Understanding the interactions between Notch1 and toll-like receptor 4 (TLR4) signaling pathways in the development of diabetic peripheral neuropathy may lead to interpretation of the mechanisms and novel approaches for preventing diabetic neuropathic pain. In the present study, the interactions between Notch1 and TLR4 signaling pathways were investigated by using dorsal root ganglion (DRG) from diabetic neuropathic pain rats and cultured DRG neurons under high glucose challenge. The results showed that high glucose induced not only Notch1 mRNA, HES1 mRNA, and TLR4 mRNA expression, but also Notch1 intracellular domain (NICD1) and TLR4 protein expression in DRG neurons. The proportion of NICD1-immunoreactive (IR) and TLR4-IR neurons in DRG cultures was also increased after high glucose challenge. The above alterations could be partially reversed by inhibition of either Notch1 or TLR4 signaling pathway. Inhibition of either Notch1 or TLR4 signaling pathway could improve mechanical allodynia and thermal hyperalgesia thresholds. Inhibition of Notch1 or TLR4 signaling also decreased tumor necrosis factor-α (TNF-α) levels in DRG from diabetic neuropathic rats. These data imply that the interaction between Notch1 and TLR4 signaling pathways is one of the important mechanisms in the development or progression of diabetic neuropathy. Toll-like receptors (TLRs) may regulate the processes of neurogenesis and neurite outgrowth, suggesting their roles in neuronal plasticity2. Increasing evidence suggests that Toll-like receptor 4 (TLR4) contributes importantly to chronic pain sensitization3. The role of TLR4 in diabetes mellitus has been receiving much attention at present. TLR4-mediated chronic inflammation not only causes many diabetes complications such as diabetic neuropathy, but also has a profound impact on the internal environment of the body and microenvironment of the nervous system4. Since TLR4 is widely distributed in the nervous system and also has an important role in the regulation of neuroinflammation, the unique role of TLR4 in diabetic neuropathy should be further clarified.A wide array of cell signaling mediators and their interactions play vital roles in neuroinflammation associated neurodegeneration5. Tumor necrosis factor-α (TNF-α) is a downstream pro-inflammatory cytokine of TLR4 signaling pathway7. Activation of TLR4 induces production or release TNF-α in DRG8. Increased expression of pro-inflammatory cytokines such as TNF-α in the peripheral nervous system suggests the possibility of change in pain perception in diabetes10. The possibility exists that TLR4 signaling is correlated with the modulation of inflammatory mediator TNF-α and increase the sensitivity of nociception.Inflammatory responses could play a critical role in the pathogenesis of neuron injury12. Notch signaling regulates the fate of cells in the developing nervous system14 and is important in synaptic plasticity and inflammation in the nervous system15. Defects in the expression of Notch genes result in severe, often lethal, development abnormalities16. Notch1 receptor plays a role in modulation of synaptic activity of distinct growth factor, which shows insights into a possible cytokine/Notch signaling cross-talk complex17. Chronic pain associated with chronic neuroinflammation is caused by a local inflammation in the peripheral nervous system. Both TLR4 and Notch signaling contributed to the induction and maintenance of mechanical allodynia in neuropathic pain15. TLR4 and Notch signaling may be crucial in the progression of painful diabetic neuropathy. However, their interactions in the process of initiating and developing diabetic neuropathy remain elusive. On the track of the crucial role for Notch1 and TLR4 signaling pathways in regulation of diabetic neuropathy, this study aims to investigate the involvement of specific interactions of Notch1 and TLR4 signaling pathways by using both streptozotocin (STZ)-induced diabetic rat model in vivo and cultured DRG neurons under high glucose challenge in vitro.The Notch signaling pathway is crucial for regulation of neuronal differentiation and survival18. DAPT has potent and specific characteristics of inhibition of γ-secretase, which specifically blocks the Notch1 pathway by preventing the intracellular domain of Notch1 (NICD1) from being released and translocated to the nucleus. The decrease of NICD1 expression was detected after DAPT treatment19. Whether the inhibitory effect of DAPT on NICD1 expression prevents the progression of diabetic neuropathy and relieves diabetic neuropathic pain should be further evaluated. TAK-242 (TAK) is a novel antagonist of TLR4 and effectively decreases neuroinflammation by its efficacy on blocking TLR4 to bind with its downstream adaptor protein20. In many experimental conditions, inhibition of TLR4 by TAK induced decreases of TLR4 expression21. The effect of TAK on reducing neuroinflammation in diabetic neuropathy should be further explored. In the present study, both DAPT and TAK were used as the specific inhibitors for detecting the interactions of Notch1 and TLR4 in the progression of diabetic neuropathy. Especially, the interactions of Notch1 and TLR4 signaling were focused in this study for their influence on reliving pain behavior. The interactions of different signaling pathways might provide a novel anti-neuroinflammatory strategy with additional therapeutic options for developing diabetic neuropathy.N-[N--1-alanyl]-S-Phenylglycinet-butylester (DAPT) is served as an inhibitor for Notch1 receptor through decreasing the expression of Notch intracellular domain (NICD) as well as the downstream gene hairy and enhancer of split 1 (HES1)According to the convergent evidence that activation of TLR4 contributes the development of neuropathic pain and its possible interactions with Notch1 signaling, inhibition of either Notch1 or TLR4 signaling on mechanical allodynia and thermal hyperalgesia of painful diabetic neuropathic rats was tested in this study. After adminstration of STZ for 6 weeks, the rats were intrathecally injected the Notch1 inhibitor DAPT  or the TLR4 inhibitor TAK , respectively, once per day for 3 consecutive days. The mechanical and thermal thresholds were measured once per day for 5 consecutive days after first injection of DAPT or TAK. Inhibition of either Notch1 or TLR4 elevated the mechanical and thermal thresholds, which reflected the improvement of the neuropathic pain behaviors. The highest point of mechanical and thermal thresholds was at 3 days after injection of Notch1 inhibitor DAPT or TLR4 inhibitor TAK. The mechanical and thermal thresholds were also maintained at a high level in 2 days after stopping injection compared with the painful diabetic neuropathic animals without injection of Notch1 inhibitor DAPT or TLR4 inhibitor TAK. These data imply that inhibition of either Notch1 or TLR4 signaling pathway might be a novel therapeutic target for relieving pain behaviors of diabetic neuropathy  and NICD1 or TLR4. The percentage of NICD1-immunoreactive (IR) neurons in control, mannitol, high glucose, high glucose + DAPT, high glucose + TAK group was 23.1% ± 4.9%, 25.9% ± 5.1%, 33.7% ± 3.4%, 29.5% ± 3.6%, and 27.8% ± 2.5%, respectively. The percentage of TLR4-IR neurons in the corresponding group was 24.7% ± 4.1%, 25.2% ± 2.5%, 35.6% ± 2.8%, 28.6% ± 6.2%, and 28.1% ± 4.2%, respectively. High glucose challenge increased the proportion of NICD1-positive and TLR4-positive neurons. After inhibition of either Notch1 or TLR4 signaling pathway, the proportion of NICD1-positive and TLR4-positive neurons decreased  of Notch1 in neuron24. TLR signaling pathway mediates neuroinflammation and expression of cytokines in DRG neurons25. Activation of TLR4 in DRG sensory neurons could influence excitation of these neurons and contribute to neuropathic pain26. Several studies dealt with that the pro-inflammatory cytokine TNF-α correlates to the diabetic peripheral neuronal abnormalities29. A recent clinical trial has shown that TNF-α may contribute to the pro-inflammatory status of the distal sensory nerves in patients with diabetes or prediabetes27. In the present study, TNF-α was upregulated in DRG from STZ-induced diabetic neuropathic pain rats. It has been shown that plasma concentrations of inflammatory indicators including TNF-α were positively correlated with TLR4 in patients with diabetic peripheral neuropathy30, which may aggravate the TLR4-mediated inflammatory cascade that is already activated. The results of our present study demonstrated that induction of inflammation contributed to the maintenance of neuropathic pain, suggesting a potential therapeutic target for the treatment of neuropathic pain.TLR4-mediated signaling pathway is associated with the promotion of neuroinflammatory response in neuronsWhen TLR4 signaling, or inflammation, is inhibited by TAK, it not only may have affected the interactions of TLR4 signaling and with members of Notch1 signaling, but also interfered with Notch-dependent transcription. On the other hand, Notch1 inhibitor DAPT inhibited the expression of TLR4 suggesting the role of Notch1 signaling on survival of affected neurons. The fact that Notch signaling pathway is crucial for neuronal differentiation and survival suggested that interactions between TLR4 with members of Notch1 signaling regulate certain aspects of latency of the neurons affected diabetic neuropathy. Consequently, for this study, we compared the effects of the inhibitors of both signaling pathways to test whether TLR4 inhibitor TAK interfered with members of Notch1 signaling and Notch1 inhibitor DAPT with TLR4. TLR4 inhibitor TAK consistently interfered with members of Notch1 signaling molecules and TLR4 was also consistently inhibited by Notch1 inhibitor DAPT.31. However, there may be conflicting roles of different signaling pathways particularly of their effects on the neuronal activity. In this study, the pain behaviors developed in the painful diabetic neuropathy model were reversed by either Notch1 inhibitor DAPT or TLR4 inhibitor TAK, suggested that different pathways were involved. However, these pathways are actually playing a competing role in neuronal survival. The involvement of the Notch1 receptor in diabetic neuropathy is pro-neuronal survival which in turn promotes neuronal activity. Notch1 inhibition may or may not have direct influence on the inhibitory effect of the inflammation induced by diabetic neuropathy, but might be due to the decreased activity of neurons related to the pain behaviors by regulating the fate of these cells.It is well known that the inflammation effects are involved in the pain signal transduction in the diabetic neuropathy model in addition to their damage to the axons. TLR4 signaling also promotes repair after demyelinating conditions such as spinal cord injury16, because Notch could provide a proper balance of excitatory and inhibitory neurons of neuronal subtype specification32. In our present study, mechanical allodynia is developed in the diabetic neuropathy model. In this process, the excessive activation of Notch signaling contributed to the induction and maintenance of mechanical allodynia because more excitatory neurons are activated. Administering DAPT significantly prevented the nociceptive effects because the balance of excitatory and inhibitory neuronal activation is restored. These data suggested that Notch must be considered as important new targets of the diabetic neuropathy.Notch receptors are shown to regulate nociceptive thresholdsIn conclusion, intrathecal administration of Notch1 inhibitor DAPT and TLR4 inhibitor TAK attenuated allodynia and hyperalgesia. PCR and Western blot analysis revealed time-dependent upregulation of TLR4 mRNA and protein, Notch1 mRNA, NICD1 protein, which was paralleled by pain behavior of the established diabetic neuropathy. High glucose challenge for cultured DRG neurons similarly influenced the Notch1 and TLR4 signaling pathways in agreement with diabetic animal model. Blockade of either Notch1 or TLR4 signaling pathway produced anti-nociceptive effects and inhibited the expression of TLR4 mRNA and protein, Notch1 mRNA, NICD1 protein, which suggests that they may be putative interactions when the pain of diabetic neuropathy is developed and may be the target for future pharmacological pain relief tools. Summing up, in light of the interactions of Notch1 and TLR4 signaling pathways, both Notch1 and TLR4 signaling pathway may indeed play a significant role in development of neuropathy, which could be linked to the nociceptive behavior in diabetic neuropathy.http://www.nap.edu), all animals were carefully treated during the experiments. Especially, all surgery was performed under anesthesia and all efforts were made to minimize suffering of the animals. All procedures or protocols described here were reviewed and approved by the Ethical Committee for Animal Experimentation of Shandong University.Compliance with the National Institute of Health Guide for the Care and Use of Laboratory Animals  taken from the breeding colony of Wistar rats maintained in the Experimental Animal Center at Shandong University of China. All the rats were housed in plastic cages with a normal light-dark cycle and allowed free access to rat chow and water. Diabetic neuropathic pain rat model was induced by a single peritoneal injection (i.p.) of STZ  as our previous studyFor intrathecal injection (i.t.), a sterile polyethylene catheter   was inserted through an incision in the gap between the L4/L5 vertebrae and the tip of catheter was positioned at the subarachnoid space under anesthesia with of 3% pentobarbital sodium . After a 3-day recovery period and at the end of the experiment, 2% lidocaine  was given through the catheter to make sure the catheter tip was in appropriate position. Only the rat showing reversible hind limb motor deficits immediately following the lidocaine injection were considered to be catheterized successfully.2·2H2O 1.26, MgCl2·6H2O 1.16, NaH2PO4·2H2O 0.58, NaHCO321.0, and glucose 10.0, pH was adjusted to 7.4.Thirty-two rats were randomly divided into 4 groups (8 rats in each group): (1) Control group: The equivalent volume normal saline (10 μl) was administrated (i.t.) for normal rat as a control. (2) Diabetic group: After STZ injection for 6 weeks, normal saline (10 μl) was administrated (i.t.) for diabetic rat once per day for 3 consecutive days. (3) DAPT group: After STZ injection for 6 weeks, the Notch1 inhibitor DAPT  was administrated (i.t.) for diabetic rat once per day for 3 consecutive days. (4) TAK group: After STZ injection for 6 weeks, the TLR4 inhibitor TAK  was administrated (i.t.) for diabetic rat once per day for 3 consecutive days. After each injection, artificial cerebrospinal fluid  was used immediately for removing residual liquid in the catheter. The ACSF was composed of following ingredients (mmol/L): NaCl 138.6, KCl 3.35, CaCl34. After STZ injection for 6 weeks, the threshold of mechanical allodynia and thermal hyperalgesia was measured once per day for 5 consecutive days.The mechanical allodynia and thermal hyperalgesia were assessed by determination of the withdrawal threshold by means of a von Frey filaments  and a plantar analgesia tester , respectively. The detailed measurement of mechanical allodynia and thermal hyperalgesia was carried out as our previous studyin vitro study35. Cultured DRG neurons under high glucose challenge were served as an in vitro model of diabetic neuropathy36. These culture preparations utilized newborn rats (less than 24 h after birth) taken from the breeding colony of Wistar rats maintained in the Experimental Animal Center at Shandong University of China. Dissociated DRG cell culture procedure was similar to our previous study37. Briefly, the DRG was digested with 0.25% trypsin  and centrifuged at 1 × 103 rpm. The pellets were resuspended in Dulbecco’s Modified Eagle Medium with F-12 supplement (DMEM/F-12) medium . DRG cells for fluorescent labeling were plated at 1 × 105 cells/well in 24-well clusters  which would contain a coverslip precoated with poly-L-lysine  in each well. DRG cells for real-time PCR and Western blot assay were plated at a density of 5 × 105 cells/ml. The composition of the culture medium is DMEM/F-12 (1:1) supplemented with 5% fetal bovine serum, 2% B-27 supplement , L-glutamine . Dissociated DRG cells were cultured at 37 °C with 5% CO2 for 24 hours and then maintained in culture medium containing cytarabine (ara-C) (5 μg/ml) for another 24 hours to inhibit growth of non-neuronal cells. After that, neurons were cultured in neurobasal medium for additional 72 hours at different experimental conditions before observation.The paradigm of regenerative state of cultured DRG neurons is useful for DRG neurons at 48 h post-culture were randomly divided into 5 groups: (1) Control group: Neurobasal medium contains 25 mmol/L of glucose which is optimal for DRG neuron survival and growth, so this condition of glucose concentration was used in control group. (2) Mannitol group: Mannitol 20 mmol/L was used here to create a high osmotic pressure mimicking the high glucose condition. (3) High glucose group: Additional 20 mmol/L glucose was added to the medium as high glucose challenge. (4) High glucose + DAPT group: Additional 20 mmol/L glucose and 10 μmol/L of DAPT were added to the neurobasal medium. (5) High glucose + TAK group: Additional 20 mmol/L glucose and 10 μmol/L of TAK were added to the neurobasal medium. The cultured DRG neurons were maintained in distinct conditions for 72 hours before observation. Each condition was performed in triplicate as one experiment. Eight experiments (n = 8) were used for final analysis.34. The synthetic oligonucleotide primer sequences for Notch1, HES1, TLR4, and β-actin were as follows: Notch1 5′-GTG AGT GGG ATG GAC TGG AC-3′ (coding sense), 5′-GGA AGG AGT TGT TGC GTA GC-3′ (coding antisense); HES1 5′-TCG GTG GTT ACT TTG TTG CT-3′ (coding sense), 5′-AGG CGC AAT CCA ATA TGA AC-3′ (coding antisense); TLR4 5′-TGG CAT CAT CTT CAT TGT CC-3′ (coding sense), 5′-CAG AGC ATT GTC CTC CCA CT-3′ (coding antisense); β-actin 5′-CAC CCG CGA GTA CAA CCT TC-3′ (coding sense), 5′-CCC ATA CCC ACC ATC ACA CC-3′ (coding antisense). The final results of real time-PCR were expressed as the ratio of mRNA of control.The L4-L6 DRG from each animal after behavioral tests and the cultured DRG neurons in distinct conditions were processed for real-time PCR analysis for detecting Notch1 mRNA, HES1 mRNA, and TLR4 mRNA levels. The procedures of real-time PCR analysis were similar to our previous study34. The first antibodies used in this study were as follows: mouse anti-NICD1 monoclonal IgG , mouse anti-TLR4 monoclonal IgG , rabbit anti-TNF-α polyclonal IgG , and mouse anti-β-actin monoclonal IgG . The second antibodies were as follows: goat anti-rabbit IgG-HRP  and goat anti-mouse IgG-HRP . The relative levels of TLR4, NICD1, and TNF-α were normalized to control.TLR4 and NICD1 protein levels in DRG from diabetic neuropathic pain animals and cultured DRG neurons under high glucose challenge were detected by Western blot assay. TNF-α protein levels in DRG from diabetic neuropathic pain animals were also detected by Western blot assay after Notch1 inhibitor DAPT or TLR4 inhibitor TAK treatment. The detailed Western blot assay procedures were as described in our previous study34. The first antibodies were mouse anti-NICD1 monoclonal IgG , mouse anti-TLR4 monoclonal IgG , mouse and chicken anti-MAP2 monoclonal IgG . The second antibodies were goat anti-mouse conjugated to Cy2  and goat anti-chicken conjugated to Cy3 . Upon finishing fluorescence labeling, NICD1-IR and TLR4-IR neurons were counted in five visual fields of each coverslip. One visual field was in the center of the coverslip. The other four visual fields were just adjacent to, but not overlap with, the central visual field at the upper, lower, left, and right side, respectively. The MAP2-IR neurons in the same visual field were also counted as the total number of neurons. Then the percentage of NICD1-IR and TLR4-IR neurons could be obtained.Cultured DRG neurons under different conditions were processed for double fluorescence labeling of MAP2 and NICD1 or TLR4. The double fluorescence labeling procedures were similar to our previous studyP value < 0.05 used to delineate significance for analysis of all results.All experiments were performed in triplicate for each condition as one experiment. Eight experiments (n = 8) were finished for final analysis. All the results were reported as mean ± SD. Non-parametric test was used to compare the abnormally distributed variables. ANOVA was used to compare the normally distributed variables. Post hoc multiple comparative analysis method was used after ANOVA had tested out that the values among various groups are different. If the normally distributed variable is homogeneous of variance, Student-Newman-Keuls test was used. If the normally distributed variable is heterogeneous of variance, Dunnett’s T3 test. All these tests were analyzed by using SPSS (version 19.0) software with


This study aims to understand trends in global fertility from 1950-2010 though the analysis of age-specific fertility rates. This approach incorporates both the overall level, as when the total fertility rate is modeled, and different patterns of age-specific fertility to examine the relationship between changes in age-specific fertility and fertility decline. Singular value decomposition is used to capture the variation in age-specific fertility curves while reducing the number of dimensions, allowing curves to be described nearly fully with three parameters. Regional patterns and trends over time are evident in parameter values, suggesting this method provides a useful tool for considering fertility decline globally. The second and third parameters were analyzed using model-based clustering to examine patterns of age-specific fertility over time and place; four clusters were obtained. A country’s demographic transition can be traced through time by membership in the different clusters, and regional patterns in the trajectories through time and with fertility decline are identified. Fertility change remains an area of concern for demographers and policymakers in large part due to the continued rapid growth of the world population, set to reach 9.7 billion by 2050 with over 50% of growth occurring in sub-Saharan Africa (SSA), predominantly driven by slow fertility decline . DemograWhile most literature that seeks to characterize and understand fertility transition focuses on the TFR, a single number for a place and time, the TFR is built from age-specific fertility rates (ASFR). ASFRs compose the fertility regime that is under analysis when one looks at the TFR. However, very different age patterns of fertility can produce the same TFRs, as can be seen in how age-specific fertility changes across world regions and across time, and do these patterns provide insight into the future of fertility in areas with persistent high fertility? This paper seeks to address primarily the first portion of this question by applying a novel approach to investigating age-specific fertility over time and across countries and searching for patterns that can be associated with fertility decline.The question our approach is seeking to address is, can we find commonalities in This paper aims to present an analytical approach to understanding global fertility trends from 1950-2010 utilizing age-specific fertility rates, from the UN World Population Prospects. To create a quantitative chasracterization of fertility schedules for comparison through time and across countries, we consider the ASFRs rather than the TFR. This approach acknowledges the different ASFRs that may aggregate to similar TFRs but mean something different about fertility transition or decline. This approach is similar to methods used in previous work by the authors and their colleagues –14 and mOther methods have been used to investigate age patterns of fertility. Coale and Trussell’s  model ofWe begin by describing the data we will be using in this analysis. Next we will describe the SVD method used as applied to age-specific fertility curves. Then we will present an illustrative example of this approach using data from Sweden. Then we will show results from applying this method to fertility curves through time for 154 countries and discuss global patterns identified using this approach. Finally, we conclude with a discussion of our findings.Data used for this analysis come from the UN’s World Population Prospects (WPP) 2012 Revision . ASFRs ahttp://esa.un.org/unpd/wpp/.Data from the UN WPP are the most complete data available for global fertility and provide data for 50 years for all countries in the world, despite the fact that these data are already processed, and to an extent, smoothed by the UN. No other data cover as much time for the globe. Additionally these are the same fertility data used by the UN Population Division to inform their global estimates and population projections, and thus finding patterns and understanding the trends in these data will be useful for informing predictions of fertility. These same data have been used in comparative analyses of fertility trends elsewhere as well, for example , 19. Thehttp://fertilitydata.org.An illustrative example is presented below using data from the Human Fertility Collection . SwedishThis section summarizes the material in Clark  which prX such thatU contains the orthonormal  ‘left singular vectors’ ui (columns of U), V contains the orthonormal  ‘right singular vectors’ vi (columns of V), and S is a diagonal matrix containing the ‘singular values’, denoted as si.The singular value decomposition (SVD) (e.g. ) factoriX. The product of the left singular vectors and their corresponding singular values are the projections of the points defined by the rows of X along the new dimensions defined by the right singular vectors.The right singular vectors are a new set of orthonormal dimensions for the points defined by the rows of X) and the best approximations of those points using successively more of the new dimensions defined by V. The singular values correspond to the fraction of the overall squared distance from the origin to the points along the new dimensions V that is captured by each individual new dimension vi. The first new dimension is oriented to capture as much of this perpendicular squared distance as possible, and each successive new dimension captures the most possible of what remains.The SVD is estimated by minimizing the distance between the actual points  the first term in this sum captures or explains the bulk of the variation in the original data (rows of X), and each subsequent term explains less and less. The expression for X in xℓ in X asX as weighted sums of the left singular vectors scaled by their corresponding singular values. The weights are the ℓth elements of each corresponding right singular vector. Moreover, the Eckart-Young-Mirsky matrix approximation theorem [xℓ that are very close to the actual values. This allows us to closely approximate the columns of X with  few effective parameters—just the first few weights.The product of the SVD factors can be algebraically rearranged to yield another equivalent expression called the  formula X=∑i=1ρs theorem  reveals i ∈ {1, …, 6} orthogonal age-varying components si ⋅ ui  and country-time-varying weights associated with those components, the 1,848 elements of each vi.Using the SVD, the 6 × 1,848  matrix of ASFRs from the UN WPP data is factored into s1 ⋅ u1 is the underlying ‘shape’ of the age-specific fertility schedules  early or late fertility and s3u3 accentuates how peaked or flat the curve is. The adjustments made by the second and third components are relatively subtle refinements  but provide important differentiation between age-specific fertility curves over time and across countries.Following , the fir s1u1 in , and thefct is the age-specific fertility schedule for country c in time period t, and i indexes the three SVD-derived age-specific components that we retain. The columns of the original data matrix X are country and time-specific; hence each column is identified by a unique combination of c and t.The first three left and right singular vectors and singular values closely approximate the majority of the 1,848 empirical fertility schedules included in the matrix originally factored using the SVD. Consequently, the model of age-specific fertility that we manipulate isv weights, that are independent and interpretable because they are associated with fixed age-specific components whose age profiles are meaningful.The SVD factorization allows us to work with a high quality, three-parameter approximation of the full age-specific fertility schedules. Beyond having fewer dimensions, the SVD factorization produces effective parameters, the v1 controls the overall level of fertility: as v1 increases, fertility decreases (because we model logged fertility rates)v2 controls the comparative levels of young and old fertility: as v2 increases fertility shifts to older agesv3 controls how concentrated fertility is near the middle of the childbearing years, or how ‘peaked’ the age profile of fertility is: as v3 increases, the age profile of fertility becomes less concentrated in the middle childbearing years.mclust model-based clustering method, we group the two-element ‘weight vectors’ associated with each age-specific fertility schedule into clusters of similar weight vectors, and hence similar fertility schedules. Model-based clustering is conducted using the mclust package in R [We describe how the weights (elements of the right singular vectors) change through time by country and region, and using the age in R  on the sData for Sweden available from the Human Fertility Collection  cover hithree out of 35 components . Component two is primarily functioning to accommodate lower early fertility and higher later fertility (or the opposite for weights of opposite sign) though we see some nuance in how this is affecting the oldest age groups, seeing that at the oldest age group’s fertility is not changing. The third component has a similar structure here as for the UN WPP data, though more nuance through the 20s and 30s, the ages of highest fertility across this data.Using the Swedish data, we obtain similar components from the SVD see  as we sePanel b in v2 are associated with a shift towards higher fertility in later years. The third component similarly starts declining from the beginning of time under study, which corresponds to a flattening of the age-specific fertility curve. However, third component weights are quite volatile from the late 1930s through the 1960s, taking on a strange shape. Following 1960, these weights incline steadily, corresponding to fertility being concentrated in fewer ages, or a more pronounced peak in the curve. Likely, the trends seen starting in the late 60s for these weights are associated with the availability of modern contraception profoundly shaping fertility behaviors.Panels c and d in siui. The first component captures the overall shape of the curve of fertility with age, rising steeply from the first age group to a peak in the second through fourth age groups, and steadily declining thereafter. The weights on s1u1 are all positive. Larger weights on s1u1 result in lower fertility, pulling the curve down, and smaller weights result in higher fertility, pushing the curve up.s2u2 curve bring fertility down in the earliest age groups while simultaneously pulling up fertility at later ages, leaving fertility levels at the second age group unchanged  or to older ages (positive)). Similarly, depending on the sign of the weight on s3u3, combining this curve with s1u1 accentuates/de-accentuates peak fertility, pushing up the fertility rates at the peak ages while suppressing fertility at the extreme ages. Subsequent components made further, more complex and more subtle adjustments to the basic curve given by s1u1.The second component adjusts the earliest and oldest age groups, to accommodate higher or lower early or late fertility, while the third component adjusts the peak fertility age, in the 20s and early 30s, either flattening the curve or intensifying the peak. Positive weights for the ictv, are a parsimonious description of country-specific changes in age-specific fertility rates. Panel (a) in 1ctv are associated with lower overall fertility and the median curve shown in black shows that values of 1ctv have been steadily increasing globally since the 1960s. Though world regions do overlap, we can see distinctly that SSA countries are predominantly at the bottom of the plot, with the lowest values of 1ctv through time and with the smallest increase over time. The West, comprised of the US, Canada, Australia, New Zealand and Europe, had some of the highest values for this weight in the earliest years and has maintained, after a rise in the 1960s and 1970s, high values for this weight. For East Asia we can see a dramatic increase from low levels to the highest values of 1ctv.The country-time specific SVD-derived weights, 1ctv, in Panel (b) of 2ctv changes over time for each country, colored by world region, we do not see the regional patterns that are present in the relationship between 1ctv and time. However, SSA countries seem highly concentrated near zero, in contrast to other regions that experience more variation in values of 2ctv over time. This clearly reveals the lack of age-specific fertility change in SSA compared to other world regions. Tracking individual country lines through time, there appear to be substantial changes in values of 2ctv period to period as well as a wide variety of patterns for overall time trends. Some patterned behavior can be seen for both East Asia and the West, while most other world regions exhibit far less variability and less dramatic change over time.Weights on the second component are largely centered around zero and the variance is much smaller than seen for 3ctv, over time for each country are shown in 3ctv over time do not seem particularly pronounced, though SSA countries seem concentrated just to the positive side of zero, while East Asia and the West seem to have much higher volatility in values and predominantly negative values for 3ctv. As the third component is responsible for how peaked the fertility curves are, we see that SSA values are associated with flatter curves, or curves with peaks that span over multiple age groups, while the West and especially East Asia have curves that are quite peaked with highest fertility occurring in only one age group. This corresponds to general patterns of low overall fertility in these areas, one to two births, often relatively close together while in SSA the highest fertility years span more ages as women tend to have more than two children with sometimes substantial spacing [Weights on the third component,  spacing .1ctv⋅s1u1 curves for the 1848 country-periods included in the data is shown in 1ctv is shown in black. As seen above, this component functions much like TFR, capturing fertility levels. To explore how, independent of fertility level, age patterns of fertility may be similar or different across time and place, we have clustered the weights for the second and third components, which capture differences in young and old fertility and how peaked the fertility curve is. Four clusters of similar age-specific fertility curves were obtained from clustering vectors of the second and third weights. The reconstructed, exponentiated curves obtained are shown in The weighted first component describes the overall level on an age-specific fertility curve. The exponentiated The Traditional cluster has the most classic curve, with minimal variation from the curve created by the first component. This cluster has the highest median fertility, with a TFR of 6, but has curves with a wide range of TFRs, from 0.9 to 8.3. In this cluster, peak fertility occurs at ages 25-29 years, and highest fertility spans ages 20 through 34 years. Fertility is relatively low in the youngest ages and declines steadily and gradually through the 30s and 40s, with fertility at the oldest age group lower than that of the youngest age group. Most SSA curves are in this cluster, and all world regions have curves in this cluster. The Traditional cluster was the largest cluster with 956 age-specific fertility regimes.The Peaked cluster diverges from the basic curve obtained by the first component with a distinctive peak in the middle reproductive years after a rather sharp increase from low early fertility and a relatively sharp decline afterwards. The median curve places this distinct peak at ages 25-29, though curves in this cluster may have earlier peaks, later peaks or peaks that span more than one age group. This cluster had the fewest members, 119 fertility regimes, though there is substantial variation in the shape of these curves despite the unifying peak. The median TFR for these curves is 3.0 but TFRs ranged from 1.0 to 8.0 in this cluster. This cluster contains no curves from Latin America and the Caribbean or from SSA.The Early High cluster is named for its higher fertility at early ages. The median TFR for its 504 member curves was 2.4, over a range of 1.2 to 7.6. The median curve for this cluster peaks at ages 20-24 and then declines steadily. Generally, these curves have a slight decrease or even an increase in fertility from ages 20-24 to ages 25-29 followed by a gradual decline to the oldest ages (some with very slow decline). Curves from all regions except East Asia are represented in this cluster.The Late High cluster is named for its higher fertility at older ages. These curves are similar to those in the Traditional cluster, but while the curves in the Traditional cluster have fertility concentrated at and before ages 25-29 years, in this cluster’s curves fertility is concentrated in ages 25-29 and 30-34 years. Also, fertility at the youngest ages is lower in this cluster than in the Traditional cluster. TFRs for these curves range from 1.2 to 8.4 for the 269 member curves, and median TFR is 4.3. No curves from Latin America and the Caribbean are included in this cluster.Clearly, patterns of decline in SSA’s more advanced fertility declines show similarities to patterns seen in other regions, suggesting the fertility behaviors outlined in Caldwell’s African Exceptionalism will not necessarily keep SSA countries from seeing fertility decline similar to patterns seen in other countries, if not comparatively delayed. Instead, these similar patterns in the more advanced declines of SSA point to the interpretation of Bongaarts and Casterline  that SSAIncorporating age patterns of fertility directly in modeling provides more depth to the analysis of global fertility trends by making explicit how changes in fertility may occur within stable age patterns of fertility and also how changing age patterns of fertility may result in only small TFR changes in the short-term. This analysis makes explicit the idea that many different patterns of fertility can result in similar levels of fertility, or that different levels of fertility can have very similar age patterns. Seeing that no particular age pattern structure was associated with particular fertility levels supports Hirschman’s  observatOur results still support the primacy of the overall level; the explanatory strength of first SVD component and the large membership of the Traditional cluster suggest that the general fertility curve is the most prevalent. However, from our clustering results we see distinctive patterning of differences in age-specific fertility curves that are not associated with fertility level. Categorizing the fertility regimes into clusters allows us to visualize how changes in the age structure of fertility are occurring differently across fertility declines. Our work suggests some regional patterning in how age-specific fertility changes during fertility decline. Looking at the weights on our SVD components and looking at the clustering results, we see very little change in age-specific fertility patterns in SSA. However, we also see virtually no change in these patterns in Latin America and the Caribbean, and for some Asian countries. Casterline and Odden  also finThis analysis demonstrated that dimension reduction of age-specific fertility curves is possible and that with reduced dimensions a coherent story of historical trends can be visualized and analyzed. The Swedish example, with the high quality, annual data spanning over a century illustrates the level of detail in age-specific fertility schedules that can be retained in a fraction of the dimensions. In the global analysis, investigating the patterns of fertility decline and age-specific fertility concurrently allow us to compare patterns of age-specific fertility curves over time across countries, which provides a global context for fertility behaviors seen in individual countries or regions. Specifically, investigating how SSA age-specific fertility patterns fit into global patterns, we can see that for SSA countries with more advanced fertility declines, their patterns of age-specific fertility are similar to patterns found in other regions.


This cross-sectional study evaluated the prevalence of infection with human T-lymphotropic virus 1 and 2 (HTLV-1 and HTLV-2) in a population from the municipalities of Anajás, Chaves, São Sebastião da Boa Vista (SSBV) and Portel in the Marajó Archipelago and correlated these data with the epidemiological characteristics of the study population.A total of 1899 biological samples were evaluated. The samples were screened for the presence of anti-HTLV antibodies using an enzyme-linked immunosorbent assay (ELISA), and infection was confirmed using conventional polymerase chain reaction (PCR), real-time PCR and nucleotide sequencing.Eleven samples (0.58%) were seropositive for HTLV, but molecular analysis confirmed positivity in only two samples (0.11%). Nucleotide sequencing and phylogenetic analysis indicated that the two samples positive for HTLV-1 that were isolated in Chaves belonged to the Cosmopolitan subtype 1 (HTLV-1a) and Transcontinental subgroup (A).Our results confirmed the presence of Cosmopolitan Transcontinental HTLV-1 in the Marajó Archipelago, Amazon region, and the majority of the population revealed a lack of knowledge about sexually transmitted infections, which increases the risk of dissemination of HTLV and other agents. Retroviridae, subfamily Oncovirinae, genus Deltaretrovirus , following the manufacturer recommendations.DNA was extracted from peripheral blood leukocytes using the Biopur extraction kit  following the manufacturer’s instructions. DNA was quantified using a Qubit 2.0 Fluorometer . The samples considered valid for polymerase chain reaction (PCR) contained at least 20 ng of DNA. The DNA was re-extracted from the stored blood aliquot, in samples with less than 20 ng of DNA.2O, 4.0 μL of extracted DNA, 10.0 μL of 1.25 mM dNTP, 1.5 μL of each primer (20 pmol), 1.5 μL of 50 mM MgCl2, 5.0 μL of 10× buffer  and 0.25 μL of Taq DNA polymerase (5 U/μL) in a final volume of 50 μL. A second reaction step (nested PCR) was conducted using 4.0 μL of the previous amplification product under the same conditions described.The pX region was amplified to confirm infection by the presence of proviral HTLV DNA in individuals who met the serological criteria . The amp2O, 4.0 μL of buffer E , 0.4 μL of BSA and 1.0 μL of the restriction enzyme Taq I  and incubating the reaction at 65 °C for 5 hours. The presence of the T/CGA site generated three fragments , which are present in HTLV-2 but absent in HTLV-1.The amplification product (159 bp) was subjected to restriction fragment length polymorphism (RFLP) analysis to assess the presence of a restriction site (T/CGA) for the Taq I enzyme, which is found only in HTLV-2, to distinguish the viral types present. The RFLP analysis of the pX gene product was conducted by mixing 20.0 μL of the amplification product (nested PCR), 14.6 μL of H2O, 2.0 μL of extracted DNA, 8.0 μL of 1.25 mM dNTP, 1.5 μL of each primer (20 pmol), 2.5 μL of 50 mM MgCl2, 5.0 μL of 10× buffer  and 0.3 μL of Taq DNA polymerase (5 U/μL) in a final volume of 50 μL. A second reaction step (nested PCR) was conducted using 2.0 μL of the previous amplification product under the same conditions described.Nucleotide sequencing involved the amplification of the 5′ LTR region (788 bp) . Each re2/1000 mL deionized water) and visualized under ultraviolet light using a transilluminator.The products of amplification of pX and 5′ LTR and the products of enzymatic digestion were separated by electrophoresis (100 V for 45 min) using a 3% agarose gel in 1× Tris-acetate-EDTA (TAE) buffer  5′- gaacgctctaatggcattcttaaaacc-3′, (HTLV1R) 5′- gtggttgattgtccatagggctat-3′, (HTLV1 probe) 5′- FAM-acaaacccgacctaccc-NFQ-3′]. Albumin gene was used as endogenous control  .The reactions were performed in a StepOne PLUS™ Real-Time PCR System , and for each reaction, [1X] TaqMan® Universal PCR Master Mix, [1X] of TaqMan® Assay [20X], and 20 ng DNA in a final reaction volume of 20 μL were used. After an initial incubation of 2 min at 50 °C, 10 min at 95 °C, followed 50 cycles of 50 s at 95 °C and 1 min at 60 °C.The amplification products of the 5′ LTR region were purified to optimize nucleotide sequencing. Purification was performed using the PureLink® PCR Purification Kit . Nucleotide sequencing was based on the biochemical synthesis of DNA using the ABI PRISM™ 310 BigDye Terminator v3.1 kit Matrix Standards (Applied Biosystems) and the method of Sanger et al. . The DNAhttps://blast.ncbi.nlm.nih.gov [The genetic similarity between nucleotide sequences of the strains isolated herein and those available in the Genbank was accessed using the Basic Local Alignment Search Tool (BLAST) online platform from the National Center for Biotechnology Information (NCBI), available at .nih.gov –28.The sequence alignment of 437 bp from 5′LTR was performed using the Clustal W program implemented in BioEdit software version 7.1.9 . The phyThe prevalence rates were estimated by calculating the number of individuals who have the desired characteristics searched at a given point in time over the total number of individuals evaluated. The values of the variables analyzed were presented as percentages.The statistical reliability of Bayesian tree was evaluated using 1000 boostrap. The tree was viewed using the FigTree v1.4.0 program .In the studied population Table , there wWith regard to education, 905 individuals (54.98%) in the four municipalities were literate, 273 individuals (16.59%) were illiterate, 215 (13.06%) individuals had received a primary education, 180 (10.94%) had received a secondary education, and 73 (4.43%) had received a higher education. The lowest gross household incomes (less than one minimum monthly wage) were found in SSBV (52.81%). An income comprising one to three minimum monthly wages was more prevalent in Anajás (54.61%), Portel (73.87%) and Chaves (63.36%).Table With regard to sexual orientation, 95.14% of the study population claimed to be heterosexual. The municipality of Anajás presented the lowest prevalence of heterosexuals (90.64%) and the highest prevalence of homosexuals (8.87%). When inquired about the use of illicit drugs, 96.19% of the study population reported having never used them. Most (53.08%) of the respondents had initiated their sexual life at the age of 16 to 20 years. In addition, 74.09% of the study population was sexually active, and 93.41% reported not having sex with sex workers.Of the 1899 samples tested with ELISA, 11 (0.58%) samples were positive and eight (0.42%) samples showed an indefinite pattern for antibodies against HTLV-1/2. The signal to cutoff ratio of these samples as well as data on age, sex and municipality are shown in Table Of the 19 seropositive samples, only two were truly positive for HTLV infection, which was confirmed by amplification of the 159-bp fragment of the pX gene. This result indicated that the prevalence of infection with the virus in the study population was 0.11%.Taq I enzyme, which indicates infection with HTLV-1. Real-time PCR also confirmed the HTLV-1 infection in these two samples. In all of the samples, the human albumin gene was amplified. The two infected individuals (#146 and #180) lived in Chaves.These two samples showed no restriction site for the Nucleotide sequencing and phylogenetic analysis Fig.  indicateThe two infected individuals (#146 and #180) lived in Chaves. Sample #146 belonged to a woman who was 53 years old, single and homosexual and who had reported not having used illicit drugs, initiated her sexual life at the age of 10–15 years and reported never using condoms. Sample #180 belonged to a woman who was 31 years old, married and heterosexual and reported not having used illicit drugs, initiated her sexual life at the age of 16–20 years and reported never using condoms.Chlamydia pneumoniae, Chlamydia trachomatis, Treponema pallidum and Plasmodium vivax. The antibody reactions to cytomegalovirus (100%), rubella virus (82%), hepatitis A virus (64%) and P. vivax (36.36%) were expressive; however, an antibody reaction to HIV was not observed.Table The Brazilian Institute of Geography and Statistics (Intituto Brasileiro de Geografia e Estatística–IBGE) reported a small difference in the percentage of men and women distributed in the municipalities of the Marajo archipelago, with a predominance of men . HoweverThere was a significant number of children and individuals younger than 20 years in the population studied. In this respect, it has been reported that the prevalence of HTLV-1 is high between the third and fifth decades of life ; howeverThe analysis of the education level indicated that the illiteracy rate was not considerable, accounting for the percentage of literate individuals and those with up to 8 years of education (primary education). However, the 16.5% of the population who were illiterate cannot be ignored because a low level of education is a risk factor for infection with HTLV . These dThe prevalence rate of HTLV infection of 0.11% (2/1899) observed in Marajó is considered low compared to the rate of 1.8% recorded in Salvador, which is the highest rate recorded in Brazil. In some specific risk groups, including pregnant women in Mato Grosso do Sul   and blooN = 259) in Quilombola communities in Marajó, where cases were found in the municipalities of Santana do Arari (2.06%) and Ponta de Pedras (1%). By contrast, a prevalence of HTLV-2 infection of 1.06% was found in Santana do Arari [The occurrence of two cases of HTLV-1 in Chaves agrees with the evidence of the infection with this virus type in urban and rural populations in the Brazilian Amazon. A group of researchers in northern Brazil found a prevalence of HTLV-1 carriers of 3.06% (do Arari .N = 1324) was found in indigenous communities in the Amazon [The prevalence of HTLV-2 has been reported among Amerindian peoples in Brazil and other countries. A high prevalence of HTLV-2  was identified in Quilombola villages in Bahia, and a phylogenetic analysis indicated the occurrence of African migration during the slave trade .Both HTLV-1 isolates from Chaves belonged to the Cosmopolitan subtype and Transcontinental subgroup (HTLV-1aA). This viral subtype is widely distributed throughout the world and is endemic in Africa, Asia and the Americas .In Mozambique, the screening of blood donors and patients infected with HTLV via nucleotide sequencing of the LTR region indicated that all HTLV-1 isolates belonged to the Cosmopolitan Transcontinental subtype . In CubaHTLV-1aA is the major circulating viral subtype in Brazil, and the states of Bahia , São PauIn Pará, the Cosmopolitan subtype, Transcontinental subgroup was the only subtype observed in urban and coastal areas , except The prevalence of HTLV-1 varies according to age, gender and economic status in most areas where the virus is endemic . In thisThe prevalence of HTLV infection increases considerably starting at age 30 and is higher among women. This result is because the retrovirus is transmitted more efficiently from men to women. The risk of spread is directly proportional to the advanced age of the male partner, high proviral load and the length of the relationship . This reThese results corroborate the prevalence of HTLV in two women in Chaves. We highlight that approximately 70% of the study sample were women, and this predominance may have influenced the results.The main risk factors for infection with HTLV are low socioeconomic status, low education and risky sexual behavior . A case-In this study, both women reported early sexual initiation and never having used condoms. One woman had three sexual partners over her lifetime; however, both women denied having relations with sex workers or having contracted STDs. One woman did not know what STDs were. Risky sexual behavior has been shown to be a facilitator of HTLV infection .With regard to the diagnostic methods, some factors may influence the occurrence of false positive results in ELISA, including a low titer of anti-HTLV antibodies, low proviral load, infection with other retroviruses and cross-reactivity against other parasitic agents, particularly those that cause malaria, which is endemic in Pará . NotablyUltimately, our results suggest the low specificity of ELISA and reinforce the importance of the implementation of molecular techniques in the routine practice of health and surveillance centers to increase the reliability of epidemiological data on HTLV.Our results confirmed the presence of Cosmopolitan Transcontinental HTLV-1 in the Marajó Archipelago, Amazon region, and the majority of the population revealed a lack of knowledge about sexually transmitted infections, which increases the risk of dissemination of HTLV and other agents.


In this study, simultaneous electrochemical detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) was performed using a modified graphite paste electrode (MGPE) with epigallocatechin gallate (EGCG) and green tea (GT) powder. It was shown that the anodic peak current increased in comparison with that of the graphite paste electrode (GPE) in the cyclic voltammograms. The optimal pH for simultaneous determination of a quaternary mixture of AA–DA–UA was determined to be pH 2. The anodic peak potentials for a mixture containing AA–DA–UA were well separated from each other. The catalytic peak currents obtained at the surface of the MGPE/EGCG were linearly dependent on the AA, DA, and UA concentrations up to 23, 14, and 14 µM, respectively. The detection limits for AA, DA, and UA were 190, 90, and 70 nM, respectively. The analytical performance of this sensor has been evaluated for simultaneous detection of AA, DA, and UA in real samples. Finally, a modified electrode was prepared using GT and used for simultaneous determination of AA, DA, and UA. Based on the results, MPGE/GT showed two oxidation peaks at 0.43 and 0.6 V for DA and UA, respectively, without any oxidation peak for AA. The calibration curves at the surface of MGPE/GT were linear up to 14 µM with a detection limit of 0.18 and 0.33 µM for DA and UA, respectively. MGPEs provide a promising platform for the future development of sensors for multiplexed electrochemical detection of clinically important analytes. Tea is one of the most widely consumed beverages in the world, with the main varieties being green and black. Green tea is produced by precluding the oxidation of polyphenols present in the leaf compared to black tea where oxidation of the polyphenols is promoted . Green tEGCG, in particular, has been shown to have interesting properties including many potential therapeutic benefits such as anti-inflammatory ,4, anti-Modification of electrode surfaces using organic molecules is an exciting area of research with many interesting applications. Electrochemical modification using oxygenated functional groups such as carboxylic, hydroxyl, quinone, and other ketonic groups have been reported ,15. In aUsing the EGCG-modified graphite paste electrode (GPE), we were able to simultaneously detect AA, DA, and UA in the concentration ranges of 1–10 and 10–23 μM for AA, and 0.5–5 and 5–14 μM for both DA and UA. The theoretical detection limits were obtained as 190, 90, and 70 nM for AA, DA, and UA, respectively. Additionally, we have also reported a green tea (GT) powder modified GPE for the successful electrochemical detection of DA and UA using DPV. Since catechins constitute up to 30% of the dry leaf weight, we wanted to examine whether a GPE directly modified with green tea powder  could be deployed for the detection of clinically important analytes. While the green tea powder-modified electrode was able to successfully detect two out of the three analytes (DA and UA), its performance was inferior compared to the EGCG–MGPE. This suggests that modifying electrodes with the pure extracted polyphenol compound, in fact, increases the performance of the electrochemical sensor.3PO4 (0.1 M); the pH range was adjusted to 2.0–5.0 with 0.1 M H3PO4  with NaOH  solutions 0.1 M and these PBS solutions were used as supporting electrolytes. Green tea was purchased from Hamasaen (Japan). All solutions were prepared with ultra-pure Milli-Q water with a resistivity of 18.2 MΩ cm. Epigallocatechin gallate was purchased from Sigma-Aldrich . High purity graphite powder, ascorbic acid (AA), dopamine (DA), uric acid (UA), potassium ferrocyanide, and potassium ferricyanide were purchased from Sigma-Aldrich . Phosphate buffer solution (PBS) was prepared from H6]3−/4− prepared in 0.1 M KCl over a frequency range of 0.1 Hz to 10 kHz with 0.02 V amplitude (rms). A Metrohm Titrando pH meter (model 888) was used for pH measurements.Electrochemical measurements and electrochemical impedance spectroscopy (EIS) were carried out with a µAutolab PGSTAT 128N  potentiostat/galvanostat controlled by NOVA 2.0 software. All electrochemical experiments were carried out in a conventional three-electrode cell at room temperature. A platinum counter electrode and an Ag/AgCl reference electrode were used in connection with a GPE and MGPE/EGCG or MGPE/GT as the working electrode. Electrochemical impedance spectroscopy (EIS) measurements were performed in 10 mM  − 0.8033 (R2 = 0.9907), ΔIp2(AA) = 0.2194[AA] + 5.5343 (R2 = 0.9752), ΔIp1(DA) = 2.1178[DA] + 0.304 (R2 = 0.9918), ΔIp2(DA) = 0.8895[DA] + 7.1107 (R2 = 0.9986), ΔIp1(UA) = 1.7279[UA] − 1.2067 (R2 = 0.9849), and ΔIp2(UA) = 0.8248[UA] + 3.9679 (R2 = 0.9996), respectively. We hypothesized that the difference in the slopes for the calibration curves was due to different activities of the surfaces at low and high concentrations of the analytes. At lower concentrations of the analytes, due to a high number of active sites on the surface, the slope of the first calibration curve is high. While at higher concentrations of the analytes, due to decreasing active sites on the surface, the slope of the second segment of the calibration curve shows a decrease. The detection limit was calculated based on the relationship LOD = 3 Sblank/m, where Sblank is the relative standard deviation of blank signals (n = 10) and m is the slope of the calibration plot. The theoretical detection limits were obtained as 190, 90, and 70 nM for AA, DA, and UA, respectively.Electrocatalytic peak currents of AA, DA, and UA oxidation at the surface of MGPE/EGCG are linearly dependent on the analyte concentrations with two segments in the range of 1–10 and 10–23 μM for AA and 0.5–5 and 5–14 μM for both DA and UA. The regression equations for AA, DA, and UA were obtained as ΔITo evaluate the practical applicability of the proposed modified electrode, the MGPE/EGCG was utilized for the simultaneous determination of AA, DA, and UA in vitamin C tablets, human urine, and blood serum samples. The samples were diluted in PBS and DPV was performed for the simultaneous determination of AA, DA, and UA using the standard addition method. As depicted in n = 9) simultaneous determinations of AA, DA, and UA and the results are shown in a values for AA, DA, and UA were retained at 95.3, 96.5, and 94.3%, respectively. Therefore, we conclude that the electrooxidation current responses of AA, DA, and UA at the MGPE/EGCG surface has excellent repeatability, reproducibility, and stability.The stability and repeatability of the MGPE/EGCG surfaces were investigated using DPV for repetitive (p(DA) = 0.8243[DA] + 0.4585 (R2 = 0.9944) and ΔIp(UA) = 0.4152[UA] + 0.2639 (R2 = 0.9912), respectively. We hypothesized that the difference in the slopes for the calibration curves of MGPE/EGCG and MGPE/GT is due to the different activity of the modifier in the MGPE. The sensitivity values for determining DA and UA at the surface of the MGPE/EGCG are 2.6 and 4.2 /(MGPE/GT)), which is more than for MGPE/GT and is attributed to the modifier catalytic activity of the pure EGCG being greater than GT powder.An electrode modified with green tea powder was used to simultaneously determine AA, DA, and UA and the results are shown in We have demonstrated for the first time a green tea derivative (EGCG) modified GPE for the simultaneous determination of AA, DA, and UA. We have also presented a GPE modified directly with green tea powder  and have shown that we were able to successfully detect two out of the three analytes tested. Compared with the bare electrode, a significant increase in peak current was observed at the MGPE/EGCG electrode, which clearly demonstrates that EGCG can be used as an efficient modifier to enhance the kinetics of the electrochemical process of AA, DA, and UA. Optimization of the experimental conditions yielded a detection limit for AA, DA, and UA of 190, 90, and 70 nM, respectively. In addition, the presented sensor was successfully applied for the simultaneous determination of AA, DA, and UA in real samples with promising results for future development as a diagnostic device. A future application of this developed sensor could be as a wearable  or an in


Two commercially available fragment libraries were screened computationally for possible inhibitors and a selection of fragments was subsequently tested in vitro. The screening setup consisted of two orthogonal assays measuring TSLP binding to TSLPR: a BLI-based assay and a biochemical assay based on a TSLP:alkaline phosphatase fusion protein. Four fragments pertaining to diverse chemical classes were identified to reduce TSLP:TSLPR complex formation to less than 75% in millimolar concentrations. We have used unbiased molecular dynamics simulations to develop a Markov state model that characterized the binding pathway of the most interesting compound. This work provides a proof-of-principle for use of fragments in the inhibition of TSLP:TSLPR complexation.The pro-inflammatory cytokine thymic stromal lymphopoietin (TSLP) plays a pivotal role in the pathophysiology of various allergy disorders that are mediated by type 2 helper T cell (Th2) responses, such as asthma and atopic dermatitis. TSLP forms a ternary complex with the TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Rα), thereby activating a signaling cascade that culminates in the release of pro-inflammatory mediators. In this study, we conducted an  Figure 5, which in turn regulates immunity at these barrier surfaces. Dysregulation of this system is known to result in the development of atopic disease, which is a group comprised of three different conditions: asthma, atopic dermatitis and atopic rhinoconjunctivitis6. These diseases place a significant burden on healthcare systems throughout the world. In addition to its role in atopic disease, TSLP has also been implicated in various other pathophysiologies, such as chronic obstructive pulmonary disorder and corticosteroid resistance5. The potential role of TSLP in cancer development/progression is currently unclear and is still a topic of ongoing investigation. While some studies have provided evidence for a tumor-promoting role8, other studies have shown that TSLP does not play any significant role in tumor progression10.The pro-inflammatory cytokine, thymic stromal lymphopoietin (TSLP), is produced by skin keratocytes and epithelial cells of the lung and gut in response to pathogenic stimuli. TSLP signaling causes dimerization of the cognate TSLP receptor (TSLPR) and the interleukin-7-receptor subunit alpha (IL-7Rα) at the cell surface. TSLP is initially captured at the cell surface by a high affinity interaction with TSLPR (kD = 32 nM). Thereafter, IL-7Rα is recruited to the TSLP:TSLPR complex in a high affinity manner (kD = 29 nM) to elicit further intracellular signaling12. TSLP traps, which are constructed by fusing the TSLPR and IL-7Rα extracellular regions together, have also demonstrated promising results13. Unfortunately, biologicals generally suffer from limited tissue penetration, a lack of oral bioavailability and high production costs14. Furthermore, they often present with complicated intellectual property situations15. We therefore feel a small molecule approach would provide a useful parallel form of targeting. Protein-protein interactions have generally been regarded to be difficult targets for the development of small molecule inhibitors, due to their oftentimes flat and extensive nature. However, it appears that not all residues contribute equally: a limited number of residues is often responsible for the majority of binding energy16. Residues accounting for more than 2 kcal/mol of the binding energy are known as hotspots. Bogan et al. found that tyrosine, tryptophan and arginine residues are over-represented in hotspots17. The discovery of hotspots has been of critical importance for the field of small molecule protein-protein inhibitors and as such, inhibitors for various targets have been developed in recent years, for instance Amgen’s MDM2-p53 inhibitor AMG23218, Sunesis Pharmaceuticals’ IL2-IL2R inhibitor SP420619 or AbbVie’s ABT-19920, which targets B-cell lymphoma-2 (BCL2). In order to provide sufficient binding energy to compete with the native protein-protein interaction, protein-protein inhibitors tend to span several small pockets, making them larger than conventional drug molecules21. The aim of this study was to analyze the TSLP:TSLPR:IL7Rα complex with an emphasis on the druggability and to leverage this information in order to identify a fragment capable of disrupting the formation of the complex through a combined virtual screening – in vitro screening cascade.The relevance of TSLP as a therapeutic target has been demonstrated in a clinical trial conducted by Amgen, where administration of the TSLP blocking antibody, Tezepelumab, resulted in a decrease of the baseline variables for airway inflammation, as well as a reduced sensitivity to various allergens12. The TSLPR-binding epitope of TSLP consists of the TSLP helix D, the C-terminus and a large section of the TSLP AB loop. TSLP and the TSLPR ectodomain demonstrate a pronounced electrostatic complementarity, with TSLP presenting a positively charged surface patch to the negatively charged TSLPR interdomain elbow. We elected to target the TSLP:TSLPR interface for three important reasons. Firstly, the binding of TSLP to TSLPR is a mechanistic prerequisite for the formation of the cooperative ternary complex22. In absence of TSLPR, IL-7Rα does not have any measurable affinity for TSLP. Secondly, through targeting TSLPR, we hope to avoid any off-target effects on the IL-7 pathway. Thirdly, the TSLP:TSLPR interface appears to be more tractable than the TSLP:IL7Rα interface from a drug-design context, due to the presence of a well-defined binding cleft and the polar character of the interface. The interface is shown in the Fig. The crystal structure of the human TSLP:TSLPR:IL-7Rα complex has recently been elucidated through X-ray crystallography by Verstraete and coworkers (PDB code 5J11)in silico methods to examine the TSLP:TSLPR binding site and evaluate possible hotspots. Possible hotspots in the TSLP:TSLPR complex were examined with PredHS, a machine learning web-based tool which predicts residues that account for the majority of binding energy based on structural neighborhood properties to identify hotspots in the TSLP:TSLPR complex23. The PredHS support vector machine method predicts TSLP residues TSLP-Arg149, TSLP-Arg150 and TSLP-Arg153 to be essential for the binding process as shown in Fig. 5012. Moreover, mutation of the contacting TSLPR residues TSLPR-Asp92 and TSLPR-Trp112 into alanine resulted in a thousand fold increase in EC5012. The three essential TSLP arginine residues bind to TSLPR in the binding cleft in which TSLPR-Asp92 and TSLPR-Trp112 are located, which is a promising result for the development of small molecule inhibitors.We used established 24. This technique scans the surface of TSLPR using a variety of computational solvent probes, clustering the solvent probes to identify sites that are prone to binding small molecules. Two sites were identified near the TSLP binding cleft as displayed in Fig. As an orthogonal technique, computational solvent mapping was performed on TSLPR with FTMap3 search box was defined around the binding cleft. The 1,000 compound Enamine Gold Fragment library and the 2,500 compound Maybridge rule-of-three diversity library were then docked into TSLPR. Docking was performed using Autodock Vina 1.1.225. The top five poses of each ligand were rescored using DSX 0.8826. The top scoring ligands, judged by raw scores as well as normalized scores, were inspected manually with specific attention to their conformations and the interactions with the pocket. Sixty fragments were selected for in vitro analysis and therefore purchased from their respective vendors 12. TSLPR was incubated with TSLP-AP and the fragment at a concentration of 2.5 mM, followed by a washing step and quantification of the phosphatase activity of the fusion protein. This AP activity is a measure for TSLP:TSLPR binding, i.e. reduction of AP activity indicates reduced TSLP:TSLPR complexation. Eighteen fragments displayed less than 75% residual activity in the AP-based assay. The second assay employed bio-layer interferometry (BLI)27, whereby TSLP was immobilized onto a sensor tip and dipped into a solution containing TSLPR and a fragment at a concentration of 2.5 mM. The assay results for BLI and AP are shown in Fig. A two-stage biological screening was used to assess the Four fragments reduced the TSLP:TSLPR binding to less than 75% in both assays. Their structures are annotated in Fig. 28. This resynthesized compound will be denoted as fragment 3*. A second BLI screening was then performed in duplicate for the top four compounds and the resynthesized compound, confirming that fragment 3* exhibits similar inhibition to the original fragment 3  was constructed as follows31. Contacts between the protein and ligand were used as features. These features were transformed using time-structure independent components analysis (TICA)32 with a lag time of 10 ns, retaining three dimensions and clustered into approximately 500 microstates with MiniBatchKMeans. These microstates were then used to construct an MSM, which resolved four kinetically distinct macrostates: the bulk state, two metastable states and the bound state . Binding events where the ligand passes through the intermediate states were rare: 0.3% of binding events occur through the first metastable state, while the second metastable state accounts for 0.8% of binding events. Finally, the MSM can be used to estimate thermodynamics of binding. The dissociation constant Ket al. and was shown to inhibit TSLP-driven activation of dendritic cells12. Furthermore, a recent study by Park and coworkers has explored the potential of peptide-derived inhibitors, resulting in three peptides capable of TSLP inhibition at submillimolar concentrations33. However, biologicals generally present with a number of challenges: they have low tissue penetration, are not orally active and are expensive to produce. We therefore feel the development of a small molecule inhibitor would be a useful parallel avenue to explore.The aim of our study was to explore a parallel avenue towards the development of TSLP:TSLPR interaction inhibitors. Indeed, biologicals have been the main paradigm in inhibition of TSLP signaling and in inhibition of protein-protein interfaces in general. One of the most prominent achievements in the field has been Amgen’s development of an anti-TSLP monoclonal antibody Tezepelumab, also known as AMG157. Currently in phase II clinical trials, it has been shown to be a useful tool for the management of moderate-to-severe asthma, highlighting the relevance of TSLP signaling as a therapeutic target. A fusion protein consisting of the ectodomains of TSLPR and IL-7Ra, also known as a TSLP-trap, has been developed by Verstraete 3. Following an in silico characterization of the TSLP:TSLPR interface, a docking experiment was performed to identify inhibitors. A set of sixty fragments was purchased in order to validate our results in vitro, of which four fragments were shown to be active in two different assays. A limitation of the assay setup is that both assays measure TSLP:TSLPR interaction, rather than directly quantifying the binding of the fragment to TSLPR. One fragment was selected for further examination due to its favorable structure and synthetic accessibility. We performed molecular dynamics in order to develop a Markov state model, which was used to explore the binding pathway and mode of binding. Our model indicates that the fragment binds at the TSLP binding site and that the TSLPR site undergoes a conformational change of the TSLPR site that may be required for fragment binding.In this study, we present the results of a proof-of-principle fragment–based screening campaign with the aim of identifying fragments capable of disrupting the TSLP:TSLPR complex. The interactions leading to this binary complex are a mechanistic prerequisite for the recruitment of the shared receptor IL-7Rα to establish the pro-inflammatory signaling assembly mediated by TSLP in allergy and asthma34. Fragment growing is the most commonly employed technique and will be the initial focus of follow-up research, as the binding sites of the fragments are not yet known, hindering the use of fragment linking, and no scaffolds for TSLPR inhibition have been described thus far, rendering fragment merging difficult. Crystallography of a fragment in complex TSLPR would be invaluable for fragment growing. Indeed, structural information about the complex under the form of crystal structures or NMR structures is regarded as indispensable for fragment optimization in some organizations. However, modeling techniques such as the MSM presented herein can also be used to guide the synthetic effort.Going forward, the main challenge will be expanding the fragments identified in this work into more potent lead molecules. Such inhibitors could further help elucidate the potential role of TSLP in various pathophysiologies and could also be a starting point for the development of drugs targeting this pathway. Three main strategies for the elaboration of fragments have been used in literature: linking fragments that bind to different sites together chemically, merging fragments with existing scaffolds and growing fragmentsin vitro screening approach to identify the first fragments to inhibit the TSLP:TSLPR interaction, providing a proof-of-principle for the use of fragments in the modulation of TSLP signaling.In conclusion, we have successfully used a combined virtual – 12. PredHS hotspot prediction was performed on the TSLP:TSLPR complex. FTMap was run on TSLPR with the complex partners deleted in protein-protein interaction mode using the default probe set consisting of acetamide, acetonitrile, acetone, acetaldehyde, methylamine, benzaldehyde, benzene, isobutanol, cyclohexane, N,N-dimethylformamide, dimethyl ether, ethanol, ethane, phenol, isopropanol and urea.The coordinates for the crystal structure of the human TSLP:TSLPR:IL-7Rα complex used in all calculations were kindly provided by Kenneth Verstraete and a further refined version of this structure was deposited to the PDB under identifier 5J1135 structure preparation tool and converted into a PDBQT file.The Enamine golden fragment database  and Maybridge fragment library  were downloaded from their respective vendor sites. The compound files were imported into MOE and processed through the database wash protocol. This protocol assigns relevant protonation states and generates 3D coordinates. These were then converted to Autodock Vina’s PDBQT format. The receptor was processed using the MOE29. General Amber force field (GAFF)36 parameters for the ligand were obtained using FESetup37. The TIP3P water model was used for solvent and Amber99sb-ildn was used for the protein and ions38.All molecular dynamics simulations were performed with Gromacs 5.1.2All frames of the trajectory were centered on the protein backbone atoms and aligned to a common reference frame. The contacts between the protein and the ligand were then extracted as features. These features were transformed using a 10 ns lag time TICA, retaining three dimensions. MiniBatchKMeans clustering with a cluster number of 500 was then performed, merging clusters containing fewer than five points. These clusters were used to construct a Markov state model with a lag time of 15 ns and 4 macrostates.12 in TBS-T buffer and subsequently washed three times with TBS-T. Wells were incubated for 4 hours with TBS-T containing 2.5 mM fragments, 2.5% DMSO and 1/60 diluted cell culture supernatant containing recombinant hTSLP-alkaline phosphatase fusion protein12. Wells were washed three times with TBS-T buffer, and bound alkaline phosphatase activity was determined using the PhosphaLight kit (Tropix) and an Envision chemiluminescence counter (PerkinElmer). Luminescence signals of samples containing fragments were compared with luminescence of samples containing hTSLP fusion protein and 2.5% DMSO without fragment.Black 96-well Maxisorp plates (Nunc) were coated with 0.25 µg/ml anti-penta-His antibody (Qiagen) in 50 mM sodium carbonate/bicarbonate buffer pH 10.6., followed by a 2 hour blocking with 1% bovine serum albumin in Dulbecco’s phosphate buffered saline (Gibco). Wells were washed three times with TBS-T buffer . Wells were incubated for 2 hours with 1 µg/ml recombinant his-tagged ectodomain of the human TSLP receptorR127A/R130S  carrying a C-terminal AVITAG at its C-terminus12 and quenched with a 10 µg ml−1 biotin solution. The human TSLPR ectodomain  was produced from stable transfected HEK293S-TetR MGAT1−/− cells was used as analyte at a concentration of 100 nM12. Compounds were included in the TSLPR containing wells to give a final concentration of 2.5 mM. The data was analyzed using FortéBio Data Analysis 9.0.0.4. For all measurements a column of non-functionalized sensors was used to enable parallel reference subtraction.BLI experiments were performed in PBS-buffer supplemented with 0.01% (w/v) BSA, 0.002% (v/v) Tween 20 and 2.5% DMSO, with an Octet RED96 instrument (FortéBio), operating at 25 °C. Streptavidin-coated sensor tips were functionalized with mammalian-derived biotinylated human TSLPSixty compounds were tested in the first BLI-screen using one column of sensor tips functionalized with 1 nm of biotinylated hTSLP and one column of reference tips. By using eleven serial cycles of a 200 s association phase followed by a 700 s dissociation phase a single sensor tip was used to measure multiple compounds. The relative response for each measurement was calculated as the response at the end of the association phase divided by the average response of control samples (100 nM TSLPR without compound).2SO4. The relative response (%) was calculated as the response at the end of the association phase divided by the average response of a 100 nM TSLPR measured in the cycles directly preceding and following each control (100 nM TSLPR) or sample (100 nM TSLPR + compound). Each compound was measured in duplicate.In the second BLI-screen five compounds were tested using one column of sensor tips functionalized with 1 nm of biotinylated hTSLP and one column of reference tips. Each tip was used for 22 serial cycles consisting of a 100 s equilibration phase, a 100 s association phase, a 20 s dissociation phase and a 3 × 5 s regeneration cycle in 0.5 M H4-chloropyridine hydrochloride , sodium 2-methylpropan-2-olate  and 9,9-dimethyl-4,5-bis(diphenylphosphino)xanthene  were placed in an argon flushed high pressure tube and suspended in dioxane (5 ml) which was previously degassed by bubbling with argon. This suspension was degassed by bubbling with argon. Tris(dibenzylideneacetone)dipalladium(0)  was added, after which the suspension was again degassed by bubbling with argon. Cyclopentanamine  was added and the suspension was degassed by bubbling with argon for 10 minutes. The tube was sealed and the reaction was stirred at 90 °C overnight. The resulting suspension was filtered through celite and washed with methanol. Reverse phase chromatography using a methanol-water gradient yielded N-cyclopentylpyridin-4-amine .Proton NMR: 1H NMR  δ 1.42 , 1.55 , 1.65  1.91 , 3.72 , 6.44 , 6.47 , 7.98 .The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.Supplementary information


Human papillomavirus (HPV) is the most prevalent sexually transmitted infection, affecting an estimated 11% of the world’s population. The high-risk HPV types (HR HPV) account for approximately 5% of the global burden of cancer and thus cause high morbidity and mortality. Although it is known that persistent infection with HR HPV is the greatest risk factor for developing HPV-associated cancer, and that the HPV early proteins E6 and E7 dysregulate immune detection by its host cells, the mechanisms of immune evasion by HR HPV are not well understood. Previous work in the laboratory identified the endogenous cytoplasmic host protein NFX1-123 as a binding partner of the HR HPV type 16 oncoprotein E6 (16E6). Together NFX1-123 and 16E6 affect cellular growth, differentiation, and immortalization genes and pathways. In a whole genome microarray, human foreskin keratinocytes (HFKs) stably expressing 16E6 and overexpressing NFX1-123 showed a diverse set of innate immune genes downregulated two-fold or more when compared to 16E6 cells with endogenous NFX1-123. We demonstrated that 16E6 and NFX1-123 decreased expression of pro-inflammatory cytokines and interferon-stimulated genes (ISGs) in 16E6 HFKs at the mRNA and protein level. Knock down of NFX1-123 in 16E6 HFKs resulted in a derepression of innate immune genes, pointing to the requirement of NFX1-123 for immune regulation in the context of 16E6. Studies using immunofluorescent microscopy revealed that 16E6 and NFX1-123 disturbed the normal localization of signaling proteins involved in initiating the immune response. This study identifies NFX1-123 as a critical host protein partner through which 16E6 is able to subvert the immune response and in turn permit a long-lived HR HPV infection. There are over 200 types of human papillomaviruses (HPV), which infect keratinocytes of the stratified squamous epithelium . Those tIn addition to their structural role, keratinocytes are involved in immune system functioning. During the early stages of an HPV infection, the host innate immune response is the first line of defense against the infection. Multiple cells are involved in promoting an immune response against HPV infection, including dendritic cells, Langerhans cells, natural killer T cells, and keratinocytes. Keratinocytes provide robust immune defenses, expressing pathogen recognition receptors (PRRs) that activate signaling cascades and lead to production of soluble immune effector proteins such as cytokines and interferon-stimulated genes . DespiteImmune evasion mechanisms mediated by E6 and E7 generally act to prevent production of pro-inflammatory cytokines, interferons, and other antiviral genes or to disrupt antigen presentation . E6 has Our laboratory has previously studied the partnership between the E6 protein of HR HPV type 16 (16E6) and the host cytoplasmic protein NFX1-123 –34. NFX1We were interested in exploring what other pathways are manipulated by 16E6 and NFX1-123 to alter the host cell and engender an environment supportive of persistent HR HPV infection. In this study, we establish that 16E6 and NFX1-123 deregulated the innate immune response of keratinocytes, impeding the normal expression of diverse immune genes including cytokines and interferon stimulated genes. The data presented here identified NFX1-123 as a critical host protein partner through which 16E6 was able to subvert the immune response, revealing another cellular process targeted by this protein partnership that could further promote a HR HPV infection.The plasmids for FLAG-tagged NFX1-123WT, pBabe-puro 16E6, LXSN vector control, scramble short hairpin control, and short hairpin 1 RNA to NFX1-123 (sh1) have been described previously .Primary cultures of human keratinocyte cells (HFKs) were established as previously described from neonatal foreskins . HFKs weThe microarray was performed and analyzed as previously described . BrieflyRetrovirus was produced in 293T cells by a previously described transient vesicular stomatitis virus G-pseudotyped virus (VSV-G) production protocol  or by a Whole-cell protein extracts were resolved by SDS-polyacrylamide gel electrophoresis and transferred to polyvinylidene difluoride . Blots were probed with anti-NFX1-123 (1:1000), anti-p53 , , anti-TRIF , anti-TAK1 , anti-TAB1 , anti-TAB2 , and anti-GAPDH  primary antibodies. The secondary antibodies used were anti-mouse IgG HRP  or anti-rabbit IgG HRP . The rabbit polyclonal anti-NFX1-123 antibody was generously provided by Dr. Ann Roman. Animals were immunized with peptide composed of amino acids 1102–1120 of NFX1-123. All films were scanned using Epson Perfection V700 and imported using Adobe Photoshop.Total RNA was isolated with TRIzol reagent . Total RNA (1 mcg) was DNase treated and used to generate cDNA with random hexamer primers and SuperScript IV reverse transcriptase  as described previously ,35,36. QPrimer sequences for NFX1-123, and 36B4 were described previously ,41 AmpliImmunofluorescence was performed on cells grown on cover slips (#1 1/2 x 18mm). Cells were fixed with 4% paraformaldehyde for fifteen minutes at room temperature, washed with PBS and permeabilized with ice cold methanol/acetone (1:1) for 30 seconds. After blocking with PBS containing 1% TWEEN-20 and 3% BSA for one hour at room temperature, cover slips were incubated overnight at four degrees Celsius in blocking buffer with the same primary antibodies used in Western blot analysis above , unless otherwise stated: anti-TRAF6 (1:500), anti-TRIF (1:500), anti-TAK1 (1:500), anti-TAB1 (1:500), and anti-TAB2 (1:500). All secondary antibodies were obtained from Life Technologies  and were as follows: anti-rabbit AlexaFluor 488 (1:500), anti-mouse AlexaFluor 546 (1:500), and anti-goat AlexaFluor 633 (1:500). Secondary antibodies were incubated in the dark for one hour at room temperature with Hoechst stain . Cover slips were washed with cold PBS and mounted in glass slides with ProLong reagent . Confocal images (stacks) were acquired at 0.2 micron spacing with an Olympus 60x oil immersion objective as specified in the figure legends with an Applied Precision DeltaVision RT microscope system . The exposure times were kept constant for each fluorescence channel within each experiment and antibody used. Stacks were deconvolved using a constrained iterative algorithm with DeltaVision SoftWoRx program, version 4.1.2.Previously deconvolved and normalized images of HFK, 16E6/control, and 16E6/FN123 cells grown on coverslips, fixed and co-stained for either TAB1, TAB2 and TAK1 or TRIF, TRAF6 and TAK1 were quantified using the FIJI scientific imaging analysis platform . The fluPreviously deconvolved and normalized images of HFK, 16E6/control, and 16E6/FN123 cells cells grown on coverslips, fixed and co-stained for TAB1, TAB2 and TAK1 or TRIF, TRAF6 and TAK1 were split by channels into greyscale images. These were visually sorted according to whether the staining was above background, and whether the staining was in the cytoplasm or had coalesced into distinctive brighter staining perinuclear or nuclear foci. The Hoechst nuclear staining was used as a general mask. A minimum of 60 cells from each of three separate biological backgrounds were used for quantification.NFX1-123 is a cytoplasmic protein whose partnership with 16E6 has previously been shown to co-regulate expression of genes such as Notch1, epithelial cell differentiation markers, and hTERT –36. To eAn Illumina beadchip microarray was performed in the three independent biologic backgrounds for each 16E6/control and 16E6/FN123 (GEO Accession number GSE43082). There were over 200 genes identified whose average expression was decreased by at least two-fold in at least two out of the three independent 16E6/FN123 HFK lines compared to 16E6/control HFKs. There were 26 genes found to be downregulated in all three cell lines , box. ThA subset of the over 200 genes whose average expression was decreased in at least two of three HFK cell lines are listed in Following our microarray studies, we further validated the roles of 16E6 and NFX1-123 in co-regulating genes of the immune response at the mRNA and protein levels. We returned to the three 16E6 HFK cell lines in which the microarrays were completed  for validation. Fold changes in mRNA expression were quantified by qPCR for a set of genes that were decreased in the screening microarray of 16E6/FN123 cells . AlthougHaving found that a diverse set of innate immune genes were downregulated in 16E6 HFKs with overexpression of NFX1-123, we then hypothesized that knock down of the endogenous amount of NFX1-123 would result in a derepression of these genes. Two additional biologically independent HFK lines were transduced with 16E6 (16E6 HFK 4 and 5), then expanded and transduced with either a short hairpin RNA targeting NFX1-123 (sh1) or a scramble short hairpin control (scr). Again, expression and function of 16E6 were confirmed by p53 Western blot . NFX1-12In normal keratinocytes, the expression of genes such as IL-8, CXCL1, and other genes found to be downregulated in our screening microarray are induced through immune signaling pathways. Input, in the form of pathogen assault or stimulus, is communicated through these signaling pathways; output, in the form of proinflammatory cytokines, interferon-stimulated genes, and other factors, creates the innate immune response. A few common signaling pathways are responsible for induction of hundreds of these immune genes. The broad number of innate immune genes found modulated in the screening microarray and the lack of alignment with a singular category, such as proinflammatory cytokines, led us to hypothesize that the dysregulation of the immune response genes might be occurring at a level above, or prior to, the direct downregulation of the genes themselves. We therefore next queried whether co-regulation of the immune response by 16E6 and NFX1-123 occurred through disruption of the signaling pathways that govern expression of innate immune genes. A diagram of an immune signaling cascade and the key proteins involved is depicted in The mechanism by which 16E6 and NFX1-123 dysregulate protein signaling complexes could occur in a number of ways, including 1) a decrease in total signaling protein level, 2) sequestration of proteins, or 3) prevention of signaling complex formation. We addressed the first possibility by comparing total quantities of key signaling proteins in normal HFKs, 16E6 HFKs with endogenous levels of NFX1-123, and 16E6 HFKs with overexpressed NFX1-123. As before, HFKs were serially transduced with 16E6, and then either a FLAG-tagged NFX1-123 construct (FN123) or a vector control (control). Whole cell lysates were collected from each, and subsequent protein blots were probed for the immune signaling proteins TRIF, TRAF6, TAK1, TAB1, and TAB2. Experiments were conducted in three independent HFK cell lines with representative data of one cell line shown here . InteresOrdered formation of signaling complexes is essential for full functioning of the signaling pathways depicted in The subcellular localization of TRAF6 appeared to change dramatically with overexpression of NFX1-123 , top rowSimilar to TRAF6, subcellular localization of TAB2 also appeared to be altered with more NFX1-123  binding proteins to increase hTERT expression at the posttranscriptional level , the effFuture research will further examine how 16E6 and NFX1-123 deregulate the immune response during an active stimulation. Keratinocytes constitutively express some cytokines, but are also are primed to respond quickly, producing soluble effector proteins to both initiate an anti-pathogenic  state and recruit or activate other resident immune cells. This state is largely possible due to constant expression of signaling proteins that, upon stimulation, rapidly transduce a signal and induce gene expression. 16E6 and NFX1-123 appear to disturb the normal localization and likely function of the signaling proteins. We thus hypothesize that there are functional consequences upon the ability to mount an immune response both at the keratinocyte level and the larger epidermal level. Keratinocytes are the first-line responders to any infection and act as a link to the rest of the immune effector cells in the region . 16E6 anIn conclusion, the studies presented here identify NFX1-12 as a host protein that is co-opted by 16E6 to deregulate the innate immune response of keratinocytes and inhibit the expression of immune genes. This is achieved by perturbing the normal localization of signaling proteins, resulting in a broad inhibition. These data support previous work that elucidates how 16E6 and NFX1-123 contribute to a cellular environment that supports long-lived HPV infection. Persistent infection with HR HPV is the highest risk factor for cancer development; uncovering the mechanisms of immune evasion by HR HPV could advance understanding of how to prevent persistent infection and ultimately cancer.S1 FigProtein levels of (A) p53, (B and C) NFX1-123, or (A and D) GAPDH were assessed in three biologically independent HFK backgrounds. Per biological background, samples were HFKs, HFKs transduced with 16E6 and vector control, or HFKs transduced with 16E6 and NFX1-123 overexpression construct.(TIF)Click here for additional data file.S2 FigProtein levels of (A) IRF7 and(B) GAPDH were assessed in 16E6 HFK 1. Boxed lanes in (A) indicate HFK1 samples. HFKs were serially transduced with 16E6 and either scrambled short hairpin control or short hairpin RNA construct targeting NFX1-123. Protein levels of (C) p53, (D and G) NFX1-123, and (E and F) GAPDH were assessed in 16E6 HFK 4 and 16E6 HFK 5. HFKs were transduced with 16E6 and either scrambled short hairpin control or short hairpin RNA construct targeting NFX1-123. Protein levels of (H) IRF7 or (I) GAPDH were assessed in 16E6 HFK 1. HFKs were serially transduced with 16E6 and either vector control or NFX1-123 overexpression construct.(TIF)Click here for additional data file.S3 FigProtein levels of (A) TRAF6, (B) TRIF, (C) TAB1 and TAB2, (D) TAK1,(E) Actin, and (F) NFX1-123 were assessed in HFK cells. Samples were HFKs, HFKs transduced with 16E6 and vector control, or HFKs transduced with 16E6 and NFX1-123 overexpression construct.(TIF)Click here for additional data file.