clonal hematopoiesis . Inactivating mutations of PHF6 have been identified in 5-16% of pediatric and 19-40% of adult patients with T-ALL and ~25% of adults with T-lymphoblastic lymphoma (T-LBL) with some groups identifying an association with NOTCH1 mutations (67%-84.6% of PHF6 mutated/deleted T-ALL with NOTCH1 mutations versus 39.8% PHF6 WT)   of early T-cell precursor subtype of T-ALL (ETP), a form of T-ALL that frequently expresses myeloid-associated markers (The PHF6 WT) –38. Copyvs 2.6%) , 33. Rec markers , 42.PHF6 plays in leukemogenesis is actively under investigation. Analyzing whole exome sequencing data from diagnostic and relapse leukemias, Wendorff et al. showed that somatic mutations of PHF6 occur early in leukeomogenesis  with T-ALLs that overexpress homeobox transcription factors, TLX1 and TLX3 , and complex karyotypes were abnormalities most often identified (q21q26.2)/t and 15.4% of cases of AML with myelodysplasia related changes (MRC)  . InteresS to AML . Furtherhe other , 57. Int1 in AML .PHF6 mutations leading to inactivation of the protein, an analysis of PHF6 expression levels in AML regardless of mutation status revealed that PHF6 protein levels are higher in patients with AML than normal controls, a finding seemingly at odds with its role as a tumor suppressor (Despite ppressor . Moreoveppressor . Decreasppressor .de novo AML identified PHF6 mutations in 6 (2%) cases with FAB subtypes of M0, M1, and M2 (PHF6 AML), with 4 of 6 succumbing to the disease. Co-genetic abnormalities included RUNX1/RUNX1T1 translocations, NUP98/KDM5A translocations, and mutations in WT1, RAS, ETV6, TET2, IDH1, and BCORL1 , as aged mice with knocked-out PHF6 exhibit megakaryocytic dysplasia and associated decreased platelet counts as well as extramedullary hematopoiesis (PHF6 mutations are relatively rare (~3%) in MDS (PHF6 mutations are found most frequently (5.3% of MDS cases) in the high-grade subtypes (MDS with excess blasts)  in MDS , 62–64.  blasts) . PHF6 muulations . The mosPHF6 mutations are rarely identified in myeloproliferative neoplasms (MPN) (0.7%), occurring in only 1.6% of chronic myelogenous leukemia , and upregulation of CD4 and T-cell signal transduction genes  and DNMT3A (23%) as the most common recurrent mutations , and have higher relapse at 2 years  compared to MPAL lacking these mutations  (PHF6 mutations in 5 patients with B/T MPAL (56%)  . FurtherAL (56%) .PHF6 mutations are believed to be early events in MPAL, as Xiao et al. found every blast population isolated from selected cases showed nearly 100% VAF  and is frequently associated with early T-ALL which frequently shows myeloid marker expression. The underlying contextual factors, including cell of origin and cooperative gene mutations, remain to be elucidated to understand what drives a PHF6-associated malignancy to be T-lineage, myeloid lineage, or a combination of both.Finally, it is becoming clear that OW conceived of the review subject matter and provided editorial review while JK primarily composed the manuscript. All authors contributed to the article and approved the submitted version.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.


Increasing evidence demonstrates that inflammatory cytokines—such as tumor necrosis factor (TNF)—are produced at low levels in the brain under physiological conditions and may be crucial for synaptic plasticity, neurogenesis, learning and memory. Here, we examined the effects of developmental TNF deletion on spatial learning and memory using 11–13-month-old TNF knockout (KO) and C57BL6/J wild-type (WT) mice. The animals were tested in the Barnes maze (BM) arena under baseline conditions and 48 h following an injection of the endotoxin lipopolysaccharide (LPS), which was administered at a dose of 0.5 mg/kg. Vehicle-treated KO mice were impaired compared to WT mice during the acquisition and memory-probing phases of the BM test. No behavioral differences were observed between WT and TNF-KO mice after LPS treatment. Moreover, there were no differences in the hippocampal content of glutamate and noradrenaline between groups. The effects of TNF deletion on spatial learning and memory were observed in male, but not female mice, which were not different compared to WT mice under baseline conditions. These results indicate that TNF is required for spatial learning and memory in male mice under physiological, non-inflammatory conditions, however not following the administration of LPS. Inflammatory signalling can thereby modulate spatial cognition in male subjects, highlighting the importance of sex- and probably age-stratified analysis when examining the role of TNF in the brain. Cytokines are a class of immunity-associated molecules that have profound effects on the brain’s response to peripheral inflammation . In addiWithin the CNS, TNF is primarily produced by the myeloid-derived microglia, and in the case of neuroinflammation, also by infiltrating blood-borne immune cells ,14,15,16Lipopolysaccharide (LPS) is an immunostimulatory glycolipid located on the outer membrane of all Gram-negative bacteria. It binds to Toll-like receptor 4 (TLR4) in conjunction with CD14, MD-2 and LPS-binding protein, which are all expressed by the microglia ,22. SeveThe aim of the present study was to examine the role of TNF in spatial cognition under physiological conditions and following LPS-induced inflammation. Based on accumulating data on the homeostatic functions of TNF, we reasoned that TNF-KO mice would be impaired in the BMT compared to WT animals. To examine whether TNF impairs cognition after peripheral immune activation, we first characterized the effects of 0.5 mg/kg LPS on sickness behavior and locomotor activity using both male and female mice. TNF-KO and WT mice were then studied in the BM at a time-point when LPS-induced sickness behavior had dissipated, to avoid potential confounding.All procedures complied with Danish law  and European Union directive 2010/63/EU, regulating animal research. Ethical permission was granted by the Animal Experimental Council (nr 2016/15-0201-00952).n = 4–8/cage), 11–13-month-old, male and female mice were employed in the studies.TNF-KO mice were originally purchased from the Jackson laboratories . The aniE. coli serotype 0111:B4, Sigma-Aldrich, Søborg, Denmark) was dissolved in sterile, phosphate-buffered saline (PBS), and administered once intraperitoneally (IP) to TNF-KO and WT mice at the dose of 0.5 mg/kg. Vehicle mice received PBS in a final injection volume of 150 µL. At least 1 week prior to experimentation, animals were transported and housed in a dedicated behavioral testing facility. Experiments were then conducted during the light phase of the light/dark cycle, between 08:00 h and 15:00 h. LPS (n = 4/group).The effects of 0.5 mg/kg LPS on sickness behavior and locomotor function in the open field test were examined using both male and female mice  with symptoms of ptosis (drooping eyelids), lethargy (curled body posture and diminished locomotion after single prompting), and piloerection  included in the score . Each syThe open field test was performed 24 h after injections, immediately after the final evaluation of sickness behavior. Animals were placed in the center of a non-transparent, square polypropylene arena (W 45 cm × D 45 cm × H 40 cm), which was illuminated by four 120 W halogen spotlights. Spontaneous locomotor activity was tracked for 10 min, by using an overhead video camera  connected to SMART video-tracking software . For®-isolated RNA (2 μg) from the hippocampus of WT, PBS and LPS-treated male and female mice was reverse-transcribed to cDNA, by using the Applied Biosystems™ high-capacity cDNA transcription kit . Samples were analyzed in triplicates on a StepOnePlus™ Real-Time PCR system . Each 20 μL sample contained nuclease-free H2O , 1× Maxima SYBR Green dye for TNF or 1× TaqMan Probe master mix for hypoxanthine phosphoribosyl transferase , 500 nM forward and reverse primers , undiluted cDNA for TNF or 10× diluted cDNA for HRPT1 (reference gene). Primer sequences for HPRT1 were: forward, 5΄-GTT AAG CAG TAC AGC CCC AAA ATG-3΄; reverse, 5΄-AAA TCC AAC AAA GTC TGG CCT GTA-3΄ and for TNF: forward, 5΄-TGG CCT CCC TCT CAT CAG TTC-3΄; reverse, 5΄-ACT TGG TGG TTT GCT ACG ACG-3΄. For each sample, relative fold differences from the mean TNF levels of unmanipulated control samples were calculated after normalisation of TNF against HPRT1 mRNA, by using the ΔΔCt method. Nuclease-free H2O and genomic DNA instead of cDNA were used for control purposes.Animals were euthanized by cervical dislocation immediately following the open-field tests. The left hippocampi were isolated and frozen in dry ice for measurement of TNF mRNA by reverse transcriptase polymerase chain reaction (RT PCR), as described previously . BrieflyThe Barnes maze test (BMT) is a dry-land alternative to the MWMT and uses bright light instead of water for motivating behavior. In this study, the BM arena was an open, circular platform (92 cm), possessing 20 holes that were evenly distributed around its perimeter . The arena was situated 1.5 m above the ground and illuminated by a set of four bright lights (4 × 120 W). A recessed dark box was placed under one of the twenty holes, providing animals with a route to escape from the brightly lit arena.n = 7–8/group). The 48 h time-point, as well as the gender of the animals used for LPS injections, were chosen based on the dose-assessment studies, characterizing the effects of 0.5 mg/kg LPS on sickness behavior and locomotor activity in the open field. Data were generated after four independent BM experiments, which were performed and analyzed in a blinded manner. The location of the escape box was kept constant during a given experiment but was changed to different positions between experiments. In addition to male mice, a set of female WT and TNF-KO mice was also tested in the BM under identical conditions, 48 h following an injection of PBS only (n = 4–7/group).Male, age-matched, WT and TNF-KO mice were tested in the BM in a paired manner. The animals were injected once with PBS or 0.5 mg/kg LPS, 48 h before the spatial acquisition (learning) phase of the BMT , primary latency, which was the time required for an animal to reach the escape hole for the first time (first correct nose-poke), target block time, which was measured on DAYS 4 & 11 and was defined as the time each mouse spent in the quarter of the arena where the escape box used to be situated, and nose-poke distribution, which was the number of nose-pokes conducted by each animal in each of the 20 holes on DAYS 4 and 11. Immediately after the BMT, mice were euthanized by cervical dislocation and the left hippocampi isolated and frozen in dry ice. Samples from male mice were subsequently sent to Oslo University Hospital, Norway, where they were assayed for total glutamate and noradrenaline content. 6 hydrochloride  and DL-glutamic acid-d3 (C/D/N Isotopes Inc.), were prepared in 25 mM formic acid and stored at 4 °C. Working solutions for calibrators and quality control samples were prepared independently by dilution of stock solutions in 25 mM formic acid. Calibrators (10–4000 nm) and quality control samples (30–3200 nm) were prepared by appropriate dilution of the working solutions in 25 mM formic acid.Determination of neurotransmitters was performed using a previously described ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) method by Bergh et al.  with minHippocampal samples were homogenized in type 1 water (50 mg/mL) using a VirSonic 300 ultra sound sonicator . Aliquots were collected for triplicate determinations of total protein content , prior tFor determination of neurotransmitters, brain homogenate (50 μL) and internal standard (25 µL) were added to brown eppendorf tubes. Ice-cold 250 mM formic acid (50 µL) was added previous to vortexing. The samples were centrifuged before the supernatant was transferred to autosampler vials. For calibrators and quality control samples, solution (50 μL) was added to internal standard (25 µL) and 225 mM formic acid (50 μL).6 (176.2 > 158.1) and DL-glutamic acid-d3 (151.0 > 87.0). The limit of quantification for the analytes was between 100 and 200 nm. Data was acquired and processed using Masslynx™ 4.1 software . For more detailed information about the UHPLC-MS/MS analysis, see Bergh et al. , with several studies showing no effect ,18,56 orTo examine how TNF deletion impairs spatial learning and memory in TNF-KO mice, the concentration of glutamate and noradrenaline was measured in the hippocampi of male mice. TNF can exert direct effects on glutamatergic  and noraAlthough the exact mechanisms by which TNF modulates cognition were not identified here, our results imply that other LPS-induced molecules can compensate for the effects of TNF on learning and memory. Compensatory effects for the absence of TNF were evident in LPS-treated TNF-KO mice, which showed no deficits in the BMT arena. Among the broad range of cytokines, chemokines and growth factors that are released upon LPS treatment, IL-1β could be a candidate for replacing the absence of TNF in TNF-KO mice. In IL-1 type 1 receptor knockout mice, TNF has been shown to mimic the effects of IL-1β on LPS-induced sickness behavior  and workThe observation that constitutive levels of TNF are required for spatial cognition in male subjects, and the large body of evidence documenting sex differences in the immune response to peripheral inflammation, prompted us to study the effects of TNF deletion in the BMT using female subjects. Unlike male mice, no differences in spatial learning and memory were observed between female WT and TNF-KO mice, which is in line with previously reported results from our group, showing no effect of TNF deletion on baseline BMT performance in 9-month-old female mice . These rIn conclusion, the present data support a physiological role for TNF in modulating spatial learning and memory in male subjects. The effects of TNF deficiency were modulated by prior systemic inflammation, since LPS administration 48 h before the BMT reversed the deficits in TNF-KO mice, emphasizing the complexity and perhaps redundancy of inflammatory signaling in the brain. In addition, we note a close association between male gender and responsiveness to TNF, which is not limited to LPS-induced sickness behavior but may extend to aspects of physiological cognitive function. These results underline the importance of sex-stratified analysis when examining the role of TNF signaling in the brain and invite further consideration of gender as an important determinant of the response to TNF drugs.The possibility that the effects of TNF deletion on cognition were masked by the higher motor activity in LPS-treated TNF-KO vs. WT male mice cannot be excluded by the present data. However, previous studies indicate that mouse motor behavior recovers within 48 h after the injection of LPS ,71,72. MThe small sample size in the BM studies employing female TNF-KO mice and the possibility of a Type II error should also be noted as study limitations. The scarcity of 11-13-month-old female mice prevented us from studying the effects of LPS administration on cognition in both sexes. Such studies are warranted, given the reported sex differences in response to the endotoxin. Additionally, to control for genetic confounds comparing TNF-KO and WT mice it would be advisable to include heterozygous mice in future studies.Additionally, systematic studies of microglial TNF expression in the aging male and female mice are required. Such studies ideally be performed at the single cell level, and include co-expression analysis of other cytokines, such as IL-1β, which we have previously shown to be expressed in a subset of microglia distinct from the TNF expressing microglia .Finally, studies in mice with inducible, cell-specific deletion of TNF can be used to confirm whether microglia, the major source of TNF in the CNS, mediate the effects of TNF deletion on cognition in male subjects ,14,16.


Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) participates in the regulation of cellular stress and inflammatory responses, but its function in neuropathic pain remains poorly understood. This study evaluated the role of RIPK1 in neuropathic pain following inferior alveolar nerve injury. We developed a model using malpositioned dental implants in male Sprague Dawley rats. This model resulted in significant mechanical allodynia and upregulated RIPK1 expression in the trigeminal subnucleus caudalis (TSC). The intracisternal administration of Necrosatin-1 (Nec-1), an RIPK1 inhibitor, blocked the mechanical allodynia produced by inferior alveolar nerve injury The intracisternal administration of recombinant rat tumor necrosis factor-α (rrTNF-α) protein in naive rats produced mechanical allodynia and upregulated RIPK1 expression in the TSC. Moreover, an intracisternal pretreatment with Nec-1 inhibited the mechanical allodynia produced by rrTNF-α protein. Nerve injury caused elevated TNF-α concentration in the TSC and a TNF-α block had anti-allodynic effects, thereby attenuating RIPK1 expression in the TSC. Finally, double immunofluorescence analyses revealed the colocalization of TNF receptor and RIPK1 with astrocytes. Hence, we have identified that astroglial RIPK1, activated by the TNF-α pathway, is a central driver of neuropathic pain and that the TNF-α-mediated RIPK1 pathway is a potential therapeutic target for reducing neuropathic pain following nerve injury. The characterization of neuropathic pain is continuous and/or paroxysmal pain associated with dysesthesia or allodynia. It has been previously established that peripheral neuropathies caused by lesions in the peripheral nervous system are extremely difficult to treat as multiple underlying mechanisms can be involved and effective interventions are dependent on the cause. Drug development for treating neuropathic pain often focuses therefore on the inhibition or relief of certain underlying causes or symptoms.Receptor-interacting serine/threonine protein kinase 1 (RIPK1), a member of the serine-threonine protein kinase family, is a well-known and critical mediator of necroptosis and a regulator of the responses to cellular stress and inflammation ,3,4. PreTumor necrosis factor (TNF)-α is regarded as a proinflammatory cytokine with a central function in regulating pain communication between the immune system and the brain . GeneralWe hypothesized that the TNF-α-mediated activation of the RIPK1 pathway plays a key role in trigeminal neuropathic pain following inferior alveolar nerve injury. For this purpose, we examined changes in RIPK1 expression and TNF-α concentration in the trigeminal subnucleus caudalis (TSC) following inferior alveolar nerve injury in a rat model. We also used this model to examine the changes in the air-puff thresholds and TNF-α concentration after blockade of the RIPK1 pathway by intracisternally administered Nec-1, an RIPK1 inhibitor. Finally, we evaluated the cellular localization of RIPK1 and TNF receptor in the TSC of these animals by double immunofluorescence analysis.p < 0.05, F(2.17) = 800.124, p < 0.05, (2.18) = 44.791, p < 0.05, (2.19) = 53.625, p < 0.05, (2.19) = 13.4, p < 0.05, (2.18) = 172.249, p < 0.05, p < 0.05, Alterations in the air-puff thresholds and RIPK1 expression in naïve rats following the intracisternal administration of rrTNF-α protein are illustrated in p < 0.05). As shown in p < 0.05, F(2.18) = 48.416), which appeared 2 h after the 20 μg injection and 4 h after the 2 μg injection. These effects had dissipated by 24 h post-injection. Vehicle administration did not alter the mechanical allodynia induced by the malpositioned dental implantation. Western blotting indicated that the intracisternal administration of TNF-α antibody, but not vehicle, attenuated the upregulated RIPK1 expression in the TSC, resulting from the inferior alveolar nerve injury on POD 3 . These findings indicate that the RIPK1 pathway is activated by the actions of TNF-α in the TSC. This TNF-α-mediated RIPK1 pathway has been studied by the cell death cellular signaling mechanism. In TNF-α-stimulated cells, RIPK1 was reported to be activated intracellularly through the TNF receptor  and to rTNF-α has two receptors and both TNFR1 and 2 are known to be involved in neuropathic pain ,27. TNFRThe animal experiment followed the protocols of the Committee of the School of Dentistry, Kyungpook National University (No. 20210034). Adult male Sprague Dawley (SD) rats were used. A total of 269 SD rats were purchased from Jung-Ang experimental laboratory . All animals, weighting between 200 and 220 g, were maintained in a pathogen-free environment, in a 12:12 h light-dark cycle, and maintained at 23 ± 1 °C. Food and water were provided ad libitum. All experiments followed the ethical guidelines set for the investigation of experimental pain in conscious animals by the International Association for the Study of Pain (IASP). Each rat was used only once and all rats were handled at least 5 days before the surgery or behavioral testing to minimize stress. All of these experiments were conducted in a blinded fashion by a single researcher and the animals were randomized during the experiments.In the trigeminal neuropathic pain model, SD rats were anesthetized with a ketamine/xylazine  mixture. After anesthetization, the second molar of the left mandibular was extracted and a mini-dental implant was placed  to injure the inferior alveolar nerve, as previously described . SimilarWhile under anesthesia, intracisternal administrations were performed in the rats using a stereotaxic frame, and a polyethylene tube 10 (PE10) was implanted into each animal, as previously described ,31,32,33We measured mechanical allodynia using previously described methods ,37,38. FFor immunofluorescence analysis, the rats were sacrificed and perfused transcardially with 0.9% saline, followed by 4% paraformaldehyde in 0.1 M phosphate buffer . The caudal medulla was dissected and a portion of this tissue then underwent additional fixation using the same fixative solution for 2 h at 4 °C. Following 2 h fixation, the sample was then placed in 30% sucrose in 0.1 M PB solution overnight. Prior to processing for immunofluorescence analysis, transverse frozen sections  were cut using a cryostat. All tissue was blocked with a 10% normal donkey serum in phosphate buffered saline  for 30 min at room temperature and for the double immunofluorescence, the sections were incubated overnight at 4 °C with a mixed solution of rabbit anti-RIPK1  or a rabbit anti-TNFR1  with a mouse anti-NeuN , a goat anti-Iba-1 , or mouse anti-GFAP . Following these primary antibody incubations, samples were than incubated with a mixture of anti-rabbit Cy3  and anti-mouse or anti-goat FITC . Images were collected with a fluorescence microscope  or a confocal laser scanning microscope  to observe the immunofluorescence signals.For Western blotting analysis, the ipsilateral caudal medulla was collected and homogenized as described previously by Yoon et al. . Total pAt the indicated time points, protein supernatants were collected and evaluated for cytokine levels using commercial ELISA kits, in accordance with the manufacturer’s protocol. The TNF-α ELISA kit was purchased from R&D Systems  and the optical density (OD) was measured spectrophotometrically at wavelengths of 420–570 nm. The data were expressed relative to a standard curve prepared for TNF-α.Nec-1 was purchased from Selleckchem  and dissolved in a combination of 45% PEG 300, 5% DMSO, and 50% DDW. TNF-α antibody (R&D systems) was dissolved in normal saline. Recombinant rat TNF-α (rrTNF-α) protein was obtained from R&D systems and dissolved in sterile PBS.n = 7 per group). Mechanical allodynia was determined at 2 days prior to the operation and at 1, 2, 3, 5, 7, 10, 14, 21, 30, 35, 40, 45, and 50 days after the inflicted injury to the nerve. Western blotting analysis was conducted to evaluate RIPK1 expression following inferior alveolar nerve injury (n = 6 per group) on POD 3, 7, 21, and 50. Neuropathic mechanical allodynia was assessed after a blockade of RIPK1. The dose of Nec-1, an RIPK1 inhibitor, was based on prior reference [n = 7 per group).Prolonged nociceptive behavior was observed following inferior alveolar nerve injury in several previous studies ,38. Hereeference . Nec-1 (n = 7 per group). RIPK1 protein expression changes in the TSC were determined by Western blot analysis 2 h after treatment with rrTNF-α protein (n = 8 per group). To assess the participation of RIPK1 in TNF-α-induced mechanical allodynia, the effects of Nec-1, an RIPK1 inhibitor, on mechanical allodynia generated by the administration of rrTNF-α protein were monitored in naïve rats. Nec-1 (10 µg/10 µL) was administered 4 h before the rrTNF-α protein (200 ng/10 µL) injection and mechanical allodynia was evaluated at 0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 6, and 24 h after rrTNF-α protein injection (n = 7 per group).To evaluate the effects of rrTNF-α protein on air-puff thresholds, the rrTNF-α protein (20 or 200 ng/10 µL) was injected intracisternally into naïve rats. Mechanical allodynia was then measured at 0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 6, and 24 h after treatment with the rrTNF-α protein or vehicle (n = 10 per group) on POD 1, 3, and 5 to evaluate changes in the TNF-α concentration subsequent to inferior alveolar nerve injury. We also investigated changes in neuropathic mechanical allodynia and RIPK1 expression after a blockade of TNF-α in the rats with inferior alveolar nerve injury. On POD 3, TNF-α antibody (2 or 20 µg/10 µL) was administered intracisternally followed by saline flushing. Mechanical allodynia was then measured at 0, 0.5, 1, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, and 24 h after treatment with TNF-α antibody or vehicle (n = 7 per group). Western blotting was used to evaluate expression changes in RIPK1 within the TSC at 6 h after treatment with TNF-α antibody in the rats with inferior alveolar nerve injury (n = 8 per group).ELISA analysis was performed (n = 6 per group) was completed on POD 3 for RIPK1 and TNFR1 to evaluate their subcellular localization within the ipsilateral TSC, using markers for neurons (NeuN), microglia (IBA1), or astrocytes (GFAP).Double immunofluorescence staining .Repeated measures analysis of variance (ANOVA), followed by the Holm–Sidak post hoc test, was utilized to statistically analyze all behavioral data. For qualitative data obtained by Western blotting or ELISA, changes were evaluated using a Student’s Our results provide a connection between trigeminal neuropathic pain and TNF-α-RIPK1 pathway. Inferior alveolar nerve injury results in a significant upregulation of RIPK1 expression in the TSC and a blockade of the RIPK1 pathway effectively relieves mechanical allodynia. A single intracisternal administration of TNF-α antibody attenuates trigeminal neuropathic pain and suppresses the upregulation of RIPK1 expression. Double immunofluorescence analyses revealed the colocalization of RIPK1 and TNFR1 with astrocyte markers. Hence, an astroglial TNF-α-mediated RIPK1 pathway is involved in important pathogenic mechanisms underlying our rat pain model. Modulation of this pathway may be a viable therapeutic strategy to alleviate neuropathic pain.


In a cluster randomised controlled trial (CRCT), randomisation units are “clusters” such as schools or GP practices. This has methodological implications for study design and statistical analysis, since clustering often leads to correlation between observations which, if not accounted for, can lead to spurious conclusions of efficacy/effectiveness. Bayesian methodology offers a flexible, intuitive framework to deal with such issues, but its use within CRCT design and analysis appears limited. This review aims to explore and quantify the use of Bayesian methodology in the design and analysis of CRCTs, and appraise the quality of reporting against CONSORT guidelines.We sought to identify all reported/published CRCTs that incorporated Bayesian methodology and papers reporting development of new Bayesian methodology in this context, without restriction on publication date or location. We searched Medline and Embase and the Cochrane Central Register of Controlled Trials (CENTRAL). Reporting quality metrics according to the CONSORT extension for CRCTs were collected, as well as demographic data, type and nature of Bayesian methodology used, journal endorsement of CONSORT guidelines, and statistician involvement.Twenty-seven publications were included, six from an additional hand search. Eleven (40.7%) were reports of CRCT results: seven (25.9%) were primary results papers and four (14.8%) reported secondary results. Thirteen papers (48.1%) reported Bayesian methodological developments, the remaining three (11.1%) compared different methods. Four (57.1%) of the primary results papers described the method of sample size calculation; none clearly accounted for clustering. Six (85.7%) clearly accounted for clustering in the analysis. All results papers reported use of Bayesian methods in the analysis but none in the design or sample size calculation.The popularity of the CRCT design has increased rapidly in the last twenty years but this has not been mirrored by an uptake of Bayesian methodology in this context. Of studies using Bayesian methodology, there were some differences in reporting quality compared to CRCTs in general, but this study provided insufficient data to draw firm conclusions. There is an opportunity to further develop Bayesian methodology for the design and analysis of CRCTs in order to expand the accessibility, availability, and, ultimately, use of this approach. In a cluster randomised controlled trial (CRCT), randomisation occurs at the group (or “cluster”) level as opposed to the individual level that is typical in traditional Randomised Controlled Trials (RCTs). Examples of naturally-occurring clusters include schools, villages and GP practices. Randomisation of clusters, rather than individuals, is conducted for a number of reasons: (i) when the intervention is to be delivered at the cluster level (e.g. to a whole school/class within a school); (ii) when there is a risk of contamination, either between participants or those delivering the intervention; or (iii) when there is a clear administrative, logistic or cost-based rationale .Cluster randomisation has methodological implications that go beyond merely the randomisation procedure itself. Measurements on individuals within the same cluster are likely to be more correlated to one another than measurements on individuals from different clusters. This correlation creates an additional level of complexity, which must be accounted for in both the study design and sample size calculation, and the statistical analysis. Failure to do so can result in an underpowered study and ultimately spurious conclusions about the efficacy or effectiveness of the intervention or treatment under investigation.p-values, an approach which has been criticised in recent years [CRCTs are a relatively novel study design, but the methodology is now well established in the literature. Prior to the 1980s, there was only sparse use of CRCTs , but thent years  are cleaWith the increased use of CRCTs, the need for consistent, high-quality reporting is crucial. In response to this recognised need, the CONSORT extension to cluster randomised trials was first published in 2004  and updaThis review aims to:(i) Quantify and explore the use of Bayesian methodology in the design and/or analysis of CRCTs;(ii) Appraise the quality of reporting of CRCTs conducted in a Bayesian framework against the current relevant CONSORT guidelines and identify whether the reporting quality differs from previous reviews assessing reporting quality in CRCTs more generally .The impact of the introduction of the CONSORT guidelines for CRCTs in 2004 and 2012 on reporting quality will also be appraised.The protocol for this methodological systematic review was developed prospectively and made publically available online  before cWe sought to identify all published parallel group CRCTs in which Bayesian methodology was used in either the study design  or statistical analysis. We also opted to include any papers in which Bayesian methodology was discussed or considered, even if such methods were not implemented in the study, whilst recognising that such a scenario would be unlikely. We did not restrict our search or inclusion on the basis of publication date, location, intervention type or population in any way, provided the relevant paper was published in the English language, due to resource limitations.In order to be included in this review, it had to be evident that randomisation in the study occurred at a group level, in which multiple participants were randomised together, as per the definition of a CRCT.We did not exclude references on the basis of type (category) of published paper. Specifically, we included not only primary reports of efficacy or effectiveness but also protocol papers, papers reporting secondary analyses and publications reporting results of pilot/feasibility studies. We also included studies reporting Bayesian methodological developments in the area of CRCTs. At the data extraction stage, we sought to identify supplementary literature related to the same study, if indicated, to obtain the required information, but only included such examples as a single entry. It was anticipated, for example, that this might include obtaining additional detail from a published protocol or monograph that had been omitted in the corresponding primary results paper.We excluded papers reporting only cost-effectiveness. We also excluded studies implementing a stepped-wedge or other longitudinal cluster randomised design, as the methodological considerations are different and the reporting quality metrics presented in the CONSORT extension to CRCTs  are not We searched both Medline and Embase using Ovid, as well as the Cochrane Central Register of Controlled Trials (CENTRAL), for relevant publications on 24 July 2018, without restriction on date of publication. The full electronic search strategy was an extension of that presented by Taljaard et al. [After conducting electronic searches, all references were downloaded and imported to Mendeley  for elecAfter the initial sift, full-text articles were obtained for all remaining references. BJ examined the full texts and again made inclusion/exclusion decisions using Rayyan. SC or AB re-examined approximately half each of all full texts and independently made inclusion or exclusion decisions. Any disagreements were once again resolved through further discussion.p-values were reported for comparison of baseline demographics, as has been collected in previous systematic reviews of CRCTs [For the primary and secondary published reports of trial results, we collected a range of data including demographic data, technical detail regarding design and analysis methodology with relation to Bayesian techniques, and information regarding statistician involvement with the study and their respective affiliations. For papers reporting primary results, we also collected a selection of reporting quality metrics taken from the 2012 CONSORT extension to CRCTs [of CRCTs , 23, CliWe considered the paper as having statistician involvement, via a previously used criterion , 24, 25,We classified journal endorsement of the CONSORT statement using previously defined criteria : a journSeparate data extraction forms were developed for primary and secondary results papers to ensure that all the required information was obtained independently, consistently and without bias. The forms were piloted by BJ prior to data extraction. Formal data extraction was not undertaken for the methodological papers, but rather these papers were examined for the purpose of qualitative reporting and descriptive summaries of the methods developed in order to gain an understanding of the extent of methodological developments in this area.BJ conducted data extraction on all primary and secondary results papers. SC, AB and AS independently conducted approximately one-third each of the data extraction on all papers, and final data was agreed by the whole study team. BJ and SC also each independently classified the results papers as primary or secondary. Any disagreements were resolved through discussion. Separately, BJ examined the methodological papers for qualitative reporting, but no second data extraction was undertaken. BJ double-entered all data from the data extraction forms into separate excel spreadsheets for primary and secondary papers.We present descriptive statistics of frequencies and percentages or means and standard deviations, as appropriate, for demographic qualities relating to each of the results publications, including trial location, number of participants recruited and type of primary outcome, by category of published results (primary or secondary). For the reporting quality measures, we present the number of primary results papers satisfying each criterion overall, by year , 160 were individually randomised trials, and eight were papers reporting cost-effectiveness only). Full texts were obtained for the remaining 58 papers. At this final stage, following independent review of the full texts, a further 37 were removed , leaving 21 papers from the electronic search. A further six papers, all of which were methodological, were added through additional hand searches, resulting in a total of 27 papers included  publication date before or after the publication of the CONSORT extension to CRCTs in 2012 [One of the papers retrieved was a pre-specified sub-study and so was classified as a secondary results paper Table , R10. WeWe were unable to identify any results papers in which a Bayesian approach was taken, or even discussed, for study design or sample size calculation. One secondary paper did, however, specify that the design factor used to inflate the sample size calculation was derived from the results of a Bayesian hierarchical model.Of the eleven results papers included in the review, all adopted some form of Bayesian approach to statistical analysis Table . In ninet priors centred at 0 on the treatment effect parameter and other fixed logistic regression coefficients, which the authors acknowledged would only affect inference if the data provide little information about the parameters. No detail was provided on the prior distributions specified for the variance components in this paper. Five  papers specified the use of non-informative prior distributions, although only one of these (R5) provided more specific detail, stating normal prior distributions for the treatment effect and each of the fixed logistic regression coefficients, and uniform prior distributions for the variance components. Four studies  did not specify their choice of prior distribution. One paper fitted two Bayesian models (R3) - one model implementing a non-informative prior and the other utilising “collateral” information, so we recorded the use of both an informative and a non-informative prior.In these results papers, prior distributions were informative in two  papers; in one, (R3) “collateral” information from a previous study was used to construct a prior distribution for the variation in practice effects ; in the other (R11) an informative prior distribution for the treatment effect parameter within a negative binomial regression was constructed based on a meta-analysis of relevant reviews obtained from the Cochrane library, and used to inform the estimation of the outcome of interest . No information was provided on the prior distributions placed on the variance components. Weakly informative prior distributions were used in one  study, by placing Student’s We categorised 13 (48.1%) of the 27 papers included as methodological papers, where the focus was on the development of Bayesian methods for use in the design or analysis of CRCTs, as opposed to applying existing methods to data from CRCTs. Of these 13 papers, we defined 11 (84.6%) as “pure” methods papers, in which Bayesian methodological developments are reported independently of an applied scenario . We categorised two (15.4%) papers as being methodological but with the developments being driven by a specific statistical problem encountered in a CRCT, in which the method is presented and subsequently used to analyse the data of interest. Finally, we categorised three (11.1%) of the 27 papers as comparison of methods papers, in which existing methodology (both Bayesian and frequentist) were applied to the same data for comparative purposes.Of the 11 “pure” methodological papers, seven presented analysis methods , two presented methods for design/sample size calculation  and two presented elements of both . Both papers driven by specific application presented analysis methods .The analysis methods papers predominantly presented hierarchical modelling methodology applied to dealing with a range of data types, such as incidence rates (M1), count data (M2) and binary data , in a Bayesian setting, citing flexibility of modelling and the ability to incorporate prior information and account for the complex variance structures as key advantages. One paper reports Bayesian methods for modelling multivariate outcomes (M7), which allow for multiple outcomes without concern for multiplicity whilst accommodating complex correlation structures. Another paper presents Bayesian network meta-analysis methods for CRCTs (M12), allowing for comparison of multiple treatment arms whilst accounting for the complex correlation structure inherent in clustered data.A number of methodological papers identified within our review focus on the ICC. One such paper centres on analysis only, presenting methods for constructing intervals for the ICC and suggesting prior distributions for use in modelling (M11). The two papers in which both design and analysis are discussed focus heavily on the ICC; one provides a range of options for choice of prior distribution alongside recommendations, before discussing briefly how the uncertainty in the ICC can be accounted for in sample size calculations (M8). The other paper presents methods for formulating prior distributions for use in sample size calculations and statistical analysis on the basis of multiple previous estimates, whilst incorporating the relevance of the studies from which they were obtained (M10). One of the papers presenting only study design methodology also focused on ICCs, and developed methods to formulate prior distributions from single and multiple previous ICC estimates for use in sample size calculations (M6).The remaining study design paper presented a behavioural Bayes approach (M9), extending existing methodology –29 for sTo the best of our knowledge, this is the first methodological systematic review of the use, or consideration of, Bayesian methods in CRCTs.As the number of included papers is small, drawing robust conclusions regarding overall reporting quality between subgroups Table  is not pEvidently, the use of Bayesian methods in the design or analysis of CRCTs remains uncommon relative to the use of frequentist methods Fig. , with onA common criticism of the Bayesian approach in general, and in particular within the analysis of clinical trial data, is the subjective nature of the choice of prior distribution, although it is strongly recommended that sensitivity analyses be performed in order to assess the strength of the effect of the prior . InteresA protocol for this methodological systematic review was published before commencement of the electronic search  and the p-values for baseline comparisons were provided, in order to facilitate a robust judgement of reporting quality.The reporting quality metrics collected are predominantly a subset of the CONSORT checklist for CRCTs, a well-accepted set of criteria. We added a small number of additional items such as whether cluster size variability had been accounted for in the presented sample size calculation  and whetDespite this, we acknowledge the possibility that we may have missed some publications in which Bayesian methodology was used or considered in the design or analysis of CRCTs. In particular, we opted for a search strategy in which specificity was maximised, rather than sensitivity, in order to make the sifting process more manageable with limited resource. We added six additional methodological papers through hand searching, but were unable to identify any additional trial results papers. This is not surprising given the search strategy was developed to identify the latter, but may suggest a greater risk that further methodological papers have been missed compared to trial results papers.Furthermore, we present reporting quality metrics by journal endorsement of the CONSORT guidelines. However, we acknowledge that the guidelines may, in some cases, have changed since the date of the associated publications, and as a result, a journal’s endorsement may have been intensified since the included papers were accepted for publication. To the best of our knowledge, this issue has not been raised in previous systematic reviews of trial reporting quality; archiving of journal guidelines would help researchers conducting quality assessment systematic reviews in the future. Similarly, we sought to identify author affiliations during data collection, but again acknowledge that these may have changed since publication of the research, particularly for papers published some time ago.We intended to summarise the pre-specified reporting quality metrics by time periods  according to publication date to assess the effect of the relevant CONSORT statements on reporting quality. We acknowledge that the time delay between completion of the study and submission of the final report for publication may have resulted in some studies being categorised as published after the publication of the CONSORT extension guidance, when in fact it was designed, conducted and possibly even analysed before.The use of Bayesian methods in the statistical analysis of CRCTs is rare and was not found at all in the design of any of the reviewed studies or their sample size calculations. There have been some developments in Bayesian methodology for CRCTs but far less so than within the frequentist paradigm. Reporting quality may differ between CRCTs utilising Bayesian methodology compared with previous reviews of CRCT quality, although the number of papers identified in this review is small. There is a need for further Bayesian methodological developments in the design and analysis of CRCTs, including approaches for the specification of prior distributions, as well as statistical software development to allow easier implementation of methods, in order to increase the accessibility, availability and, ultimately, use of the approach.


Acinetobacter baumannii have emerged as a significant global health threat. One successful therapeutic option to treat bacterial infections has been to target the bacterial ribosome. However, in many cases, multidrug efflux pumps within the bacterium recognize and extrude these clinically important antibiotics designed to inhibit the protein synthesis function of the bacterial ribosome. Thus, multidrug efflux within A. baumannii and other highly drug-resistant strains is a major cause of failure of drug-based treatments of infectious diseases. We here report the first structures of the Acinetobacterdrug efflux (Ade)J pump in the presence of the antibiotic eravacycline, using single-particle cryo-electron microscopy (cryo-EM). We also describe cryo-EM structures of the eravacycline-bound forms of the A. baumannii ribosome, including the 70S, 50S, and 30S forms. Our data indicate that the AdeJ pump primarily uses hydrophobic interactions to bind eravacycline, while the 70S ribosome utilizes electrostatic interactions to bind this drug. Our work here highlights how an antibiotic can bind multiple bacterial targets through different mechanisms and potentially enables drug optimization by taking advantage of these different modes of ligand binding.Antibiotic-resistant strains of the Gram-negative pathogen  The bacterial ribosome represents a major target for antimicrobial agents, as it is vital for protein synthesis and is one of the largest molecular machines in the cell . Bacteri1–The tetracycline class of antibiotics are powerful antimicrobials that exhibit inhibition of Gram-positive, Gram-negative, and anaerobic bacteria –8. Tetra–10–Acinetobacter baumannii, a Gram-negative opportunistic pathogen. A. baumannii poses a severe nosocomial threat and is listed by the World Health Organization as a first priority for antibiotic research and development  superfamily of transporters IJK efflux system is the most prominent in conferring tetracycline resistance  to solve the structures of the AdeJ pump in the presence of Era. We also acquired structural information of Era-bound forms of the A. baumannii ribosome to critically examine the drug-binding modes of AdeJ and the ribosome. Here, we present the first structures of the A. baumannii AdeJ multidrug efflux pump with and without Era to resolutions of 2.86 Å and 2.87 Å, respectively. We also report six different structural states of the A. baumannii ribosome, including the 70S, 50S, and 30S forms, in the presence of Era, to resolutions that range from 2.50 Å to 3.04 Å. Our results show that the A. baumannii AdeJ pump and ribosome use very distinct modes of action to bind Era, providing a framework for the development of future generations of tetracycline antibiotics optimized to specifically bind the ribosome to halt protein synthesis yet be refractory to RND transporter export.In order to better understand how resistance is conferred to tetracyclines via the A. baumannii AdeJ recognizes the tetracycline class of antibiotics, we determined its structure using single-particle cryo-electron microscopy (cryo-EM). AdeJ was expressed in Escherichia coli, purified, and reconstituted into lipidic nanodiscs. Subsequently, the AdeJ-nanodisc sample was incubated with Era for 1 h to form the AdeJ-Era complex. Extensive classification of the single-particle images indicated that there were two distinct populations of the AdeJ membrane protein coexisting in this single nanodisc sample (To understand how c sample  to d andc sample  to c. Of10.1128/mBio.01031-21.1FIG S1A. baumannii AdeJ. (a) Data processing workflow of apo-AdeJ and AdeJ-Era. (b and c). Representative two-dimensional classes of apo-AdeJ and AdeJ-Era. (d and e). Gold-standard Fourier shell correlation (GS-FSC) curves of apo-AdeJ and AdeJ-Era. (f and g). Side and top views of the apo-AdeJ and AdeJ-Era cryo-EM density maps. The three protomers in apo-AdeJ are colored royal blue, gold, and gray. The three protomers in AdeJ-Era are colored tomato, violet, and lawn green. Download FIG S1, JPG file, 1.5 MB.Data processing of Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Overall, AdeJ adopts the fold of a typical hydrophobe-amphiphile efflux (HAE)-RND efflux pump and assembles as a homotrimer  to d. EaOur cryo-EM structure of the apo form of AdeJ has provided a clear view of the structural basis of this pump that enables substrate transport . A cleft10.1128/mBio.01031-21.6TABLE S1Table S1, PDF file, 0.03 MB.AdeJ cryo-EM data collection and refinement statistics. Download Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Pseudomonas aeruginosa MexB and E. coli AcrB, respectively. These arginines have previously been shown to be important for substrate specificity  connecting the cleft entrance to the proximal drug-binding site. This F-loop also creates the bottom section of the proximal site. Cryo-EM structures and molecular dynamics (MD) simulations of the AdeB pump depict this loop as being very flexible with distinct conformations within different physiological states of the pump . Interes32–E. coli AcrB multidrug efflux pump, there are at least 22 residues that make up the proximal drug-binding site of AcrB  compartmentalizes the proximal and distal drug-binding sites. Similar to the F-loop, the cryo-EM structures and MD simulations of the AdeB pump indicate that this G-loop is highly flexible . This loE. coli AcrB pump, the distal drug-binding site has been reported to contain at least 23 residues . Distance between DN and DC domains (exit tunnel) in AdeJ-Era (top). The access, binding, and extrusion state protomers are colored violet, tomato, and lawn green, respectively. DN and DC domain distance of the three apo-AdeJ protomers (bottom). The resting, binding, and extrusion state protomers are labeled in royal blue, gold, and gray, respectively. Distances are measured between the Cα atoms of Q125 and Y759. (b) Proton relay network of AdeJ. Resting, access, binding, and extrusion states of AdeJ protomers are colored royal blue, tomato, violet, and lawn green, respectively. Residues involved in the proton relay network  are showed as cyan sticks and surface density. Hydrogen bonds between K952 and D407, D408, K953, and T989 are labeled with yellow dashes. Download Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.01031-21.7TABLE S2Table S2, PDF file, 0.03 MB.Classification of AdeJ protomer states. Download Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Campylobacter jejuni CmeB trimeric multidrug efflux pump  The r.m.s.d. between the apo-AdeJ and AdeJ-Era is 1.206 Å. The resting, binding, and extrusion protomers of apo-AdeJ are colored blue, gold, and gray, respectively. The access, binding, and extrusion protomers of AdeJ-Era in tomato, violet, and lawn green, respectively. The helices are shown as tubes. (b to d) The r.m.s.d. values between the resting protomer of apo-AdeJ and access protomer of AdeJ-Era (b), binding protomer of apo-AdeJ and binding protomer of AdeJ-Era (c), and extrusion protomer of apo-AdeJ and extrusion protomer of AdeJ-Era (d) are shown. (e) Enlarged view of the distal drug-binding site of the apo-AdeJ-binding protomer (gold) and AdeJ-Era-binding protomer (violet). The motion of the G-loop between these two protomers is highlighted with a black arrow. Download Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 2+ ion is known to play a role in stabilizing the binding of tetracyclines to ribosomes, it is surprising that we do not see additional cryo-EM densities corresponding to Mg2+ ions within the vicinity of bound Era in the AdeJ-Era structure. However, this finding indeed agrees with the previous structural study of AcrB bound with the tetracycline derivative minocycline using X-ray crystallography, where no bound Mg2+ ion was found  generated from the transmembrane domain to extrude drugs from the periplasmic domain. In the transmembrane domain of AdeJ, residues D407, D408, K952, N953, and T989 are conserved and form the proton relay network . These rA. baumannii AdeJ pump and 70S ribosome are capable of binding tetracyclines, we decided to solve the cryo-EM structure of A. baumannii 70S bound with Era. These structures are expected to shed light on the mechanisms of drug recognition for these two biomolecules.Since both the A. baumannii 70S ribosome was incubated with Era for 1 h to form the ribosome-Era complex. We then used cryo-EM to solve structures of this complex. Extensive classification allowed us to separate the single-particle data into six distinct particle classes. The first two particle classes represent images from the small 30S subunit and the large 50S subunit (The  subunit  to e.10.1128/mBio.01031-21.4FIG S4A. baumannii ribosome. (a) We processed 3,217 micrographs to give an initial pool of 404,703 particles. (b) Extensive three-dimensional classification resulted in three different populations, 50S, 30S, and 70S. (c) Classes were combined and used as targets to retrieve particles from the full particle set. (d) Refined 30S cryo-EM density. (e) Refined 50S cryo-EM density. (f) Three-dimensional variability analysis followed by clustering in cryoSPARC was used to separate 70S particle by tRNA population and hpf occupancy. (g) Final reconstructions of P-site tRNA, E-site tRNA, empty and hpf-bound 70S particles, respectively. Download FIG S4, JPG file, 1.5 MB.Data workflow of Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the A. baumannii 70S ribosome  Representative two-dimensional classes (top left); GS-FSC curves of two locally refined regions, 30S core and 30S head (right); and combined final density-modified 30S map (bottom left). (b) Representative two-dimensional classes (top left), GS-FSC curve (right), and combined final density-modified 50S map (bottom). (c) Representative two-dimensional classes (top left); GS-FSC curves of three locally refined regions, 50S, 30S core, and 30S head (right); and combined final density-modified P-site tRNA 70S map (bottom). (d) Representative two-dimensional classes (top left); GS-FSC curves of three locally refined regions, 50S, 30S core, and 30S head (right); and combined final density-modified E-site tRNA 70S map (bottom). (e) Representative two-dimensional classes (top left); GS-FSC curves of three locally refined regions, 50S, 30S core, and 30S head (right); and combined final density-modified empty 70S map (bottom). (f) Representative two-dimensional classes (top left); GS-FSC curves of three locally refined regions, 50S, 30S core, and 30S head (right); and combined final density-modified hpf-bound 70S map (bottom). In all panels, the 50S is depicted in blue, 30S core is shown in yellow, and the 30S head is colored red. Download FIG S5, JPG file, 1.8 MB.Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mBio.01031-21.8TABLE S3Table S3, PDF file, 0.04 MB.Ribosome cryo-EM data collection and refinement statistics. Download Copyright © 2021 Zhang et al.2021Zhang et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 2+ ions. These two Era molecules contact one another to form a dimer via aromatic stacking  and populations    and 4, EA. baumannii infections and possibly other MDR bacterial strains as well.In comparison with the AdeJ and 30S Era-binding sites , it is qA. baumannii 70S ribosome ΔacrB cells, which harbor a deletion in the chromosomal acrB gene. Cells were grown in 6 liters of Luria-Bertani (LB) medium with 100 μg/ml ampicillin at 37°C. When the optical density at 600 nm (OD600) reached 0.5, the culture was treated with 0.2 mM isopropyl-β-d-thiogalactopyranoside (IPTG) to induce adeJ expression. Cells were then harvested within 4 h of induction. The collected bacteria were resuspended in low-salt buffer  and then disrupted with a French pressure cell. The membrane fraction was collected and washed twice with high-salt buffer  and once with final buffer . The membrane protein was then solubilized in 2% (wt/vol) n-dodecyl-β-d-maltoside (DDM). Insoluble material was removed by ultracentrifugation at 100,000 × g. The extracted protein was then purified with a nickel-nitrilotriacetic acid (Ni-NTA) column. The purity of the AdeJ protein (>95%) was judged using SDS-PAGE stained with Coomassie brilliant blue. The purified protein was dialyzed against 20 mM Na-HEPES (pH 7.5) and concentrated to 7 mg/ml (60 μM) in a buffer containing 20 mM Na-HEPES (pH 7.5) and 0.05% DDM.The E. coli total extract lipid was incubated for 15 min at room temperature. Afterward, 0.8 mg/ml prewashed Bio-Beads (Bio-Rad) was added. The resultant mixture was incubated for 1 h on ice followed by overnight incubation at 4°C. The protein-nanodisc solution was filtered through a 0.22-μm nitrocellulose filter to remove the Bio-Beads. To separate free nanodiscs from AdeJ-loaded nanodiscs, the filtered protein-nanodisc solution was purified by passage through a Superose 6 column  equilibrated with 20 mM Tris-HCl (pH 7.5) and 100 mM NaCl. Fractions corresponding to the size of the trimeric AdeJ-nanodisc complex were collected for cryo-EM.To assemble AdeJ into nanodiscs, a mixture containing 20 μM AdeJ, 45 μM MSP (1E3D1), and 930 μM A. baumannii ribosomes were purified as previously described (A. baumannii (strain AB0057) cells were lysed using a French pressure cell in lysis buffer , and 0.5 mM EDTA) (g for 30 min. Ribosome-containing pellets were obtained using a sucrose cushion buffer (lysis buffer with 1.1 M sucrose) and centrifuging for 16 h at 100,000 × g. The resulting pellet was stored at −80°C until further use.escribed . In briemM EDTA)  and centg. The sample was fractionated and monitored using a plate reader. Fractions containing 70S particles were exchanged into ribosome buffer 2 using 100-kDa cutoff Amicon centrifugal filters , frozen in liquid nitrogen, and stored at −80°C until further use.To increase sample purity, sucrose gradient purification was performed using a sucrose gradient  and centrifugation for 16 h at 100,000 × A. baumannii ribosome with 50 μM Era for 1 h prior to plunge freezing (15 s blot) on graphene oxide-coated Quantifoil R1.2/1.3 grids. The grids were then transferred into cartridges prior to data collection.For the AdeJ-Era sample, a 10-μM AdeJ-nanodisc sample was incubated with 20 μM Era  for 1 h to form the AdeJ-Era complex. The sample was applied to glow-discharged holey carbon grids , blotted for 5 s, and then plunge-frozen in liquid ethane using a Vitrobot (Thermo Fisher). The grids were then transferred into cartridges. The ribosome sample was prepared by incubation of 100 nM −/Å2 using SerialEM . For AdeJ, the data were collected in superresolution mode at nominal magnification of 81 K, corresponding to a sampling interval of 1.08 Å/pixel . Each micrograph was collected over 40 frames and exposed for 2 s with a total specimen dose of 36 eSerialEM . For theSerialEM .ab initio three-dimensional reconstruction, several iterative rounds of heterogeneous refinement were carried out to remove false picks and classes with unclear features, including ice and carbon contamination. The resulting 649,335 particles were then used for three-dimensional classification. Several rounds of nonuniform refinement were performed, where 83,768 and 95,451 particles were classified as the apo-AdeJ pump and AdeJ-Era complex, respectively. Nonuniform refinement followed by local focused refinement using cryoSPARC resulted in 2.87 Å and 2.86 Å global resolution maps for apo-AdeJ and AdeJ-Era based on the gold-standard Fourier shell correlation (FSC), respectively  estimation by patchCTF in cryoSPARC . Initialectively . The finectively .A. baumannii ribosome, the superresolution image stacks were aligned and binned by 2 using patch motion, and CTF was estimated using patch CTF in cryoSPARC  (For the ryoSPARC . A subsee” (BaR)  method, e” (BaR) . While ie” (BaR) .6OWS)  and ribosome  were based on the cryo-EM maps. A homology structure of apo-AdeJ was generated based on the atomic coordinates of AdeB (PDB ID 6OWS)  using th6OWS) . This in6OWS) . The A. ructures , previouructures . Mg2+ io in Coot . Subsequ in Coot  and phen in Coot  from the in Coot , respect in Coot . The sta7M4Q and 7M4P and in the electron microscopy data bank (EMDB) under accession codes EMD-23664 and EMD-23663, respectively. Atomic coordinates for A. baumannii 30S, 50S, P-site tRNA 70S, E-site tRNA 70S, empty 70S, and hpf-bound 70S have been deposited to the RCSB PDB under accession codes 7M4U, 7M4V, 7M4X, 7M4Y, 7M4W, and 7M4Z and the EMDB under accession codes EMD-23666, EMD-23667, EMD-23669, EMD-23670, EMD-23668, and EMD-23671, respectively.Atomic coordinates and EM maps for the apo-AdeJ and AdeJ-Era structures have been deposited in the RCSB protein data bank (PDB) under accession codes