Exaggerated stretch-sensitive reflexes are a common finding in elbow flexors of the contralesional arm in chronic hemiparetic stroke, particularly when muscles are not voluntarily activated prior to stretch. Previous investigations have suggested that this exaggeration could arise either from an abnormal tonic ionotropic drive to motoneuron pools innervating the paretic limbs, which could bring additional motor units near firing threshold, or from an increased influence of descending monoaminergic neuromodulatory pathways, which could depolarize motoneurons and amplify their responses to synaptic inputs. However, previous investigations have been unable to differentiate between these explanations, leaving the source(s) of this excitability increase unclear. Here, we used tonic vibration reflexes (TVRs) during voluntary muscle contractions of increasing magnitude to infer the sources of spinal motor excitability in individuals with chronic hemiparetic stroke. We show that when the paretic and non-paretic elbow flexors are preactivated to the same percentage of maximum prior to vibration, TVRs remain significantly elevated in the paretic arm. We also show that the rate of vibration-induced torque development increases as a function of increasing preactivation in the paretic limb, even though the amplitude of vibration-induced torque remains conspicuously unchanged as preactivation increases. It is highly unlikely that these findings could be explained by a source that is either purely ionotropic or purely neuromodulatory, because matching preactivation should control for the effects of a potential ionotropic drive (and lead to comparable tonic vibration reflex responses between limbs), while a purely monoaminergic mechanism would increase reflex magnitude as a function of preactivation. Thus, our results suggest that increased excitability of motor pools innervating the paretic limb post-stroke is likely to arise from both ionotropic and neuromodulatory mechanisms. Focal ischemic stroke causes changes in descending neural drive that alter spinal motor excitability , and the resulting input-output function of the motoneurons. We interpret these results as evidence that both an ionotropic and monoaminergic neuromodulatory drive are likely to contribute to the apparent increased excitability of motor pools innervating paretic muscles post-stroke.Here, we characterize TVRs in elbow flexors of the paretic and non-paretic arms of individuals with chronic hemiparetic stroke at three levels of preactivation. In particular, we quantify TVR-evoked elbow flexion joint torque amplitude and rise time, metrics that can be used to infer the spinal neuromodulatory state . The absence of inflammatory conditions at the shoulder, elbow, wrist and fingers was verified by overpressure at the end-range of motion. Potential participants were excluded from the study if the demonstrated minimal (50–66 on the FMA) or very severe (0–9 on the FMA) impairment, significant impairment of upper extremity tactile sensation or proprioception  by shoulder and lap belt restraints. The forearm, wrist and hand of each participant's paretic and non-paretic arms were fitted with custom fiberglass casts. The casted arm was coupled at the level of the wrist to a 6 degree-of-freedom load cell , and the limb was positioned such that it retained 75° of shoulder abduction, 40° of shoulder flexion, and 90° of elbow flexion. The test apparatus supported the weight of the limb throughout these experimental protocols.While interfaced with the isometric testing setup described above, participants were first required to generate MVTs in elbow flexion and extension. Visual feedback of performance was provided in real time for all trials. To obtain a reliable estimate of the true maximum torque capability in each direction, collection of MVTs continued until 3 trials were obtained within 10% of one another, without the last trial being the greatest.For the TVR protocol, participants remained interfaced with the isometric setup used for testing MVTs, and a therapeutic massage vibrator  was placed over the distal muscle belly of the biceps brachii. TVR trial onset and offset were indicated to the participant and experimentalist by auditory cues. TVR trials began after the experimentalist determined that the participant was fully relaxed . Upon trial onset, participants were first instructed to generate and maintain either 5 or 15% of their elbow flexion MVT, guided by visual feedback. Once the requisite torque was achieved, visual feedback was extinguished, and vibration commenced. The vibratory stimulus lasted for 5 s. Following each trial, participants were given at least a 15–30 s rest period to allow the limb to relax before beginning the next trial. First-pass trial acceptability was examined on-line by visual feedback provided to the experimentalist, and trials were excluded from further analysis if postural or unconstrained extremity movements occurred during the trial or if participants closed their eyes and appeared to fall asleep. Approximately 20 TVR response trials were collected at each of the 5 and 15% elbow flexion levels, and the protocol was performed on both the paretic and non-paretic limbs.Analyses of TVR-evoked elbow flexion torque were used as outcome measures in this study, computed using custom Matlab software . A Jacobian-based algorithm converted forces and moments recorded by the loadcell into elbow flexion/extension torques. The resulting torque curves were filtered with an eighth-order low-pass Butterworth filter with cutoff frequency of 50 Hz. Window averages of individual TVR trials were taken from 3.5 to 5.0 s after trial onset, corresponding to the preactivation phase, and from 9.5 to 10.0 s post-trial onset, corresponding to the last 500 ms of the vibration phase. We did not extract data during the post-vibration period because reflexive torque and EMG responses could not be reliably decoupled from volitional efforts to decrease elbow flexion torque. Preactivation windows and during-vibration windows were then ensemble-averaged for each participant and limb (paretic and non-paretic) for use in subsequent group analyses.To quantify TVR-evoked torque amplitude, we computed the change in torque from preactivation to during-vibration for each participant's ensemble-averaged torque response. We computed this difference at each preactivation level , and these values were subsequently used in group statistical analyses. Because of the likely difference in elbow flexion strength between paretic and non-paretic limbs, we calculated the TVR-evoked torque amplitude using both unnormalized torque (Nm) and normalized torque (% MVT). This dual approach ensured that between-limb results would not be inflated by normalization of paretic torque to lower MVT values.We used two approaches to quantify the temporal profile of the rising phase of the TVR-evoked torque response. First, we computed the slope of a linear fit between each participant's preactivation torque and the time at which TVR-evoked torque reached 85% of the maximum stable response (Equation 1):Second, because TVR-evoked torque generally exhibits a non-linear temporal profile, we used non-linear least squares estimation to determine the optimal fit of each group mean ensemble-averaged torque response  to a function of the form:a generally represents the amplitude of the TVR-evoked torque , term b is the time constant describing the rate of rise of TVR-evoked torque, and t is elapsed time. The model was fit to experimental data from the time of vibration onset to the time of vibration offset; a and b are coefficients fit by the optimization routine and t is elapsed time. The parameters of this model are not intended to reflect specific biophysical features of motoneuron firing.In this equation, term post-hoc t-tests were used. First, t-tests were used to determine differences between limbs at each preactivation level, with Bonferroni correction for multiple comparisons. Second, t-tests within each limb were used to evaluate differences between all combinations of preactivation levels, using Tukey correction for multiple comparisons within each limb.For TVR-evoked torque amplitude, all statistical analyses were calculated on the normalized torque values. Unnormalized torque values are presented for comparison. A 2 × 3 repeated measures ANOVA was used to determine the main effects of limb  and preactivation level , as well as the limb-by-preactivation level interaction, on normalized TVR-evoked torque amplitude. To reiterate, all participants included in this investigation were included in our original study of TVR responses post-stroke  and data from one participant in the paretic limb (with N = 9 remaining). Together, these removals reduced the total number of torque values from 60 to 51. There were two missing cases at one preactivation level for the non-paretic limb (for one participant at 0% and for another participant at 15%). Values for these cases were imputed by taking the average of values from the seven other participants. For the paretic limb, there was one missing case at the 0% condition, and the value was imputed by taking the average of the eight other participants for this condition. As a result, the number of total values that were imputed was 3 out of 51, or 5.9%. This method allowed for an ANOVA with a repeated factor of preactivation; however, because the number of participants for each limb was not the same, the factor of limb could not be repeated. Therefore, a mixed-model 2 × 3 ANOVA was used to determine the main effects of limb  and preactivation level  as well as the limb-by-preactivation level interaction on TVR-evoked slope magnitude. Between-limb post-hoc t-tests were used to determine differences in slope between paretic and non-paretic limbs at each preactivation level, with Bonferroni correction for multiple comparisons. Within-limb post-hoc t-tests were used to evaluate differences between all combinations of preactivation levels, using Tukey correction for multiple comparisons within each limb. Finally, a 2-way non-repeated measures ANOVA was also calculated without accounting for the missing data to ensure that the above analyses were not biased by methods used for accounting for missing data. Results from this ANOVA were virtually identical to those from the 2-way repeated measures ANOVA that is presented in the Results section below, with the same significant ANOVA effects and post-hoc test results.For the slope of TVR-evoked torque, there were 60 total values (2 limbs × 3 preactivation levels × 10 participants). Several outliers were detected in both paretic and non-paretic values, which were excluded from further analysis. Outliers were defined as values exceeding 3 scaled median absolute deviations from the median. Given that a 2-way repeated measures ANOVA  requires no missing cases, the following method was used to account for the missing data and allow for a repeated measures ANOVA. First, if a participant had missing data for more than one preactivation level, all data for that participant was removed. This resulted in removing data from two participants for the non-paretic limb  and sum-of-squared error (SSE) of the model. The effect of preactivation on the model parameters associated with the TVR-evoked portion of the torque profile was examined qualitatively for each limb.p < 0.05 level, and p-values for the t-tests are presented in the results after application of corrections for multiple comparisons. All statistical analyses were performed in Prism .Results of all analyses were considered significant at the As a first step toward providing additional mechanistic context for our human-subjects findings, we conducted a set of proof-of-principle TVR experiments in a decerebrate cat model. The primary goal of this model was to determine the impact of increasing preactivation level on the amplitude and rate of rise of TVR-evoked force. We chose the decerebrate cat preparation because it has a well-documented elevation of descending monoaminergic drive that does not scale with motor output  and gasses were delivered through the tube for the duration of the surgery. The animal was then transferred to a stereotaxic frame and immobilized by a head clamp, spinal clamp on the L2 dorsal vertebral process, and bilateral hip pins at the iliac crest. The left hindlimb was fixed with pins at the knee and clamps at the ankle, and the right hindlimb was secured using a clamp on the lower leg. The left soleus was dissected, isolated, and its distal tendon was attached to a load cell via a calcaneus bone chip in series with a linear variable differential transformer and customized voice coil. A distal, cutaneous branch of the right superficial peroneal nerve was dissected and a cuff electrode was secured around the nerve. The animal was then decerebrated at the precollicular level and anesthesia was discontinued , amplified (0.5–2 k) and digitized  by a 12-bit A/D converter . Force data from the soleus muscle were simultaneously acquired.With the animal's hindlimbs fixed, the soleus was activated by stimulating the contralateral superficial peroneal nerve through a cuff electrode . This elicits the crossed-extension reflex and a maintained contraction. The magnitude of contraction is generally proportional to the applied voltage, and here, we used voltages ranging from 3.5 to 5 V. This evoked sub-maximal contractions up to ~25% of maximum force output, as confirmed by the appearance of force saturation with voltages at or above 6 V in this animal. After at least 2 s of stimulation (to acquire a stable baseline preactivation), 3–5 s of vibration of the soleus tendon commenced . This elicited a TVR. Electrical stimulation of the contralateral peroneal nerve continued for the duration of vibration, and we varied the applied voltage between trials to explore the impact of vibration at a range of preactivation levels.Force data from the soleus was analyzed similarly to the elbow flexion torque data from the human subjects experiments. Preactivation force was calculated as the average of force values generated during the 0.5 s prior to vibration onset. TVR-evoked force amplitude was calculated as the change in force from the preactivation value to the average torque between 1 and 2 s post-vibration onset. The rising slope of the TVR-evoked force was calculated as with Eqn. 1 for the human data. The time to 85% max TVR-evoked force was calculated relative to vibration onset. Separate Pearson correlation calculations were used to determine if increasing preactivation level was associated with changes in TVR-evoked force amplitude, rising slope of the TVR-evoked force, or the time to 85% max TVR-evoked force.To examine motor unit recruitment and rate modulation patterns underlying the TVR-evoked force due to different levels of preactivation, multi-channel EMG data from each trial were decomposed into individual motor unit spike trains using a blind source separation approach  and preactivation level (p = 0.0004) on normalized TVR-evoked torque amplitude, and a non-significant limb-by-preactivation level interaction (p = 0.16). Examining the significant main effect of limb, paretic limb values were greater than non-paretic values, averaging 6.32% MVT across pre-activation levels vs. 2.00% MVT. The uniform increase in paretic vs. non-paretic TVR-evoked torque amplitude at all preactivation levels  was contrary to our prediction that the torque response would become similar across limbs with preactivation vs. the relaxed condition.The 2 × 3 repeated measures ANOVA revealed significant main effects of limb . Notably, however, there was no difference in TVR-evoked torque amplitude in the paretic limb between trials with torque preactivation of 5 and 15% MVT (p = 0.84). The same analysis in the non-paretic limb revealed a significant difference between the 0 and 5% conditions only (p = 0.007); comparisons of 0 vs. 15% (p = 0.32) and 5 vs. 15% (p = 0.30) were not statistically significant. Results from between-limb post-hoc t-tests are summarized in Table Results from within-limb 5% p = 0.2 and 5 vp = 0.002) and preactivation level (p < 0.0001) as well as a significant limb-by-preactivation level interaction (p = 0.0002). A 2-way non-repeated measures ANOVA, without imputation, likewise revealed significant main effects of limb (p = 0.0003) and preactivation level (p = 0.0002) and a significant limb-by-preactivation level interaction (p = 0.0008). The nature of the significant interaction can be appreciated from visual inspection of Figure Qualitatively, the rate of rise of TVR-evoked torque in the paretic limb appears to increase with increasing preactivation. Further, the rate of rise in the paretic limb appears to be more rapid than that of the non-paretic limb at matched levels of preactivation Figure . We evalPost-hoc t-tests comparing between-limb differences in the slope of TVR-evoked torque at each pre-activation level revealed a significant difference at the 15% condition (p < 0.0001) and not the 0 or 5% conditions  (Table Post-hoc t-tests comparing within-limb differences in the slope of TVR-evoked torque between each combination of the three preactivation levels (Table p < 0.0001 for both comparisons), but there was no significant difference between values for the 0 and 5% conditions (p = 0.31). The same analysis in the non-paretic limb revealed no significant differences in the slope of TVR-evoked torque among any preactivation level comparisons .Because the temporal profile of TVR-evoked torque is non-linear, particularly during the first ~1 s of vibration, we also modeled TVR-evoked torque as an exponential function according to Equation (2). All data were well-fit by this model, as can be appreciated visually in Figure a and b from the model  for the paretic (pink) and non-paretic (blue) limbs as a function of preactivation level. These two parameters describe the shape of the during-vibration profile. Parameter a, most closely associated with the amplitude of TVR-evoked torque, tends to increase as a function of preactivation level for the paretic limb but not the non-paretic limb. Parameter b, reflective of the rate-of-rise of the TVR-evoked torque, is lower overall in the paretic limb—indicating more rapid torque development during vibration—and qualitatively appears to decrease as preactivation level increases.In Figure from the 5% preactivation data to the 15% preactivation data (separately for the non-paretic and paretic limbs). This manipulation gives an estimate of similarity between TVR-evoked responses at increasing preactivation levels, particularly during the rising phase of the contraction. We found that the optimal parameters for describing the 5% preactivation response in the non-paretic limb also accounted for 98.25% of the variability in the 15% preactivation trials in the same limb  instead of some type of compensation by descending inputs.not associated with a larger TVR-evoked force amplitude, with virtually no correlation between the two variables . In comparison, there was a higher correlation between preactivation force and the rising slope of the TVR-evoked force (r = 0.48) and time to 85% max TVR-evoked force (r = −0.62); however, neither of these correlations reached significance at the p < 0.05 level with the amount of data available (p = 0.19 and p = 0.08).We found that the pattern of TVR-evoked force in the decerebrate cat was strikingly similar to that of the paretic elbow flexors in individuals with chronic hemiparetic stroke Figure . SpecifiTo further investigate how the TVR-evoked torque arose, we utilized motor unit spike trains to characterize motor unit recruitment and rate modulation. Motor unit spike trains for two TVR trials with different preactivation levels are represented in Figure t = ~3.5–4.5 s). This persistent elevated force was accompanied by sustained firing of the vibration-recruited motor units despite removal of the vibration stimulus. Interestingly, we also observed differences between the two trials in the proportion of vibration-recruited motor units that demonstrated sustained firing. For the trial with lower preactivation, 32 of the 33 vibration-recruited motor units demonstrated sustained firing. For the trial with higher preactivation, however, only 12 of the 24 vibration-recruited motor units demonstrated sustained firing through the end of the trial.The decerebrate cat preparation also allowed us to examine potential post-vibration force production (given the lack of descending voluntary drive as a confounding factor), and, by extension, the ability of a purely spinal mechanism to account for any such effects. When vibration was discontinued, force persisted at an elevated level until peroneal nerve stimulation was discontinued , because a lack of monoamines below the lesion appears to drive adaptive processes that result in constitutive activity of monoaminergic receptors on motoneurons (Murray et al., One potential explanation for the increased amplitude of TVR-evoked torque in the paretic compared to the non-paretic arm Figure  could beAlternatively, it is possible that a tonic excitatory ionotropic drive to paretic motor pools could have contributed to the increased TVR amplitude we observed in the paretic arm. Such a drive could arise from ionotropic reticulospinal or vestibulospinal pathways following stroke-induced damage to primary motor resources (Mottram et al., does abolish the resting excitability imbalance between limbs, then our results cannot be explained solely by a tonic ionotropic drive to motor pools innervating the paretic muscles. If that were the case, then TVR responses in paretic and non-paretic limbs would equilibrate with preactivation.Our findings contrast with some aspects of the ionotropic drive hypothesis, particularly as they relate to other studies that cite this mechanism as possible explanation for exaggerated stretch-sensitive reflexes post-stroke. For example, when stretch reflexes are evoked by imposed joint excursions in the paretic and non-paretic arms at matched levels of preactivation, the difference in reflex response between arms is often extinguished (Lee et al., Changes in spinal circuits post-stroke could have also contributed to the increased TVR amplitude we observed in the paretic arm, although our experimental paradigm and analyses were not able to directly measure or clearly infer the potential contribution of such changes to our results. Nevertheless, there is evidence that the net effect of Group Ib afferent feedback transitions to from a combination of inhibition and excitation (Houk et al., It is unclear why the magnitude of TVR-evoked torque did not increase in either limb when preactivation increased from 5 to 15% MVT. Indeed, it is well accepted that the amplitude of stretch reflexes elicited by imposed joint excursions increases with increasing preactivation in paretic, non-paretic, and control limbs. Further, Henneman's size principle (Binder et al., Two potential mechanisms could contribute to this unexpected finding. In the first, synaptic inhibition could simultaneously increase and decrease in direct proportion to preactivation level, a phenomenon known as “proportional,” or “balanced,” inhibition (Powers et al., To further explore our finding that paretic limb TVR-evoked torque amplitude was not different between 5 and 15% preactivation levels post-stroke, we investigated the impact of increasing preactivation level on the amplitude and rate of rise of TVR-evoked force in a decerebrate cat model. This model has a strong descending monoaminergic drive, the magnitude of which is not modified by vibration or crossed-extension reflex inputs (Lee and Heckman, after vibration was discontinued, which was not possible in our human-subjects experiments. We found maintained, elevated force post-vibration rather than a return to preactivation level or the relaxed state. This behavior is characteristic of PICs in motoneurons (Heckman et al., Importantly, the decerebrate cat model also enabled us to investigate force production Together, these findings corroborate and extend key aspects of our overall unexpected human-subjects findings, and reinforce the notion that monoaminergic mechanisms are a potential component of the observed paretic arm TVR responses. However, it should be noted that in the decerebrate cat there is no natural analog to the non-paretic arm in humans, and it is unknown how the afferent drive provided by peripheral nerve stimulation in the cat compares to volitional preactivation in humans with regard to its inhibitory and excitatory content.We found that the slope of TVR-evoked torque amplitude and the gain of the modeled torque both increased with increasing preactivation in the paretic limb. These findings are consistent with an increased influence of monoamines in paretic motor pools, which could result in a combination of larger PICs in recruited motoneurons, more motoneurons recruited, and/or a reduced time to PIC activation as preactivation increases.PIC activation time is proportional to the difference in membrane potential and PIC threshold potential (Heckman and Lee, Finally, an intriguing question raised by these results is why TVR responses continue to be elevated in the paretic limb compared to the non-paretic limb at matched levels of preactivation, yet stretch reflex responses equilibrate under analogous conditions. It is conceivable that this distinction is related to the potency of vibration as an input to motor pools compared to imposed joint excursions. Indeed, it has been suggested that vibration elicits more robust activation of Ia afferents than group Ib or II fibers, which may be activated more strongly by joint excursion (Matthews, This explanation seems unlikely, however, both because spindle-mediated feedback appears to be unchanged post-stroke (Hagbarth et al., Our study has important limitations. First, we reiterate that because our human-subjects experiments used indirect probes of spinal neural excitability, our interpretation of the underlying mechanisms remains inferential. Additionally, we did not conduct TVR analyses in individuals without neurological injury. Although this choice was motivated by an attempt to limit variability, the ipsilesional arm is not truly unaffected post-stroke, and thus, future studies are warranted. We also did not acquire elbow flexion/extension torque after cessation of vibration in the human-subjects portion of the study. While this choice was made to avoid the confound of volitional activity in any persistent muscle activation post-TVR, it prevents our study from assessing the impact of preactivation on persistent motoneuron firing—an important component of PICs. And finally, regarding the decerebrate cat experiments: because the primary purpose of this preliminary cat model was to provide context for the mechanical response to vibration in a situation with known elevation of monoaminergic drive, we did not design the protocol with the specific goal of acquiring EMG data amenable to studying PICs. As a result, we are not able to make inferences about PICs from these data.Our results suggest that a combination of both ionotropic and neuromodulatory mechanisms likely underlie the exaggerated TVR responses we observed in the paretic elbow flexors post-stroke, although the relative impact of each remains unclear. The finding that TVR-evoked torque amplitude did not change with preactivation level could imply a more pronounced role for synaptic inhibition in motor pools innervating the paretic muscles than previously thought. For example, an increase in inhibitory drive as volitional motor output increases (Powers and Heckman, All authors contributed to the conception and design of the work; JM, LM, CT, ME contributed to the acquisition of data; JM, LM, CT contributed to analysis of data; all authors contributed to the interpretation of data and drafting, revising and approving the manuscript for publication. All authors are in agreement to be accountable for all aspects of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


MuLnc1 was found to be cleaved by mul-miR3954 and produce secondary siRNAs in a 21 nt phase in mulberry. It was demonstrated that one of the siRNAs produced, si161579, can silence the expression of the calmodulin-like protein gene CML27 of mulberry (MuCML27). When MuCML27 was heterologously expressed in Arabidopsis, the transgenic plants exhibited enhanced resistance to Botrytis cinerea and Pseudomonas syringae pv tomato DC3000. In addition, the transgenic MuCML27-overexpressing Arabidopsis plants are more tolerant to salt and drought stresses. Furthermore, the network of mul-miR3954-MuLnc1-siRNAs-mRNAs was modeled to elucidate the interaction between lncRNAs and sRNAs with mRNAs. All of these, taken together, suggest that MuLnc1 was associated with environmental stress in mulberry and may be considered as a potential genetic improvement target gene of mulberry. The information provided may shed light on the complicated gene expression regulatory mechanisms in mulberry stress responses.Environmental stresses are major constraints that limit the leaf productivity and quality of mulberry. LncRNAs have emerged as important regulators in response to biotic and abiotic stresses in plants. However, the functions and mechanisms of most lncRNAs remain largely unknown. A novel lncRNA designated as  Morus spp), an important food plant of the silkworms (Bombyx mori), is widely cultivated throughout the world in subtropical and temperate regions and is subjected to various environmental stresses during its entire life cycle  transcript of mulberry. Furthermore, we modeled a network of interactions between miRNAs, lncRNAs, siRNAs and protein-coding mRNAs. It may provide a basis to further study of the complicated gene expression regulatory mechanisms in mulberry stress responses and to explore the genes and ncRNAs which have a great potential application value in mulberry biotechnology in future.In this study, based on the ncRNAs and transcriptome information attained, we report a novel lncRNA, M. multicaulis) were grown in a growth chamber at 26°C with 12 h of light and 90% humidity. Arabidopsis thaliana (Col-0) plants were incubated under standard greenhouse conditions .One-year-old mulberry cutting seedlings of Husang 32 . The cDNA library was constructed and sequenced according the method described by 1. The predicted miRNA targets were validated using the degradome sequencing data of the leaves of Husang 32 with the software package, CleaveLand 3.0, as previously described (2), CNCl and Pfam were used to predict transcripts with coding potential, and the transcripts with CPC score<-1 and CNCl score <0 were discarded. The remaining transcripts with length >200 nt and open reading frames (ORFs) <80 bp were considered as lncRNAs. The secondary siRNAs were identified based on the sequences from small RNA library sequencing data of the leaves of Husang 32 according to the method described before  was used to extract total RNAs of the leaf samples, and the RNAs extracted were digested with DNase I before being used. qRT-PCR was performed on the Rotor-Gene 3000A instrument  with the SYBR Premix Ex TaqTM kit  for mRNA and the PrimeScriptTM miRNA qPCR Starter Kit Ver.2.0  for miRNAs according to the manufacturer’s protocol. The actin and U6 genes were chosen as reference genes for normalization of mRNA and miRNA, respectively. The comparative cycle threshold (Ct) method (Supplementary Table S1.The TRIzol) method  was usedTM RNA Isolation Kit . Specific digoxigenin-labeled RNA probes complementary to the mul-miR3954 and each siRNA were synthesized by Roche Ltd . Prehybridization, hybridization, washing, and detection were performed as previously described method  formaldehyde denatured agarose gel and then were transferred onto nylon Hybond N membrane. The blots were hybridized with the probes labeled by digoxigenin (DIG) using the PCR DIG Probe Synthesis Kit . Prehybridization, hybridization with probe, washing, and detection steps were performed according to the protocol described by d method . The proThe prepared proteins were mixed with 5 × SDS–PAGE sample buffer and heated for 3 min at 95°C and then were subjected to SDS/PAGE on 12% (w/v) polyacrylamide gels. After electrophoresis, proteins were transferred electrophoretically onto nitrocellulose membranes for protein gel blot analysis. Polyclonal anti-MuCML27 antibodies were generated by immunizing rabbits with purified MuCML27 protein, and the protein was detected by western blots using horseradish peroxidase (HRP)-conjugated polyclonal anti-MuCML27. Western blot analysis was conducted according to the procedure described by Supplementary Table S3.To study the function of si161579, the vector OE-si161579 over-expressing si161579 was constructed as described by MuCML27 and MuLnc1 genes, respectively. Primers (Supplementary Table S3) used to amplify the genes were designed based on the gene sequences (Supplementary Table S4). The genes cloned were then ligated individually into the binary vector pBI121 under the control of the CaMV 35S promoter. Then the vector was introduced into Agrobacterium tumefaciens strain GV3101 and transformed into WT Arabidopsis plants by floral dipping. Transformants were selected and confirmed by qRT-PCR and northern blot. The T3 generations from independent ectopic expression transgenic lines were randomly chosen for further functional studies.The mature mul-miR3954-producing DNA region was cloned from mulberry DNA, and the RNA isolated from leaves of mulberry was used to synthesize cDNA which was used as template to clone the Pst DC3000 was conducted by spraying the bacterial suspensions (105 CFU mL-1) of Pseudomonas syringae pv tomato DC3000 (Pst DC3000) onto the rosette leaves. Bacterial growth within the leaf was monitored by a serial-dilution assay  and then the mixture was boiled for 25 min at 100°C, followed by centrifugation for 5 min at 7,500 × g. The supernatant was used for MDA concentration measurement according to the procedure as described previously , and this was further experimentally verified by mRNA degradome sequencing . To explore whether MuLnc1 functioned as a target transcript of mul-miR3954, the correlation between the expression levels of MuLnc1 and mul-miR3954 in mulberry tissues were examined by qRT-PCR. The results showed that MuLnc1 was expressed at relatively high level in the ripe fruits, but its transcript level was very low in the roots, phloem and leaves , whereas the expression level of mul-miR3954 was very low in the ripe fruits, but its transcript level was relatively high in the roots, phloem and leaves. This suggested that MuLnc1 and mul-miR3954 expressions were highly tissue-specific, and there was a very good negative correlation between their expression levels , and this is in accord with the function of miRNA in guiding target mRNA cleavage.Based on the transcriptome information attained, one lncRNA, MuLnc1 transcript downstream of mul-miR3954 binding site , and northern blot results confirmed the existence of these siRNAs . Thus, MuLnc1 transcript might be cleaved by mul-miR3954 and generate the secondary siRNAs. Since the efficient genetic transformation system has not been established in mulberry trees, and the MuLnc1 and mul-miR3954 do not exist in Arabidopsis, to further explore whether the MuLnc1 is targeted by mul-miR3954, the MuLnc1 and MUL-MIR3954 genes were cloned and introduced into Arabidopsis plants, respectively. Genome PCR analysis results showed that both the MuLnc1 and MUL-MIR3954 genes were integrated into the Arabidopsis genome , and qRT-PCR and northern blot analysis results indicated that the MuLnc1 transcript and mature mul-miR3954 were successfully expressed in the transgenic Arabidopsis . The hybrids between MuLnc1 and MUL-MIR3954 transgenic Arabidopsis were produced and used to analyze the cleavage of MuLnc1 transcript by mul-miR3954. qRT-PCR and northern blot assays showed that there was no difference in the expression levels of mul-miR3954 between the hybrid and MUL-MIR3954 transgenic plants . However, the expression levels of MuLnc1 were significantly lower in the hybrid plants than those in the MuLnc1 transgenic plants . This suggested that mul-miR3954 can target and cleave MuLnc1 transcript in the hybrid plants. Moreover, four siRNAs, si47311, si161579 and si24218, generated from MuLnc1 transcript were detected in the hybrid plants, but not detected in the MuLnc1 and MUL-MIR3954 transgenic plants . Therefore, mul-miR3954 can cleave MuLnc1 transcript and trigger the production of secondary siRNAs from MuLnc1 transcript in vivo. Moreover, we found that these siRNAs generated from the downstream of the mul-miR3954 binding sites were in a 21-nt “phased” pattern which is a characteristic feature of ta-siRNA. Thus, these siRNAs were potential ta-siRNAs.Interestingly, some siRNAs in our small RNA library sequencing data were found to match to the MuLnc1 transcript can target the mulberry calmodulin-like protein 27 gene (MuCML27) . To examine whether the si161579 is functional in vivo, the expression level of MuCML27 in different tissues of mulberry was determined. The results showed that the expression level of MuCML27 was relatively high in the ripe fruits, but it was low in the roots, phloem and leaves . This suggested that there was a negative correlation between MuCML27 and siRNA-triggering mul-miR3954, and the si161579 generated from MuLnc1 transcript is functional and able to down regulate its target. To further verify the cleavage of MuCML27 by si161579, the artificial vector OE-si161579 over-expressing si161579 was constructed first and then was transformed into Arabidopsis thaliana. Analyses of qRT-PCR and northern blot showed that the si161579 can be expressed in the transgenic Arabidopsis thaliana plants (OEs) successfully . Moreover, the MuCML27 gene was also cloned and transformed into Arabidopsis thaliana. qRT-PCR, northern blot and western blot analyses showed that the transgenic plants (OEc) expressed the MuCML27 gene successfully . Then the OEsiR-ARF vector constructed was transformed into the OEc plants, and the transgenic lines (OEsc) obtained were used to explore the si161579–mediated MuCML27 gene silencing. qRT-PCR and northern blot analyses showed that the si161579 was successfully expressed in the OEsc transgenic Arabidopsis plants . Interestingly, the mRNA and protein abundances of MuCML27 in the OEsc plants were significant lower than those in the OEc plants . These results indicated that the si161579 can silence and down-regulated the expression of MuCML27 gene in the OEsc plants, and the silencing may occur at the level of transcription.Analysis of the mRNA degradome data indicated that the siRNA, si161579, generated from MuCML27 gene is involved in plant responses to pathogens, the OEc and OEsc plants were inoculated with B. cinerea and Pst DC3000, respectively. Rosette leaves were detached from 4-week-old Arabidopsis plants and inoculated with B. Cinerea, and development of disease symptoms was analyzed 4 days after inoculation (DAI). The results showed that expanding disease yellow lesions were yielded in the leaves of wild type and OEsc plants, and the symptoms in the leaves of wild type plants were the same as those in the OEsc plants. However, the disease spot size in the inoculated leaves of OEc plants was smaller than that in the inoculated leaves of wild type and OEsc plant . When the plants were inoculated with Pst DC3000, there were severe disease symptoms showing gray-brown lesion with chlorosis in the wild type and OEsc Arabidopsis plants. However, the disease symptoms were not evident in the leaves of OEc Arabidopsis plants , although mild chlorosis or necrosis was occasionally observed. To determine whether the depressive symptom development reflected the restricted growth of Pst DC3000 inside the leaves, the bacterial growth in the inoculated leaves was monitored. Arabidopsis leaf samples were taken at 36 h after inoculation, and the strain Pst DC3000 reaches the concentrations of 105 colony-forming units (CFU) cm-2 of leaf in the inoculated leaves of wild type Arabidopsis. Growth of the strain in the inoculated leaves of OEsc plants was essentially the same as that in the inoculated leaves of wild type Arabidopsis. Whereas growth of Pst DC3000 strains was extremely inhibited in the inoculated leaves of OEc plants . Therefore, these results indicated that overexpressing MuCML27 can also enhance plant resistance both to Pst DC3000 and B. cinerea, and si161579 indeed silences the MuCML27 gene and inhibits the functions of MuCML27 in plant response to biotic stress.Recent evidences suggest that several members of calmodulin-like protein (CMLs) play important roles in both abiotic and biotic responses including plant-microbe interactions . To findMuCML27 mediated by si161579 is associated with plant tolerance to abiotic stress, we compared the drought and salt tolerance of the OEc, OEsc and wild-type Arabidopsis. When the plants were exposed to drought stress, the leaves of wild-type and OEsc plants became severe rolling and wilting at 12 days after withholding water. However, the leaves of OEc plants showed less rolling and wilting symptoms as compared with the wild-type and OEsc ones during the drought stress process . When the plants were exposed to salt stress, the leaves of wild-type and OEsc plants became wilted and curled after treatment with 250 mM NaCl for 2 weeks and the plants had a severe retardation in their growth. Whereas the growth inhibition level in the OEc plants was relatively less . In addition, the proline and malondialdehyde (MDA) contents in the leaves of wild type and OEc, OEsc plants under salt and drought stresses were also measured. The results showed that under salt and drought treatments, the proline level was higher but the MDA content was significantly lower in the OEc plants compared to that in the OEsc and wild type plants . These demonstrated that MuCML27 transgenic plants exhibit increased both drought and salt tolerance, and silencing of MuCML27 guided by si161579 inhibited the functions of MuCML27 in plant response to drought and salt stresses.To explore whether silencing of MuLnc1, was identified in mulberry. Blast searches of MuLnc1 against the Long Non-coding RNA Database v2.0 yielded none homolog, indicating it was lack of evolutionary conservation.Although recent studies have discovered thousands of lncRNAs, only a small number of lncRNAs have been sufficiently described, and the functions and molecular mechanisms of most lncRNAs still remain elusive . In thisMuLnc1 was predicted to be one of the targets of mul-miR3954, and the negative correlation expression pattern between MuLnc1 and mul-miR3954 and the degradome sequencing results supported the predicted results. It was reported that miR3954 was also involved in cotton responses to salt and drought stresses and was associated with drought response in tomato  to protect the miRNA targets . In thisn tomato . Therefocis- and trans-regulators of gene activity in many different ways , suggesting that MuLnc1 may function as siRNA precursors. It was reported that 22-nucleotide miRNAs are sufficient to trigger secondary siRNA biogenesis in plants . So mul-miR3954 may trigger the production of secondary siRNAs which were in a 21-nt “phased” pattern and were potential ta-siRNAs . Therefore, these potential ta-siRNAs may regulate the expression of MuLnc1 transcript in cis; moreover, they may function in trans to target other genes. Our data showed that one of the siRNAs, si161579, can target and silence the expression of the MuCML27 gene belonging to the CML family whose members are important Ca2+ sensors and play significant roles in mediating plant stress tolerance (MuCML27 transgenic plants exhibited increased resistance to biotic and abiotic stresses. Besides the si161579, the siRNAs originated from the MuLnc1 were predicted to target many other protein-coding genes with diverse functions. Therefore, as the precursor of these siRNAs, the MuLnc1 gene may be involved in different physiological processes, and there was a complex regulatory network of mul-miR3954-MuLnc1-si161579-MuCML27 involved in the response to environmental stress in mulberry. Based on the information obtained, the complex regulatory network of mul-miR3954-MuLnc1-siRNAs-MuCML27 involved in mulberry response to environmental stress is outlined in Figure 11.Previous studies showed that lncRNAs may function as ent ways , and soment ways . Analysin plants . Furthersitivity . There wolerance . Our resMuLnc1. So more research is needed to understand the functions of MuLnc1, and MuLnc1 can be used as a target for genetic improvement of mulberry in the future.In addition, it was reported that lncRNAs are widely involved in regulation of gene expression including transcription, mRNA splicing and translation, and can affect the stability of RNA-protein complexes and regulate the activities of proteins . Since tMuLnc1, was found to be cleaved by mul-miR3954 and produce secondary siRNAs in a 21-nt “phased” pattern in mulberry. One of the siRNAs produced, si161579, can silence the expression of the MuCML27 gene, and the transgenic Arabidopsis plants ectopically expressing MuCML27 gene showed more resistant to biotic and abiotic stresses. Therefore, there was a complex regulatory network of mul-miR3954-MuLnc1-si161579-MuCML27 involved in mulberry response to environmental stresses. All of these, taken together, suggest that MuLnc1 is associated with environmental stress in mulberry, and has potential applications in mulberry genetic improvement in the future.The novel lncRNA, SRP139984, SRP139984, and SRP140041, respectively.Raw data of transcriptome, sRNA datasets and degradome can be obtained from SRA database with the accession number Y-PG and X-LJ designed the research. S-SY generated and characterized Arabidopsis transgenics. Y-NZ performed quantitative RT-PCR. H-NZ and H-LZ designed and performed northern and western blot assays. X-LJ wrote the manuscript with input from all authors. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The objective of this study was to assess the potential clinical value of the concentration of soluble salivary E-cadherin (sE-cadherin) compared with the clinical value of the presence of membranous E-cadherin (mE-cadherin) in oral squamous cell carcinoma tumor tissues.Data regarding patient demographics, clinical stage, saliva and tumor tissue samples were collected. The saliva was analyzed for sE-cadherin protein levels and was compared to the mE-cadherin immunohistochemical expression levels in tumor tissues, which were assessed via the HercepTest® method. Patients without cancer were included in the study as a control group for comparisons of the sE-cadherin levels.p=0.031). Low mE-cadherin expression was statistically significantly associated with lymph node positivity (p=0.015) and advanced clinical stage (p=0.001). The inverse relationship between mE-cadherin and sE-cadherin was significant in terms of lymph node positivity (p=0.014) and advanced clinical stage (p=0.037).sE-cadherin levels in the saliva of patients without cancer were lower than those in patients with cancer, and the difference was statistically significant (The results suggest that sE-cadherin levels are significantly increased in patients with oral cancer and that its low expression within the membrane as well as the progression of the disease appear to be inversely associated with levels of sE-cadherin in the saliva. Key words:E-cadher.in, saliva, oral cancer. Oral epithelial cells possess unique morphological characteristics, including extensive inter-cellular junctional complexes and stable cell-cell and cell-matrix adhesions . The decE-cadherin belongs to the cadherin family of proteins, which was first described in connection with tissue specificity since these proteins were found in epithelial tissues . E-cadheAlthough reduced expression of E-cadherin was once considered necessary for metastatic dissemination, several reports have documented invasive and aggressive tumors that nonetheless maintain E-cadherin expression -10.It is now known that not only does its reduced expression play a role in the transition to a malignant phenotype and in cancer progression but that the proteolysis of E-cadherin by several proteases converts the mature 120-kDa E-cadherin to an extracellular N-terminal 80-kDa fragment termed soluble E-cadherin (sE-cadherin), which serves as a paracrine/autocrine signaling molecule in cancer .It has been reported that the serum levels of sE-cadherin are higher in oncological patients than in healthy subjects -14. It iThe goal of our research was to determine, for the first time, the concentration of salivary sE-cadherin in OSCC, to assess the membrane expression of E-cadherin, to correlate this expression with disease characteristics and to determine the association between sE-cadherin and membranous E-cadherin (mE-cadherin).-Patients Individuals diagnosed with OSCC who were patients at the Jalisco Institute of Oncology between January 2013 and February 2015 were enrolled in the study. In all, 26 patients were enrolled . The reason for the greater number of female patients was simply because they volunteered in greater numbers.In addition, samples from 10 individuals without OSCC who visited the clinic for teeth extraction due to orthodontic or prosthetic indications were included  and were treated at the Civil Hospital “Dr. Juan I Menchaca”.The stage of the disease was evaluated in the Surgical Head and Neck Oncology Department, and each tumor was analyzed clinically and by computerized tomography. The disease stages were then determined according to the TNM system .Due to the finding that the diameter of the tumor and the invasion into lymphatic nodes are regarded as important clinical markers involved in prognosis, the lymphatic nodes were considered positive if patients presented metastasis in one or more lymphatic nodes. T stage and total TNM scores were redistributed in accordance with the NCI guidelines , and eacConfirmation of the diagnosis and the tumor grade (differentiation) was determined according to the WHO criteria . Both pr-Selection CriteriaPatients diagnosed with OSCC, who did not receive chemotherapy or radiotherapy, or any other oncological treatment including surgery, were enrolled in this study. Individuals without OSCC but who experienced epithelial autoimmune or inflammatory disease, those who presented isolated ulcerous disorders, e.g., traumatic disorders, or any other kind of lesion in the oral mucosa, and those with any oncological history were excluded from the study.-SamplesUnstimulated saliva was collected between 9 and 11 AM before any surgical procedure was performed and was preserved according to a previously described protocol . Saliva -Enzyme-linked Immunosorbent Assay (ELISA)The concentration of sE-cadherin was measured in the saliva of 24 OSCC patients. Saliva samples from two patients could not be collected or were insufficient for detection. It was also difficult to obtain adequate saliva for the laboratory procedures. This was because patients with tumors in the oral cavity generally experience limited mobility or paralysis or due to the size of the tumor and because the saliva usually contains blood from tumor ulceration or is heavily contaminated because of oral hygiene (both are exclusion criteria according to the protocol).We used the commercially available Quantikine® ELISA kit  according to the manufacturer’s instructions. Briefly, the saliva sample was diluted, pipetted into the wells of the titer plates and incubated with detection antibodies at room temperature for 1 to 2 hours. After incubation, the solution was aspirated, and the wells were washed 4 times. The substrate was added to each well for 20 minutes at room temperature followed by the addition of stop solution. Optical density was measured in an ELISA reader (Bio-hazard model Powean WH4101). All tests were performed in triplicate, and the concentration was calculated from a validated standard curve using a simple linear regression model. Data regarding the total concentration of proteins were unnecessary since the kit we utilized did not require this value; this kit is specifically designed for the quantification of human sE-cadherin and for the determination of its concentration in cell culture supernatants, serum, plasma, urine, and saliva, and therefore, the data are expressed as nanograms (ng) of E-cadherin per ml of saliva.-Immunohistochemistry (IH)Tissue samples from 26 cases were processed and evaluated. From the tissue blocks, 3-μm-thick sections were cut, placed on poly-L-lysine-coated slides, deparaffinized in a 60°C oven for 30 minutes and incubated in xylol for 5 minutes. The sections were then rehydrated in decreasing alcohol concentrations  and washed in distilled water. To retrieve the epitopes, the tissue sections were heated in 10 mM sodium citrate solution at pH 9 in a microwave oven at a maximum power of 750 W for two cycles of 5 minutes each. The sections were then cooled to room temperature and washed with distilled water. Endogenous peroxidase was blocked with 0.9% hydrogen peroxide, and the samples were again washed with distilled water and phosphate-buffered saline solution . The sections were incubated for 30 minutes with a primary antibody against E-cadherin ; following this, the sections were incubated with a biotiny-lated anti-mouse/anti-rabbit secondary antibody and streptavidin/peroxidase complex  for 30 minutes each. The reaction products were then detected with 3,3′-diaminobenzidine-H2O2 (Dako Corp.).Negative and positive controls were obtained from paraffin blocks containing samples of healthy mucosa and fibroma that were collected using a 5-mm punch and placed on the slides along with the samples. The slides were analyzed by an oral pathologist, and the cells were counted as previously described for the HercepTest®  for breast cancer . In this-Statistical AnalysisThe sample size of cases included in this study was in agreement with a previous study in which sE-Cadherin was analyzed in head and neck cancer .The size of the control groups was established by the hospital’s internal policy and was adopted for successful protocol authorization.p value <0.05 was considered statistically significant with a confidence interval (C.I.) of 95%.Data were captured and analyzed using descriptive and inferential non-parametric statistics (SPSS version 20). The sE-cadherin protein concentrations are expressed as median values because the Mann-Whitney U and Kruskal-Wallis tests for quantitative variables are commonly regarded as tests with which to determine medians within the population. Fisher’s Exact Test was used for qualitative variables because the number of samples for some of the analyses was less than or equal to 5. A In all, 26 patients with OSCC were included in this study. The TNM and clinical stages of the patients are shown in The area where OSCC was most frequently found was the tongue (42.3%), followed by the alveolar mucosa (19.2%) and palate (19.2%). T1 and N0 were the stages most frequently reported among patients , but a high percentage of patients in advanced clinical stages (42.3%) was also detected. None of the patients were determined to have distant metastasis (M0).The histopathological assessment of tumor tissues established that 21 tumors (80.8%) were considered well-differentiated, 4 (15.4%) were considered moderately differentiated, and finally, only one case (3.8%) was considered poorly differentiated.-sE-cadherin levels p=0.031)  was lower than that in the saliva of cancer patients , and the difference was statistically significant (p=0.159), N stage (p=0.120), clinical stage (p=0.857), or tumor grade (p=0.273). We also did not observe a marked tendency toward any particular stage. M stage was not considered in this analysis since we did not evaluate a comparative group.The difference in the levels of sE-cadherin was not statistically significant among cases that varied with respect to T stage ; in contrast, statistically significant differences were observed between positive and negative lymph nodes (p=0.015) as well as between early and advanced clinical stages (p=0.001) (The presence of mE-cadherin was classified as either low or high based on the HercepTest®. No significant differences were found in mE-cadherin expression in tumors of different sizes (p=0.001) .p=1.000) based on the presence of mE-cadherin.The degree of differentiation was not statistically significant , whereas high levels of mE-cadherin were associated with low levels of sE-cadherin   compared with the levels of sE-cadherin when the levels of mE-cadherin were high , but this difference was not statistically significant    in positive nodes compared with the levels of sE-cadherin when mE-cadherin was robustly expressed   and inhibitory substances is low . The detSince the degradation of the extracellular portion alone cannot lead to the total loss of E-cadherin protein, we also evaluated the expression of mE-cadherin .The mE-cadherin expression results are consistent with those in many publications in which low expression is statistically significantly correlated with node invasion and advanced TNM stage in OSCC ,25. HoweThe main obstacle against the use of mE-cadherin expression as a trustworthy marker is the occurrence of false-positive detection, in which aggressive, invasive tumors express mE-cadherin -10. It hThese last observations also served to address the last objective of our study, which was to demonstrate new possible associations in OSCC via a comparison of the results of the immunohistochemical analysis to the levels of sE-cadherin by ELISA to interpret the extracellular events that accompany high or low mE-cadherin expression. The inverse relationship we observed was not statistically significant; however, when these values were grouped in accordance with node invasion and advanced TNM stage, this tendency became statistically significant. These results may be associated with the proteolytic events that occur in the tumor microenvironment. These proteolytic events enable neoplastic cells to migrate and invade other sites.In contrast, a small number of OSCC cases exhibited high expression of mE-cadherin and higher median values of sE-cadherin than the control group. This finding allows for the possibility to distinguish tumors by revealing intracellular processes that mediate malignant pathways, independent of extracellular mE-cadherin proteolysis.In addition, we need to consider the difference between statistical and biological significance, since other types of analyses were not included, e.g., gene expression analysis and/or expression analysis in the cytoplasmic region as well as the measurement of proteolytic enzymes that target E-cadherin. However, if our results are both statistically and biologically significant, a therapeutic strategy could be designed to target extracellular or intracellular proteolytic events.


Lifestyle interventions targeting weight loss, such as those delivered through the Diabetes Prevention Program, reduce the risk of developing type 2 diabetes. Technology-mediated interventions may be an option to help overcome barriers to program delivery, and to disseminate diabetes prevention programs on a larger scale.We conducted a meta-analysis to evaluate the effect of such technology-mediated interventions on weight loss.In this meta-analysis, six databases were searched to identify studies reporting weight change that used technology to mediate diet and exercise interventions, and targeted individuals at high risk for developing type 2 diabetes. Studies published between January 1, 2002 and August 4, 2016 were included.P<.001) for the interventions. Several studies also reported improved glycemic control following the intervention. The small sample sizes and heterogeneity of the trials precluded an evaluation of which technology-mediated intervention method was most efficacious.The search identified 1196 citations. Of those, 15 studies met the inclusion criteria and evaluated 18 technology-mediated intervention arms delivered to a total of 2774 participants. Study duration ranged from 12 weeks to 2 years. A random-effects meta-analysis showed a pooled weight loss effect of 3.76 kilograms (95% CI 2.8-4.7; Technology-mediated diabetes prevention programs can result in clinically significant amounts of weight loss, as well as improvements in glycaemia in patients with prediabetes. Due to their potential for large-scale implementation, these interventions will play an important role in the dissemination of diabetes prevention programs. Over 29 million Americans (approximately 9% of the US population) have diabetes, and an additional 86 million Americans have prediabetes, an asymptomatic condition associated with an increased risk of developing type 2 diabetes . In 2002The remarkable success of the DPP generated nationwide efforts to translate the results of the original trial intervention into practice ,5. The NSystematic review of in-person group-based DPP programs demonstrates that they can effectively promote weight loss . AlthougThe primary purpose of this meta-analysis is to assess the effect of technology-mediated lifestyle interventions on weight loss in those at risk for developing type 2 diabetes. We also discuss reported glycemic changes associated with these interventions.We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines for conducting and reporting this meta-analysis  12]. We. We12]. Article titles and abstracts were screened to determine relevance and possible inclusion in the study. Full texts of the resulting articles were then read to determine eligibility based on the inclusion criteria. Authors were contacted directly to request missing weight change data, or clarify intervention methods and participant criteria when necessary.2; or >22 kg/m2 if Asian) and at least one additional risk factor for diabetes ; these criteria were based on those employed in the NDPP criteria [Studies considered for inclusion had to satisfy three criteria. First, the primary objective of the study was to deliver diet and exercise lifestyle interventions using technology  with the aim to achieve weight loss. Second, the study had to target patients with a diagnosis of prediabetes, or a body mass index (BMI) >24 kilograms per meter squared  were also reported, if available.Studies that included a core intervention phase, as well as a postcore maintenance phase, had data extracted and used for this analysis directly after the core phase was completed. This approach served to reduce heterogeneity between studies that did and did not include a maintenance phase. We assessed absolute weight change effect of technology-mediated interventions, and compared results between those interventions modeled on the DPP with those using a different curriculum. We also examined the influence of intervention duration on weight change. Average percent weight change was also reported, if available. Program attrition was also assessed by comparing the number of enrolled participants with the number of program completers.P-value or the CI associated with average weight change.Weight change outcomes in the core phase of each intervention were assessed using a meta-analysis. These outcomes were either directly reported in the study results, calculated by determining the within-person difference between reported weights before and after the intervention, or obtained from the authors. The focus of our study was to observe the effect of technology-mediated interventions on weight change, and since the control groups across the different papers were significantly disparate, we excluded the data reported for control arms and only extracted data from the groups receiving an intervention delivered by technology. Each treatment group (or cohort) was analyzed as one pre/postintervention study. All weights were converted to kg units. Using the standard deviation (SD) of within-person weight change outcomes was necessary for calculating the relative study-influences for the meta-analysis. Studies that did not directly report this value had SDs calculated using either the I2 statistic, defined as I2=100%*(Q-k+1)/Q, that quantifies the proportion of heterogeneity in the trial results beyond chance. Higher I2 is indicative of greater heterogeneity. Based on the observation of significant heterogeneity across studies, study estimates were pooled using a random-effects model that allowed for some random variability between studies, as well as sampling error. Publication bias between studies was assessed visually using a funnel plot. The visual effect is supplemented by the more formal Egger’s test [Heterogeneity between studies was assessed by Cochran’s Q statistic, which is the weighted sum of squared deviations of the study-specific estimates from the overall one, and is distributed approximately as a chi-squared random variable with k -1 degrees of freedom  . We furtr’s test , which ir’s test . An inflThe included studies were of varied types—ranging from observational to blinded and unblinded randomized trials (with or without control)—making a fixed protocol for quality scoring impractical. Instead we performed an indirect quality-adjusted analysis via a meta-regression, adjusting for study duration, examining whether the analysis used intention-to-treat methods, and whether the intervention incorporated DPP material. Statistical analyses were carried out in STATA 13  and R 3.3.0 .After eliminating duplicates, a total of 1024 publications were identified through the databases; one additional publication was identified from searching reference lists and through consultation with experts. Each publication was screened by title and abstract. The resulting 52 publications were reviewed in full, 37 of which were excluded because they did not meet inclusion criteria. The final systematic review included 15 publications that reported outcomes for a total of 18 intervention arms .Of the 15 studies included: 6 were RCTs in which the technology-mediated treatment arm was compared to standard care or a face-to-face intervention; 2 included control arms but assigned treatment conditions by community and without randomization; 3 randomly assigned participants to different technology-mediated intervention arms; 1 included parallel interventions arms assigned by community and without randomization; 2 were prospective cohort studies; and 1 allowed participants to self-select into the treatment arm. A total of 2774 participants were enrolled in the technology-mediated interventions, of whom 2247 had follow-up data included in the final meta-analysis. Averaged across studies, enrolled participants were 49 years old and had a starting BMI of 29 (excluding 1 study that did not report baseline BMI ). ThirtyThe duration of the interventions ranged from 12 weeks to 2 years. Half of the studies were modeled on the DPP ,25,27-29P=.002) using Egger’s test, indicating a potential for publication bias. However, Rosenthal’s fail-safe N was above 4000 (more than 40 times the 5k+10 threshold) suggesting the potential threat from such bias to be quite small. For this reason, no corrective action was undertaken.The funnel plot in 2=96.1%, P<.001), a random-effects meta-analysis of the change in weight was performed utilizing 18 cohorts from the 15 studies. P<.001). The DPP-based interventions resulted in marginally higher (P=.074) average weight loss  than non-DPP interventions . The contribution of each study to the overall effect ranged from 3.2-6.6%. Furthermore, the influence plot in Given significant heterogeneity across studies  in individuals at risk for diabetes. Additionally, as evidenced by our finding that 8 of 18 intervention arms [This meta-analysis shows that technology-mediated interventions lead to clinically significant weight loss  and smartphones (67%) . These uTwo design components that were of particular interest in this meta-analysis were: (1) studies based on the DPP curriculum, and (2) study duration. While not quite achieving statistical significance, there was a strong trend toward more weight loss in the intervention arms that were based on the DPP curriculum. Studies investigating the efficacy of technology-based interventions often rely on short-term follow-up, which is commonly seen as a limitation of the existing body of literature. Our analysis shows no effect of intervention duration on weight loss outcomes, which is not consistent with previously reported literature . It is pOne limitation of our meta-analysis was the inability to compare intervention and control weight change results within the studies. This issue arose because only four studies were RCTs with a nontechnology control arm. To demonstrate whether technology-mediated interventions have comparable weight loss outcomes to in-person interventions, future studies are needed that directly compare these two cohorts. There was wide heterogeneity in intervention type, duration, population, and study attrition. Furthermore, none of the included studies had large sample sizes. Thus, conclusions could not be drawn about which method would be most efficacious. The variety of reported glycaemia changes limited our ability to perform a meta-analysis of these results. There was a fair amount of heterogeneity across the studies when examining study populations, as well as interventions used. This heterogeneity raises concerns for the statistical pooling of study results, but it strengthens the generalizability of the conclusions drawn from this systematic review, and provides important implications for the implementation of diabetes prevention programs.Quality assessment was difficult, given the variety of study designs. Even in those studies that were RCTs, several standard quality criteria were not applicable. For example, complete blinding cannot be achieved within behavioral intervention studies. Instead, we chose three quality criteria that were relevant across studies  and included them as independent predictors in the meta-regression.Those technology-mediated interventions that were modeled after the DPP tended to result in greater weight loss compared to the non-DPP modeled interventions, although this difference was not statistically significant at the .05 level. Further research is needed to test the hypothesis that weight loss outcomes can be optimized by incorporating the DPP curriculum.Several studies investigated the effect of technology-mediated interventions on specific populations, such as younger populations or those in rural settings. Further investigation is needed using large methodologically sound comparative-effect research trials to determine which interventions are most efficacious in facilitating weight loss and glycemic improvement in specific demographic categories of participants at risk for developing diabetes. Such categories include specific age ranges, BMIs, and genders, as well as social, economic, and ethnic backgrounds. It has been shown that the success of a lifestyle intervention is largely affected by the participant’s ability to choose the intervention modality , but facStudies are needed to examine how accessible these interventions are in low-income urban populations. For technology-mediated diabetes prevention interventions to expand the reach of diabetes prevention to a greater number of individuals at high risk for developing diabetes, research is needed with respect to intervention cost and payment models.The inconsistency between using fasting blood glucose and hemoglobin A1c to measure metabolic control made it difficult to determine the extent to which technology-mediated interventions affected glycemic improvement. Weight loss was instead used as a direct health outcome measure. Some interventions may not result in weight loss but may improve glycemic control. Ideally, studies would include both weight loss and glycemic control (which would be measured using both fasting glucose and hemoglobin A1c) as a standardized evaluation methodology.While a few of the studies in this analysis compared different forms of technology, further analysis is required to understand the advantages that each technology contributes to intervention outcome. In addition, the efficacy of maintenance phase interventions needs to be adequately assessed by comparing the weight loss outcomes and glycaemia of those who choose to stay in maintenance phase and those who decide to drop out. Understanding of such factors could guide the establishment of technology-mediated interventions as a potential correlate to the NDPP’s current program.Our meta-analysis showed that technology-mediated diabetes prevention interventions resulted in weight loss and lead to significant improvements in glycaemia. These results suggest that technology-mediated interventions could be an alternative to in-person diabetes prevention programs. The option of using technology-mediated delivery can potentially overcome barriers of access and allow expanded dissemination of such interventions.


Preclinical studies support an antitumor effect of metformin. However, clinical studies have conflicting results and metformin's effect remains controversial. The aim of this study was to evaluate metformin's effect on clinical outcomes in diabetic patients with pancreatic cancer treated with curative resection.p < 0.001) was significantly higher in the 530 metformin users than in the 234 diabetic metformin non-users. After multivariable adjustments, metformin users had significantly lower cancer-specific mortality as compared with metformin non-users . Cubic spline regression analysis demonstrated significantly decreased cancer-specific mortality with increasing dose of metformin (p = 0.0047).A total of 764 patients underwent curative resection, met none of the exclusion criteria, and were prescribed oral hypoglycemic agents. The cancer-specific survival (5-year, 31.9% vs. 22.2%, Data were provided from the Korea Central Cancer Registry and the National Health Insurance Service in the Republic of Korea. The study cohort consisted of 28,862 patients newly diagnosed with pancreatic cancer between 2005 and 2011. Metformin exposure was determined from prescription information from 6 months before the first diagnosis of pancreatic cancer to last follow-up. The main outcome was cancer-specific survival.This large study indicates that metformin might decrease cancer-specific mortality rates in localized resectable pancreatic cancer patients with pre-existing diabetes, independently of other factors, with a dose-response relationship. Pancreatic cancer has become the seventh leading cause of cancer mortality in the world. In 2012, 337,872 people worldwide were diagnosed with pancreatic cancer, and 330,391 people died of this cancer .The relationships between diabetes and pancreatic cancer are especially complicated and intertwined. About 80% of pancreatic cancer patients have either glucose intolerance or diabetes . PancreaMetformin , one of the most widely prescribed drugs for type 2 diabetes mellitus, has been shown to be clinically associated with antitumor effects , 13. ThrHence, we hypothesized that the use of metformin might be associated with survival benefits for patients with resectable pancreatic cancer. We conducted a cohort study based on a nationwide population database to evaluate the effect of metformin on the clinical outcomes in patients with pre-existing diabetes and pancreatic cancer treated with curative resection.Among 28,862 pancreatic cancer patients who were diagnosed between January 1, 2005 and December 31, 2011, 1,919 patients met the eligibility criteria described in Figure p < 0.001 by the log-rank test) was significantly higher in the metformin user group than in the metformin non-user group among the diabetic groups during the follow-up period , C25) recorded by the KCCR between January 1, 2005 and December 31, 2011. Only individuals, who had undergone curative resection for localized pancreatic cancer, were eligible. The Whipple`s procedure, p ylorus-preserving pancreaticoduodenectomy, or distal pancreatectomy was defined as curative resection. Those, whose surgery was aborted due to findings of unresectability at the time of surgery, were excluded. The individuals with the age of 40 or less were excluded due to the possibility of genetic or family syndrome. The individuals were excluded if they had a history of invasive cancers other than pancreatic cancer or a follow-up duration of less than 1 month, died from complications following surgery, or were not diagnosed with pancreatic adenocarcinoma. The death from complications following surgery was defined as the death without evidence of disease progression within 1 month of the surgery date.The drug exposures of interest were metformin and non-metformin . Drug exposure was defined as OHAs or insulin medication administration in the same class for at least 90 days in the period from 6 months before first diagnosis of pancreatic cancer to last follow-up. Participants were classified as patients with pre-existing diabetes and pancreatic cancer if they had a diagnosis of non-insulin-dependent diabetes  and received the drug exposure on the basis of the above-mentioned definition. The MPR was defined as the total days the target medication was prescribed divided by the total days between prescriptions. An MPR of more than 80% was considered acceptable adherence. Cohort entry date for each patient was the date of first diagnosis of pancreatic cancer, and the exit date (censoring date) was the earliest of: a) date of death; b) date of recording of clinical event; c) 5 years after cohort entry or d) the end of the study period .In the main analysis, we compared the baseline characteristics and medications for OHA for patients with and without use of metformin. We further compared the event rates for cancer-specific mortality during the follow-up period between patients with and without metformin by cumulative probability curves derived from Kaplan-Meier estimates; the same analysis was applied for MPR groups among patients with metformin. After unadjusted analyses were initially performed, we conducted adjusted analyses, including the following potential confounders: age, sex, and Charlson comorbidity index . We perfWe conducted sensitivity analyses by the following restrictions. In the first sensitivity analysis, we restricted analysis among those whose exposure of metformin initiated from 180 days before pancreatic cancer diagnosis through the date of pancreatic cancer diagnosis to control immortal time bias . In addi


We measured the reactive hyperemia index, which is a measure of the endothelial responsiveness, by the use of an endoPAT device  in 48 ART treated HIV-infected patients with high CD 4 cell counts and viral suppression (HIV-RNA < 20 copies/mL), who had previously undergone measurement of the myocardial perfusion reserve by 82-rubidium PET/CT for study purposes. We found an inverse correlation between the reactive hyperemia index and the myocardial perfusion reserve which most likely indicates different vascular physiology. This study did not find evidence to suggest the immediate implementation of the reactive hyperemia index as a screening tool for early coronary artery disease in well-treated HIV-infected patients pending further validation in larger prospective studies.After the introduction of antiretroviral therapy (ART) the life expectancy of patients infected with human immunodeficiency virus (HIV) is now approaching that of the general population and the importance of non-AIDS co-morbidities is increasing. Specifically, the risk of coronary artery disease (CAD) seems to be higher in HIV-infected patients and an accurate risk prediction of CAD is of high importance for optimal long term treatment. In this study, we assessed the correlation of the endoPAT, which is an office-based CVD screening tool with the myocardial perfusion reserve by  This method enables the quantification of the absolute myocardial perfusion by injection of a perfusion positron-emitting tracer which allows for the estimation of the vasodilator function of the coronary circulation. Coronary microvascular dysfunction reflects the initiation and early changes in the progression toward CAD .82-rubidium PET/CT and endoPAT studies was 3.3 years (range 2.0–4.3).All participants were caffeine and nicotine abstinent for 6 h prior to the examination. The EndoPAT  was performed according to the manufacturer’s instruction in a single session with a total duration of approximately 30 min including 10 min of rest, 5 min of total occlusion of the brachial arteries, and 10 min post-occlusion rest. Blood pressures were measured prior to the test. The ratio between rest and post-occlusion was calculated automatically by the EndoPAT software, providing the reactive hyperemia index (RHI). All measurements were performed by a single observer. The mean duration between the 82-rubidium PET/CT for study purposes and the methods have been described in detail elsewhere [82-rubidium supplied from a CardioGen-82 Sr-82/Rb-82 generator . Stress images were acquired during the infusion of adenosine. The myocardial perfusion reserve was calculated as the myocardial stress perfusion/myocardial rest perfusion. These values were corrected for baseline cardiac work [All patients in this study had previously undergone lsewhere . In brieiac work . A low-diac work .Blood samples were drawn at routine visits at the HIV out-patient clinic and analysed for CD 4 cell counts by flow cytometry using the BD Multitest™ , and HIV RNA using the AmpliPrep/COBAS, TaqMan HIV-1 test vers. 2.0 . Quantitative determination of blood lipids was performed using the Cholesterol gen2 . All blood tests were routinely performed by the hospital laboratory.The Framingham risk score (FRS) was calculated according the published definitions  as the rt-test on log-transformed data or by analysis of variance (ANOVA) if more than two groups. Categorical variables were compared by Chi-square test.Data are shown as mean ± standard error of the mean (SEM), median (IQR) or number (percentage) where relevant. Correlation analyses were performed by Pearson correlation on log-transformed data, whereas groups were compared by unpaired Statistics were performed on SPSS 22 .Baseline characteristics of the 48 patients are presented in 82-rubidium myocardial perfusion study and the endoPAT study. In our study, 70% of the patients had a normal myocardial flow reserve as assessed by 82-rubidium PET/CT and 67% had a normal reactive hyperemia index.p = 0.007). Further, a negative linear correlation was found between the levels of MFR and RHI as shown in r = −0.38, p = 0.009), and this linear correlation was not explained by differences in underlying CHD risk since adjustment for FRS only attenuated this correlation slightly . The patients with a positive CACS (defined as CACS ≥ 1) did not have impaired RHI , and a positive correlation was found between CACS and RHI even when adjusting for FRS , whereas an inverse correlation was found for CACS and MFR also adjusting for FRS .As can be seen in 82-rubidium PET/CT for study purposes, we studied the correlation between the peripheral flow mediated dilation  and the myocardial flow reserve to assess the value of the endoPAT as a screening tool for early CAD. This method would offer an easy and non-invasive way to assess changes in coronary vasomotor function as a sign of early CAD. Contrary to our hypothesis, we found an inverse correlation between the MFR and RHI and as such we recommend that the endoPAT be validated in larger prospective studies before the implementation as a screening tool for CAD among HIV-infected patients. Endothelial dysfunction has been shown to be an early step towards CVD [In this follow-up study of 48 HIV-infected patients, who had all previously undergone ards CVD ,35 and sards CVD  as well ards CVD . The lacards CVD . It therards CVD ,37, wherards CVD ,39,40.82-rubidium PET/CT and the endoPAT-study and subjects in the study could have made lifestyle changes which are not accounted for here, which could possibly affect the reactive hyperemia index. However, we found a mean increase in FRS of 3.4% between the two studies, which can be explained predominantly by the increase in age. Finally, this study is cross-sectional including only HIV-infected patients without the possibility of comparison to a non-infected population.Interestingly, already one of the first studies to validate the endoPAT against myocardial perfusion found that there was no correlation using adenosine . Studies82-rubidium PET/CT, we found an inverse correlation between the two methods. Larger prospective studies are warranted to confirm our findings before any recommendations can be made on the use of the endoPAT as an office-based screening tool for detection of early CAD among HIV-infected patients.In this first comparative study of the peripheral reactive hyperemia index by the endoPAT and the myocardial perfusion reserve as assessed by