The beta-lactamase enzyme provides effective resistance to beta-lactam antibiotics due to substrate recognition controlled by point mutations. Recently, extended-spectrum and inhibitor-resistant mutants have become a global health problem. Here, the functional dynamics that control substrate recognition in TEM beta-lactamase are investigated using all-atom molecular dynamics simulations. Comparisons are made between wild-type TEM-1 and TEM-2 and the extended-spectrum mutants TEM-10 and TEM-52, both in apo form and in complex with four different antibiotics . Dynamic allostery is predicted based on a quasi-harmonic normal mode analysis using a perturbation scan. An allosteric mechanism known to inhibit enzymatic function in TEM beta-lactamase is identified, along with other allosteric binding targets. Mechanisms for substrate recognition are elucidated using multivariate comparative analysis of molecular dynamics trajectories to identify changes in dynamics resulting from point mutations and ligand binding, and the conserved dynamics, which are functionally important, are extracted as well. The results suggest that the H10-H11 loop (residues 214-221) is a secondary anchor for larger extended spectrum ligands, while the H9-H10 loop (residues 194-202) is distal from the active site and stabilizes the protein against structural changes. These secondary non-catalytically-active loops offer attractive targets for novel noncompetitive inhibitors of TEM beta-lactamase. Drug resistance in bacteria remains a major concern for public health ,2. AntibOne of the leading causes of resistance to beta-lactams in bacteria is the production of an enzyme called beta-lactamase . Beta-laAlternatively, beta-lactamases can be classified based on the class of drugs they provide resistance to . Narrow Outside of its clinical significance, beta-lactamase provides an interesting model for studying the role of dynamics on ligand binding. Despite hydrolysis of many substrates, the catalytic mechanism is relatively conserved between class A, C, and D enzymes. The structure of wild-type TEM-1 beta-lactamase is shown in Mutations in TEM beta-lactamase at residues such as Arg164 and Gly238, known as primary mutations, are often associated with novel resistance through the reduction of substrate specificity . Many seIn general, the effects of a mutation may induce changes in structure or motions far away from the vicinity of the substitution . MutatioIn this work, the dynamics of four class A TEM beta-lactamases are investigated by Molecular Dynamics (MD) simulation. The dataset contains simulations of TEM-1 and TEM-2 (representing NSBL) and TEM-10 and TEM-52 (representing ESBL) both in apo form and bound to four antibiotic substrates: ampicillin, amoxicillin, cefotaxime, and ceftazidime. The functional dynamics critical for substrate recognition are investigated using a model of dynamic allostery developed via machine learning. Dynamic allostery is a form of functional dynamics that deals with how a secondary binding event that is distant from the catalytic pocket alters vibrations . MechaniIn the rest of this paper, Eight X-ray crystal structures  and cefotaxime and ceftazidime were docked with an apo TEM-52 molecule (1HTZ), following the functional substrate profiles of the enzymes. Rigid receptor docking was performed using AutoDock Vina  and DockSimulations were performed following the protocol described in prior work . The ambThere are 32 apo systems, consisting of the TEM-1, TEM-2, TEM-10 and TEM-52 mutants, each starting with eight different crystal structures, yielding a combined total of 16 Using Java Essential Dynamics Inspector (JEDi) , each trn MATLAB ,47.k-th eigenvector, p is the number of eigenvectors (modes) equal to the state space dimension.Dynamic allostery is quantified by observing changes in correlated motions due to coupled binding events. Normal modes with the lowest frequencies represent the largest-scale correlated motions of a protein, which contribute most to the transmission of dynamic allostery. Under the quasi-harmonic approximation, the unperturbed Hessian matrix matrix Σ . From anThe modes with the lowest eigenvalues of the covariance matrix dominate the sum in Equation , yet theEquation . This miThe effect of ligand binding is modeled by adding pairwise harmonic restraints (springs) in a local spherical region that encapsulates a binding site. Each spring with spring constant i and j represents a harmonic potential provided by 2); however, as previously shown [Notice that Equation  allows tEquation , the perly shown , the resd Dryden , the chak-th normal mode has three frequencies of interest: the apo frequency, The r is a data packet index. Multiple data packets  were constructed by subsampling conformations in a trajectory. The output of SPLOC provided p modes defining a complete orthornormal basis set of vectors, where the k-th mode is denoted as Through a comparative and exploratory analysis, the functional mechanisms within beta-lactamase were extracted by supervised projection pursuit using Supervised Projective Learning for Orthogonal Completeness (SPLOC) ,51,52. Ting JEDi . The inpr-th data packet within a mode feature space plane (MFSP) for mode k. As there are two emergent properties (mean and standard deviation) per mode, the feature space dimension is A feature space was constructed from the mean and standard deviation of the data projected into each mode, such that vided in .k-th mode, there are three measures: (1) selection power, k-th mode as discriminant, undetermined, or indifferent, respectively called d-, u-, or i-mode. If any one of the three measures fell below a minimum threshold, the mode was classified as u-mode. Cross-validation was conducted within SPLOC through the consensus measure as the basis set was optimized. Thus, if a mode was not identified as a u-mode, only two cases were possible;  could be identified when functional and nonfunctional data packets were linearly separable and statistically indistinguishable within an MFSP. Each mode was assigned a rectifying adaptive nonlinear unit (RANU) in order to bifurcate mode identity towards either d-mode or i-mode. As the parameters of a RANU are data-driven based on the properties of its mode projection, a heterogeneous network of p RANUs can determines the mode efficacy, For the The total efficacy of a proposed orthonormal basis set is provided by In this study, two main categories were considered in the course of elucidating the functional dynamics of beta-lactamase by quantifying similarities and differences in dynamics using SPLOC. Each category represents functional versus nonfunctional classes. The first category provides a protein-centric comparison, where differences and similarities in protein dynamics depend on NSBL versus ESBL. The second category provides a ligand-centric comparison, where differences and similarities in protein dynamics depend on broad versus extended spectrum antibiotics. While the protein-centric perspective takes into account all MD trajectories, the ligand-centric perspective is only relevant for proteins when ligands are present. The data packet statistics used in subsequent analyses are summarized in M frames each, a subsample of m frames were randomly drawn and concatenated together. Through this method, A bootstrap approach was used in which all trajectories that shared a common characteristic were combined. From a given trajectory pool of p. In such cases, the actual RMSF and the PCA-projected RMSF will generally be very similar, which is the desired result because it is of interest to capture most of the dynamical motion using a relatively small number of PCA-modes. Using the same projection concept, the RMSF measure can be generalized using the d-modes and i-modes obtained from SPLOC. Specifically, it is possible to observe distinctly different conserved motions between two systems by using  to project out unwanted motions. When comparing functional versus nonfunctional systems, the observed differences in motion may not be related to function, and conserved motions can be important for function.A common measure obtained from MD simulations is the root mean square fluctuations (RMSF). It is common to project out small amplitude motions using a small number of PCA-modes (with largest variances) compared to n is the number of frames, the projected data matrices for the discriminant subspace, By knowing which parts of motion differ between systems and which parts are similar, it is possible to glean insights into which motions support a function and why. A hypothesis involving functional dynamics can then be refined by inductive reasoning as additional comparisons are made. After being projected to be within the  subspace, dynamical fluctuations are called . The discriminant RMSF (dRMSF) and indifferent RMSF (iRMSF) are calculated using the standard procedure for calculating RMSF, except that the first step is to respectively construct a projection operator from the d-modes and i-modes. The second step then projects out all motions outside the subspace of interest. Where there is a data matrix Each of the 32 apo and 16 holo trajectories conserved secondary structure across the TEM-1, TEM-2, TEM-10, and TEM-52 beta-lactamase mutants over The dynamics of beta-lactamase are fairly constrained, with one or two distinct basins visited by each mutant during the simulation time window. While the dynamics of the apo and holo enzymes span similar phase spaces as defined by PC-1 and PC-2, there is a slight shift of means along PC-1 between the two forms of the enzyme. Based on this analysis, it can be seen that ligand binding reduces flexibility and conformational diversity, while large-scale motions are similar between apo and holo simulations. However, differences occur on a local scale, which requires a more detailed method of extracting the functional dynamics.A perturbation scan of the Most strikingly, all three mutants show a similar pattern of allostery response, with the largest conserved shift occurring in the H10-H11 loop. terature ; Horn etIn addition to predicting this known allosteric pocket, the perturbation scan predicted multiple other locations for off-target binding sites. Notably, H3 and H4  shows an inhibiting allosteric regulation effect when constrained, and the H7 helix  shows an enhancing allosteric regulation when constrained. While the perturbation response at these regions is weaker than from the primary allosteric pocket, these results suggest that beta-lactamase can be dynamically modulated by off-binding sites.It can be observed that the dynamic response to the Gln39Lys mutation in TEM-2 is localized to specific residues that are distant from the mutation itself. The largest dynamic differences occur at Glu197, Leu198, Lys215, and Arg241. The closest major change in dynamics to the mutation is The dynamic differences extracted from TEM-10 versus TEM-1 and TEM-52 versus TEM-1 are significantly similar in H2, the omega loop, and the H9-H10 loop. To a lesser extent, dynamic differences are similar at the H10-H11 loop, the These results show that the ESBL mutations cause changes at the active site and in the omega loop, as well as weaker long-range effects. The most notable such weaker response is at the H9-H10 loop (residues 194-202), which is distant from both the active site and all three sets of mutations. This relatively hydrophobic loop was the only part of the enzyme that had sensitive dynamic changes to all three sets of mutations. A site-directed mutation study carried out in 1992  showed tIn order to investigate the changes in dynamics before and after ligand binding, all 48 simulations were partitioned into groups by the mutant they represent and then further divided into apo/holo classes for SPLOC comparison , while for NSBL enzymes (TEM-1 and TEM-2) the magnitude of motion remained essentially unchanged. This large disparity in the way dynamic changes occur depending on the functional class suggests that this loop plays a key role in coordinating or stabilizing the ligand in the binding pocket for the extended spectrum enzymes. Although the quenching effect on dynamics occurs throughout most of the ESBL enzymes, at the H10-H11 loop it is especially prominent in the TEM-52 mutant.A close inspection of the MD trajectory revealed that the H10-H11 loop can take several conformations, as illustrated by snapshots in In addition to the role played by the H10-H11 loop, the dRMSF in The biochemical distinction between beta-lactamase mutants is in how effectively they bind to a particular ligand. From this perspective, the four beta-lactamase mutants compared here are all functional. The holo simulations represent the various ways beta-lactamase can function in binding either broad-spectrum or extended-spectrum antibiotics. Similarities between these complexes can provide insights into a common ligand-independent inhibition mechanism. Therefore, the holo simulations were divided and compared according to both the protein perspective (NSBL versus ESBL) and the ligand perspective (broad-spectrum versus extended-spectrum antibiotics). From the protein perspective, SPLOC found In the indifference subspace, molecular motions are statistically indistinguishable. The iRMSF from the ligand perspective, shown in TEM beta-lactamase is dynamically constrained on a global scale while exhibiting variations in loop motions sensitive to mutations and ligand binding. In agreement with other recent studies ,57, the Dimension reduction using PCA to describe essential dynamics has long been used as a standard method for extracting functional motions from molecular dynamics simulation data ,59. Despn PCA modes and averaged over all modes in the SPLOC subspace for both SPLOC subspaces  and the full SPLOC basis set (In The i-modes describe the functional similarity between mutant pairs that is most conserved. This motion is expected to be associated with the dominant enzyme dynamics through large-scale motions, which are mainly determined by the structure of the protein. Due to the enzymes’ high degree of structural similarity, the CO of i-modes expressed in terms of PCA modes increases faster than the reference line until the dimension of the i-mode subspace is reached. The motions described by u-modes are not statistically different or the same between a pair of mutants, and thus capture outlier motions that may have been expressed differently between simulations of the same enzyme. Being sensitive to outliers, PCA often captures this high variation in the top modes, which explains why the u-modes initially increase rapidly in CO until the dimension of the subspace for u-modes is reached. Finally, The MD/SPLOC results suggest that the H9-H10 loop plays a key stabilizing role, which is in agreement with previous work  postulatactamase ,60, whicThe results in Extended spectrum ligands such as cefotaxime and ceftazidime are typically larger than their broad spectrum counterparts, and are therefore harder to accommodate in the active site. Analysis comparing all three mutation sets shows a change in motion in the H10-H11 loop for TEM-10 and TEM-52 c,d. A coContact with the H10-H11 loop does not appear necessary for ligand hydrolysis, rather promoting the capture, chaperoning, and stabilization of the protein ligand complex. For example, cefotaxime was able to resist being pulled into the solvent, although this H10-H11 loop contact was only intermittent during the simulation. In the TEM-1 holo simulation, the cefotaxime was able to reposition itself in the pocket to interact with the H10-H11 loop while remaining anchored to the omega loop. Ampicillin and amoxicillin can reside in the binding pocket, despite not being able to reach this loop. This secondary anchor forces the extended spectrum ligands to stretch across the active site, putting them in a more favorable position for catalysis. Although not required for function, these results show that this loop plays an important role in expanding substrate specificity for TEM beta-lactamase.The dynamic allostery perturbation scans of the four TEM beta-lactamase mutants suggest that substrate binding is coupled to distal loop regions. In combination with previous results from the literature, a mechanism involving the known allosteric binding pocket for reducing antibiotic affinity is examined here in detail.According to the scan, binding an effector to H11 is likely to enhance the binding affinity of antibiotics at the active site. In prior experimental work, destabilization of this region was shown to inhibit activity ,61; hereBinding an effector near residues 227-229 and nearby to residues 254-256 may inhibit binding of ligands at the active site. This mechanism is directly related to the primary allosteric region of beta-lactamase, as it houses the pi-stacking Pro226-Trp252-Pro229 triad, which is thought to stabilize this region. Strain in this region due to effector binding increases the likelihood of disrupting this interaction and further disrupting the structure of the active site, including the H10-H11 loop via long-range dynamic signal propagation. SPLOC identified large conformational fluctuations in this loop, enabling the enzyme to adapt the shape of the binding pocket to various beta-lactam molecules.Another allosteric target area was found at residues 104-106 and 111-115. This allosteric signal is strong for all mutants; however, in TEM-52 this reflects the location of the Glu104Lys mutation. Tyr105 on this loop has been previously identified as an important residue via mutation studies  and NMR It appears that the H9-H10 loop resists structural changes to beta-lactamase, although it was not identified as allosteric in the perturbation scan. While loop dynamics may not directly couple to active site residues, they are influenced by distant residues. Therefore, the H9-H10 loop may be a viable inhibitor target, as its flexibility is well conserved across mutation sets and ligand binding differences in TEM beta-lactamase. As an alternative approach to dynamic allostery, SPLOC results can be used to gain insights into how to optimize dynamic properties that improve enzyme binding. Binding a ligand to or near this loop may force the H9-H10 loop into a conformation with more rigidity, preventing the loop from maintaining stability through its dynamic mechanism. The region between H10 and the The functional dynamics of TEM beta-lactamase for substrate recognition were investigated using MD simulations. Perturbation scans revealed allosteric target sites, including the known allostery pocket between the H11 and H12 helix and the H3-H4 helix–loop region. Multivariate comparative analyses applied to the simulation data provided a detailed look at the way in which point mutations and ligand binding affect the internal motion of the protein. These comparisons showed that certain mutations from TEM-1 introduce flexibility into the active site, allowing extended-spectrum antibiotics of various shapes to fit into the binding pocket.The dynamics in most loops contribute to the way in which the protein responds to ligand binding and mutations. Comparing different mutants with the wild type TEM-1 enzyme in apo form revealed that mutations modulate the flexibility of the active site, which influences specificity. The ligand is primarily anchored in the binding pocket by the omega loop and the


While tobacco Quitlines are effective in the promotion of smoking cessation, the majority of callers who wish to quit still fail to do so. The aim of this study was to determine if 12-month tobacco Quitline smoking cessation rates could be improved with re-engagement of callers whose first Quitline treatment failed to establish abstinence.In an adaptive trial, 614 adult smokers, who were active duty, retired, and family of military personnel with TRICARE insurance who called a tobacco Quitline, received a previously evaluated and efficacious four-session tobacco cessation intervention with nicotine replacement therapy (NRT). At the scheduled follow-up at 3 months, callers who had not yet achieved abstinence were offered the opportunity to re-engage. This resulted in three caller groups: 1) those who were abstinent, 2) those who were still smoking but willing to re-engage with an additional Quitline treatment; and 3) individuals who were still smoking but declined re-engagement. A propensity score-adjusted logistic regression model was generated to compare past-7-day point prevalence abstinence at 12 months post Quitline consultation.Using a propensity score adjusted logistic regression model, comparison of the three groups resulted in higher odds of past-7-day point prevalence abstinence at follow-up at 12 months for those who were abstinent at 3 months compared to those who re-engaged , and relative to those who declined re-engagement . There was no statistically significant difference in smoking abstinence between smokers at 3 months who re-engaged and those who declined re-engagement .Tobacco Quitlines seeking to select a single initiative by which to maximize abstinence at follow-up at 12 months may benefit from diverting additional resources from the re-engagement of callers whose initial quit attempt failed, toward changes which increase callers’ probability of success within the first 3 months of treatment.This study is registered at clinicaltrials.gov (NCT02201810). In 2016, the Secretary of Defense issued a memorandum3 calling for action to address the high prevalence of tobacco use in the military. The memo mandated dramatic increases in the cost of tobacco products in military stores, establishing price parity with historically more expensive off-base establishments, and called for improved and expanded tobacco cessation programs.Tobacco is the single most preventable cause of death in the US4. Consequently, the Defense Health Agency-administered health system ‘TRICARE’ shares with national and state public health interests a common challenge germane to tobacco control: how best to reach millions of smokers seeking to quit. Available virtually anywhere where there is a phone service, tobacco Quitlines offer a compelling combination of reach and effectiveness5. Proactive Quitlines  produce better outcomes relative to reactive Quitlines 6; and this general effect has been replicated with active-duty military and TRICARE beneficiaries, for whom proactive treatment has doubled the odds of abstinence from tobacco at the follow-up at 12 months7. But even with the aid of proactive treatment, the majority of those who desired to quit smoking failed to do so, and half of the smokers who quit during treatment had re-initiated by the follow-up at 12 months7. The decay of tobacco cessation treatment effects over time is firmly established in the tobacco control literature9. As a result, a growing body of research has developed on how to best re-engage Quitline callers whose initial quit attempt was not successful.The Military Health System serves over 9.6 million retirees, family members, and active-duty military members living and working in countries around the world10 , for example, observed a five-fold increased odds of re-engagement as a consequence of proactive telephone outreach by Quitline staff between one and three months after the initial quit attempt. More extensive literature, dating back nearly 10 years, characterizes phone contact as effective in re-engaging 12–28% of Quitline participants who failed a previous quit attempt12. Still unclear, by contrast, is the degree to which re-engagement assists callers following an unsuccessful quit attempt. Characterization of the effectiveness of such re-engagement efforts will assist Quitlines in determining how best to allocate finite personnel and financial resources.Emerging evidence suggests that re-engagement efforts made by Quitlines function to increase the probability that participants will make subsequent quit attempts. Vickerman et al.The current study sought to address this gap in the literature by determining the degree to which Quitline abstinence rates can be improved with re-engagement of callers whose first Quitline treatment failed to establish abstinence. To this end, we compared tobacco use rates at 12 months across three groups of participating TRICARE beneficiaries who called the ‘Freedom Quitline’: 1) those who were abstinent at check-in at 3 months; 2) those who were still smoking at 3 months but accepted an invitation to re-engage with proactive tobacco Quitline treatment; and 3) individuals who were still smoking at 3 months but declined the opportunity to re-engage for a second Quitline treatment. We were interested in how re-engagement at 3 months improved outcomes at follow-up at 12 months. We were also interested in how participants who re-engaged compared at 12 months with those who had either reported abstinence at the check-up at 3 months or were still smoking but declined the opportunity to re-engage.13. Participants were those who were still smoking at 3 months following an initial Quitline intervention composed of counseling and nicotine replacement therapy. Smokers who were willing to try again were randomized into three re-engagement conditions: rate reduction, repetition of the initial treatment, or their choice of the preceding treatments. Quitline interventionists were research specialists trained to provide tobacco cessation treatment as part of the National Heart, Lung, and Blood Institute . Dubbed the ‘Freedom Quitline’, this service provided smoking cessation treatment exclusively to TRICARE beneficiaries from 2017 through 2020 (Supplementary file).This adaptive trial is a secondary analysis of data which derive from a randomized controlled trial designed to determine the effect of three re-engagement strategies on long-term smoking cessationRecruited participants were 614 adult TRICARE beneficiaries, including active-duty and retired military personnel from the Army, Navy, Air Force, Marines, and Coast Guard, and those among their family members covered under their insurance. Participants were recruited with physical and electronic media including posters, flyers and business cards at medical and dental facilities on military bases and through websites including TRICARE.mil, Military. com, thewingmantoolkit.org, Health Net Federal Services (hnfs.org), soldierforlife.com, 79 mdw.af.mil, and UCANQUIT2.org. Eligible participants were aged ≥18 years, had smoked at least five cigarettes daily over the preceding year, and were willing to make a quit attempt in the next 30 days. Because participation entailed access to nicotine replacement therapy (NRT), individuals who were pregnant, breastfeeding, or planning to become pregnant in the next 12 months, those with a pre-identified allergy to nicotine, or with an unstable heart condition, were excluded from the study. All persons participating in this study gave informed consent prior to engaging with the protocol.14. Other smoking-related variables included number of cigarettes smoked per day, number of years smoked, lifetime number of quit attempts, and use of NRT and additional prescription smoking cessation aids, each of which was queried directly. Past-7-day point prevalence, the primary outcome measure, was defined as the self-reported absence of tobacco use within the seven days preceding follow-up at 3 months and at 12 months15, as determined over the phone by study the research specialists.All measures were administered by telephone at baseline, at 3 months, and at 12 months from the enrollment date. Demographic variables included age, gender, race, ethnicity, education level, military status, and marital status. Smoking-related variables included intensity of physical addiction to nicotine, evaluated using the Fagerström test for nicotine dependence (FTND)All participants engaged in an initial series of four proactively initiated telephone smoking cessation calls executed in conjunction with mailing of an 8-week supply of 7, 14 or 21 mg nicotine patch therapy (contingent upon baseline smoking rate). The initial four calls were structured to include in sequence: 1) rapport-building, the evocation of change talk, and rate reduction at the first contact; 2) NRT use, the management of smoking-related triggers, and discussion of quit date; 3) post-quit problem solving, management of withdrawal symptoms, and short-term relapse prevention; and 4) long-term relapse prevention planning. Contingent upon randomization, re-engagement of those not abstinent at the follow-up at 3 months comprised either repetition of the initial call content or an alternative sequence that omitted establishment of a quit date, but which included: 1) the evocation of change talk, use of NRT, a review of rate reduction strategies, and encouragement to reduce daily cigarettes by at least 25%; 2) NRT use, the management of smoking-related triggers, and a recommended further 25% reduction in daily cigarettes; and 3) review of strategies for sustained rate reduction and preparation for a quit attempt when ready.16. This protocol was approved by the Institutional Review Board (IRB) of the 59th Medical Wing, Joint Base San Antonio-Lackland, Texas.Counselors participating in the study were research specialists hired by the University of Tennessee Health Science Center who received extensive training both in the intervention components elaborated above and in motivational interviewing, including a two-day workshop and weekly skills-training. Calls were audio-recorded and subject to random fidelity checks which formed the basis for each counselor’s monthly individual feedback concerning intervention delivery and their interactions with Quitline callers. Initial motivational interviewing proficiency and subsequent fidelity checks were accomplished with reference to the Motivational Interviewing Treatment Integrity Code (MITI 3.1.1)13. The current study was a secondary analysis comparing smoking cessation rates at 12 months among those who quit or were still smoking at 3 months (some of whom elected to re-engage with Quitline treatment), thus sample size calculations for this secondary analysis are not required.Detailed power calculations for the primary analysis of the parent study were described in Little et al.17 was defined as the probability of assignment to treatment condition based upon each participant’s set of observed risk factors potentially influencing the decision to re-engage at the check-in at 3 months. The propensity score for re-engagement was created using a multivariable logistic regression model which included participants’ demographic variables , the first three-month treatment adherence (measured as number of counseling sessions attended and NRT use), and additional NRT or other medications use. The propensity score-adjusted logistic regression model was used to assess differences in past-7-day smoking abstinence rates at follow-up at 12 months between the treatment groups. The C- index18 was used as a measure of overall model predictive discrimination, defined in this study as the ability to differentiate participants who quit tobacco by the follow-up at 12 months from those who did not. Bonferroni multiple comparison adjustment was applied to control the type I error rate due to multiple comparisons. The overall significance level was specified at 0.05. All analyses were performed using SAS 9.419.To reduce potential treatment selection bias  and control for the pretreatment (i.e. before the second-phase treatment) imbalances on participants’ characteristics, propensity score methods were developed to minimize or eliminate selection bias/confounding so that the distributions of the observed pretreatment characteristics were similar across the different treatment groups at the follow-up at 3 months. Propensity scoreOf 490 (79.8%) participants contacted at 3 months following a standard smoking cessation intervention, 226 (46.1%) reported abstinence and 264 (53.9%) were still smoking following an initial quit attempt . Of 264 Comparisons of demographic and tobacco use characteristics by smoking status at 3 months are presented in The final propensity score-weighted logistic regression model demonstrated higher odds of past-7-day abstinence at the follow-up at 12 months for those who were abstinent at 3 months compared to those in the re-engaged group  and compared to the group who declined to re-engage  . NotablyFor our analyses, we assumed that data not present at the follow-up at 12 months were missing at random (MAR). Only 33 of 490 participants at follow-up at 3 months were lost to follow-up at 12 months (about a 6.7% attrition rate for the second-phase treatment) . A propeIn the current study, we evaluated the impact of proactive re-engagement on the performance of a tobacco Quitline, defined as past-7-day point prevalence at 12 months following the initial round of treatment. At follow-up at 3 months, 46.1% of participants had quit smoking and 50.8% of those who had not quit smoking were willing to re-engage in treatment. At follow-up at 12 months, 23.8% of re-engaged participants were abstinent, resulting in an overall study crude quit rate of 46.4%.20, and we had anticipated that using proactive counseling to re-engage callers, whose initial quit attempt had failed, would improve cessation outcomes. Though effective in producing a meaningful number of additional quits, re-engagement was less successful than anticipated at improving cessation at follow-up at 12 months. We underestimated the rate at which Quitline callers would decline the opportunity to re-engage, and it is conceivable that a statistically significant treatment effect for re-engagement would have emerged had we achieved adequate statistical power.Such performance exceeds that associated with most multi-component, face-to-face smoking cessation interventions. The typical quit rate for Quitline interventions is 33%21 have estimated that each smoker generates, on average, an additional $2056 in healthcare expenses annually. Thus, the 30 quits we enabled through re-engagement may have saved the Military Health System up to $62000 in the year following the study period. The value of this strategy is predicated upon an assumption that these callers would have continued smoking, had they not been given the opportunity to re-engage with treatment. Under such an assumption, overall Quitline performance would have attenuated by 6.6% in absence of re-engagement, and from this perspective the strategy appears to have resulted in a beneficial effect on the overall performance of the Quitline. The utility of re-engagement is further reinforced by our observation that callers who were still smoking at the check-in at 3 months but declined re-engagement, had an estimated quit rate 4.3% lower at 12 months than those who re-engaged.Our observation that 24% of participants who agreed to re-engage were abstinent at 12 months supports the utility of proactive re-engagement for the 53.9% of participants who were still smoking three months following their initial quit attempt. Berman et al.Results from a comparison of callers who re-engaged with those who had achieved abstinence by the follow-up at 3 months were striking. We had anticipated that the re-engaged group’s receipt of additional treatment would render their cessation rate roughly commensurate with that observed for those who had achieved abstinence in the first three months of the study. Interestingly, those who were abstinent at the check-in at 3 months were nearly 10 times as likely as those who re-engaged to be abstinent at follow-up at 3 months. Propensity score adjustment allowed us to balance for confounding covariates, including baseline participant characteristics, severity of tobacco dependence, and the use of nicotine replacement therapy and completion of counseling during the study period. The fact that early abstinence outperformed re-engagement, even after the propensity score weighting adjustment, introduces the possibility that Quitlines wishing to incorporate re-engagement should consider investing in services  which maximize the probability of a quit within the first three months of treatment. These findings also suggest that future studies may benefit from evaluation of a broader array of re-engagement strategies tailored to specific groups of smokers.22. A Phase-Based Model23 for the structuring of tobacco cessation efforts seeks to optimize smokers’ prospects for a successful quit across a spectrum spanning from initial motivation, into preparation for behavior change, transversing the cessation attempt itself, and extending ultimately through the potential for relapse and recovery. Each of our participants was motivated to quit, having elected to call the Quitline and subsequently engaged with an intervention organized around the principles of motivational interviewing, and all callers participated in preparatory counseling broadly consistent with that outlined by Piper et al.24 . Emerging evidence for an additive effect of maintenance counseling in conjunction with extended use of NRT suggests that we may have achieved a better outcome for those who ultimately were not abstinent at three months during the ‘cessation’ phase – albeit at higher cost – had we interspersed the two months following the core intervention with bi-weekly phone contacts25. Latent class analysis has been used to successfully identify smokers for whom supplemental support may be indicated26, introducing the possibility that additional phone contacts could, in the future, be extended with increasing precision to smokers in need.Early success emerges as especially important in light of previous research demonstrating the diminishing likelihood of a successful quit following a failed attempt in the preceding year. Critically, this phenomenon strengthens with multiple such failed attempts at abstinence over the same period27, only a subset of especially motivated persons elects to engage with Quitline counseling on any given month28. It is thus critical that Quitline services be organized and executed in a manner which maximizes callers’ potential for successful tobacco cessation. Taken in context of the existing literature, our results raise the possibility that the right amount of Quitline treatment cannot be defined by a set number of calls irrespective of the individual, and should instead be understood in terms of each caller’s needs as anticipated by empirically-derived predictors of treatment response 24 and informed by their manifest response to treatment in the days and weeks following their target quit date. We extended an invitation to re-engage at three months, and this may have been as many as 90 days too late, depending upon the caller.While nearly 70% of smokers wish to quit29, in addition to proactive engagement of callers following the initial Quitline contact, which thereby limited the influence of extraneous variables on callers’ ongoing engagement with the Quitline. Each of our counselors was trained to demonstrable proficiency in motivational interviewing using the MITI16 and received feedback on randomly selected audiotaped Quitline calls throughout the study period. Standardization of training and intervention delivery enabled isolation of variables, including re-engagement status, which were of central interest to the study.Strengths of the present study include treatment conditions featuring counseling and NRT consistent with established Clinical Practice GuidelinesThis study was limited by a smaller than anticipated sample size – fewer participants than anticipated were willing to re-engage – which limited our ability to further investigate the degree to which treatment was less effective for more nicotine-dependent smokers, specifically. Also noteworthy is the exploratory nature of the analyses, residing within a larger trial specifically designed to evaluate the relative merits of three distinct re-engagement strategies. Consequently, what is, for the present purpose, referred to as ‘re-engagement’ comprises rate reduction, repetition of the earlier intervention, or the caller’s choice between the two, and these alternatives appear not to be commensurately effective. Caller tobacco use status also was ascertained by self-report , rather than empirically by means of salivary cotinine sampling. Finally, because we defined the one-year outcome as 12 months from completion of the first Quitline contact, we are limited in our ability to make strong inferences concerning the durability of quitting resulting from re-engagement, which occurred only 9 months in advance of the follow-up at 12 months.Our results suggest that, while re-engagement appears to be of benefit to those smokers for whom an initial round of treatment was unsuccessful, persons who succeed in achieving abstinence within that initial round of treatment are substantially more likely to be quit at 12 months relative to their re-engaged counterparts. Consequently, future research should seek to set on empirical footing a framework through which to tailor the amount and timing of supplemental tobacco cessation services inside the three months immediately following each caller’s target quit date, as success in this respect stands to increase considerably the corresponding quit rate at 12 months.Click here for additional data file.


Following a SARS-CoV-2 infection, many individuals suffer from post-COVID-19 syndrome. It makes them unable to proceed with common everyday activities due to weakness, memory lapses, pain, dyspnea and other unspecific physical complaints. Several investigators could demonstrate that the SARS-CoV-2 related spike glycoprotein (SGP) attaches not only to ACE-2 receptors but also shows DNA sections highly affine to nicotinic acetylcholine receptors (nAChRs). The nAChR is the principal structure of cholinergic neuromodulation and is responsible for coordinated neuronal network interaction. Non-intrinsic viral nAChR attachment compromises integrative interneuronal communication substantially. This explains the cognitive, neuromuscular and mood impairment, as well as the vegetative symptoms, characterizing post-COVID-19 syndrome. The agonist ligand nicotine shows an up to 30-fold higher affinity to nACHRs than acetylcholine (ACh). We therefore hypothesize that this molecule could displace the virus from nAChR attachment and pave the way for unimpaired cholinergic signal transmission. Treating several individuals suffering from post-COVID-19 syndrome with a nicotine patch application, we witnessed improvements ranging from immediate and substantial to complete remission in a matter of days.The online version contains supplementary material available at 10.1186/s42234-023-00104-7. The coronavirus SARS-CoV-2 evoked pandemic calamity and took a toll on the world’s population, with a death toll of 6 million victims within 30 months  and Bungarus genera, the G-ectodomains of three Rabies lyssavirus (formerly Rabies virus) (RABV) strains  which shows significant sequence homology with the neurotoxin homolog NL1, one of the many snake venom toxins interacting with nAChRs , acetylcholine (ACh) is released mainly from projection neurons (PN), which innervate distal areas, and local interneurons interspersing their cellular targets. PNs are found in several nuclei, including the medial habenula, pedunculopontine and laterodorsal tegmental areas, as well as the basal forebrain complex and the medial septum  Wess  or ionotIn contrast, nAChR activation leads to fast and non-selective opening of membrane-bound, excitatory cation channels , the viral blockade of these receptors leads to a sharp deterioration of cholinergic neuromodulation  for the natural agonist (ACh) compared to nicotine  and 3 males  who suffered from numerous symptoms indicative of post-COVID-19 syndrome following a PCR-confirmed SARS-CoV-2 infection with a subsequent mild course of disease. The patients described weakness, dyspnea, sleep disturbances, dizziness, complete ageusia and anosmia, along with a variety of other symptoms. Except for the youngest, the patients were not able to continue activities of daily life compared to the period before the SARS-CoV-2 infection. As these multiple unspecific symptoms had not improved over a certain time period without signs of acute COVID-19 infection, they visited our outpatient clinic.After meticulously explaining the hypothesis described above, as well as the expected effects of nicotine and possible side effects, the patients were advised to apply a standard nicotine patch. Since all included individuals were nicotine-naïve persons, they were instructed to use the lowest available dosage 7.5 mg/24 h) and to administer the patch once daily (in the morning). All patients followed these instructions, except for the 41-year-old patient; he mistakenly purchased the patches in a higher dosage (15 mg/24 h) than recommended. In all cases, we asked patients to register their symptoms starting 4 days before applying the nicotine patch  for seven days on November 23rd, 2021. In the days leading up to nicotine application, weakness was recorded in the range of the two highest possible levels (levels four to five), and anosmia and ageusia were reported at the highest possible level (level five). During nicotine-based treatment, recovery from weakness was most rapid; a daily reduction in symptom severity was achieved, allowing level two to be reached on day three of treatment and maintained for an additional three days. Level one was reported on day six, and by day nine, the patient reported being weakness-free  by the patient. We interpreted this symptom as a classic side effect of nicotine; it did not require further intervention.th, 2020, having undergone an acute SARS-CoV-2 infection confirmed by a positive PCR test on November 21st, 2020; moderate symptoms included fever, reduction in smell and taste, loss of appetite, headache, pain in the limbs, reduced memory, lack of drive and rhinitis, as well as neck, limb and back pain. The acute infection phase lasted until December 5th, 2020 when convalescence was confirmed via a negative PCR test. From that time onwards, she had numerous symptoms, such as chronic fatigue (level four), loss of smell and taste (level one), marked difficulty concentrating (level four), headache (level four) and considerable exercise intolerance (level four). Information, education, informed consent and nicotine therapy were given to the otherwise healthy, nicotine-naïve patient as described above (7.5 mg/24 h) for 6 days.The 31-year-old female patient presented to our outpatient clinic on December 17Starting on day two after the initiation of nicotine therapy, the patient reported a reduction in fatigue of one level per day; fatigue was completely reversed by day four. From the sixth day onwards, however, the patient experienced a recurrence of fatigue to a lesser extent (level three), which then progressed as follows: day thirteen (level two), day twenty (level one) and day twenty-three (level zero). The patient’s reduced retentiveness was perceived as very high (level four) before and at the beginning of treatment; it dropped significantly from the third day following nicotine administration (level two) and was no longer perceptible from the fourth day onward. In the same manner, the ability to concentrate was impaired until the concentration performance perceived before SARS-CoV-2 was regained from the fourth day after the initiation of nicotine therapy.Similarly, the markedly impaired exercise tolerance (level four) dropped significantly on day three (level one), becoming unreproducible on day four, but rising again slightly on days five (level two) and six (level three), only to fall continuously thereafter from day eight. From the twenty-fourth day after nicotine application, the patient reported full recovery of her physical performance.Starting on day two, the patient experienced a very unpleasant feeling of tightness in the thoracic region, which was reported to be undiminished (levels three to five) until day thirteen after the start of nicotine therapy; it decreased continuously from then on  until complete remission was achieved on day twenty-three. We attributed this symptom, which began directly with the start of nicotine administration, to a side effect of the active substance, nicotine. The patient considered these symptoms to be associated with nicotine, as well, which is why she elected to stop the nicotine therapy on day six as opposed to continuing until day seven as we had recommended. This decision was due to the otherwise very good symptom remission until the fourth day of nicotine administration . In a telephone interview after approximately six months, the patient confirmed that there had been no recurrence of her symptoms.th, 2022, having been ill from a moderate SARS-CoV-2 infection ; his symptoms had been weakness, fever, chills, headache, coughing attacks, loss of sense of smell and taste, shortness of breath, exercise intolerance, permanent fatigue and a pronounced feeling of weakness.A 41-year-old male patient visited our outpatient clinic on December 20At the time of presentation, he was suffering from a variety of persistent symptoms: chronic fatigue (level three), dyspnea (level three), anosmia (level five), loss of taste (level five), muscle weakness (level four), difficulty sleeping (level one) and headaches (level two). The nicotine-naïve patient agreed to the off-label use of nicotine patches in the manner previously described.Unfortunately, the patient did not administer the recommended dose of 7.5 mg/24 h but mistakenly doubled it (15 mg/24 h), which led to intolerable vomiting (level five) and diarrhea (level five) within seven hours; the patient discontinued the therapy after ten hours.Despite the cessation of nicotine use, chronic fatigue decreased significantly on day two after nicotine use (stage two), continued to decrease on day three (stage one) and was no longer detectable on day four. Similar to the cases described previously, the symptoms of anosmia and loss of taste showed a rather protracted yet continuously declining course; the reduction of these two symptoms occurred simultaneously in this particular case. On the eleventh day after nicotine application, there was a slight reduction in both symptoms (level four), which then dropped to level three on the twelfth and thirteenth days. After a decrease to level two on the fourteenth day, the patient was able to fully perceive all smell and taste qualities on the fifteenth day.The mild sleep problems (level one) reported by the patient permanently disappeared on the first day following nicotine patch application (level zero). Regarding the feeling of weakness, the patient described a daily reduction by one level, reaching level one on the third day; this lasted for one more day, reaching permanent elimination from day five onwards (level zero). The residual headache reported by the patient (level two) was completely resolved by day two after nicotine administration (level zero). This patient also reported no recurrence of the described symptoms after an interval of six months.st, 2022, stating that he had been suffering from persistent complaints including chronic fatigue (level two), shortness of breath (level two), difficulty concentrating (level one), difficulty sleeping (level three), mood swings (level two), chest tightness (level two) and palpitations (level two) since a PCR-positive SARS-CoV-2 infection on March 3rd, 2022.A 52-year-old male patient presented to our outpatient clinic on April 1After excluding persistent acute SARS-CoV-2 infection via a negative PCR test, we informed the patient of the apparent presence of post-COVID-19 syndrome. The nicotine-naïve and otherwise healthy patient agreed to a therapy trial using a nicotine patch (7.5 mg/24 h). Without consultation and contrary to our recommendations, the patient increased the nicotine dose to 15 mg/24 h on the third day of therapy; he then stopped the application completely on the fourth day after nearly complete symptom remission. He stated that he had not experienced any side effects of the nicotine application, which is why he doubted the efficacy and therefore applied two nicotine patches at 7.5 mg/24 h each starting on day three.Chronic fatigue increased slightly on the second day of nicotine application (level three) and then decreased significantly on day five (level one). On the sixth day, fatigue was no longer reported. The complaints of breathlessness dropped on day five (level one) and were no longer reported from day seven onwards (level zero). The patient reported that the concentration difficulties had ceased on the first day of nicotine use (level zero). Difficulty sleeping and mood swings persisted until the fourth day (level two) and were no longer detectable from the fifth day onwards (level zero).The perceived chest tightness (level two) dropped on day five (level one) and was no longer detectable on the following day (level zero). The intermittent palpitations (level one), which were perceived as mild, had not occurred for two days once nicotine usage had begun. On day three of therapy, the patient once again noticed episodes of palpitations (level two), which were recorded at this level for two days. On day three of nicotine administration, this discomfort (level one) dropped and was gone completely on day four. We interpreted this recurrence of palpitations as a classic side effect of nicotine; it stopped spontaneously and did not require further treatment. In an interview three months after the intervention, the patient confirmed that he had not noticed any recurrence of the symptoms that had brought about his initial consultation.Each of the four presented cases showed significant alleviation of their persistent symptoms; improvement was reached either immediately following nicotine patch application or in rapid succession after treatment began. There were clear differences in the patterns and the time spans for symptom relief among the four cases. It is also worth noting that the course of symptom improvement in each of the presented cases was independent of their drastically different lengths and progression prior to nicotine therapy.In each case, signs of exhaustion such as fatigue, weakness, breathlessness and exercise intolerance improved rapidly and across the board following nicotine exposure (at the very latest by day six). In cases with impairment or loss of the senses of taste and smell, improvement was observed over a longer period, with complete restoration of these senses over anywhere from thirteen to sixteen days.The perceived tightness in the chest, as well as palpitations, were described as clear (level two) and ended on the second day after their occurrence (day three after the start of nicotine administration). Regarding the chest tightness described in case two, the patient stated that she had not felt any reduction in performance; this made a coronary and/or vascular nature of the problem seem unrealistic from the author’s point of view. The patient documented complete recovery from this side effect on the twenty-second day after having started nicotine therapy.The amount of virally blocked AChR can vary greatly among individuals, which certainly influences the course of symptom reduction; this may require individualized nicotine doses and application intervals to suit the individual patients. All cases described were observed in non-smokers. We observed severe side effects only in the patient who had mistakenly applied double the recommended dosage of nicotine. Severe nausea in connection with sweating and repeated vomiting are classic side effects of nicotine and are why this patient discontinued the therapy. With continuous nicotine abstinence after this dosage misstep, all COVID-19-related symptoms previously documented by the patient decreased until restitutio ad integrum was achieved on the fifteenth day after nicotine application. From the author's point of view, this development supports the underlying hypothesis, as SARS-CoV-2 displacement from nAChR binding locations should follow a certain dose–response relationship.In the case of the patient who independently doubled the recommended dose starting on day three (case four), we suspect that the administration of the recommended dose may have led to a habituation reaction that helped lessen potential side effects from the higher dosage.The release of the SARS-CoV-2 virus from nAChR receptors can lead to short-term viremia with signs of acute SARS-CoV-2 infection when starting nicotine therapy; however, this viral load should be neutralized within a short period of time by the humoral component of the immune system due to SARS-CoV-2 antibodies formed during the acute phase of infection  of ACh and nicotine (Changeux et al. The studies conducted by Changeux et al.  and AlexInvestigations that follow such a quantitative approach would be necessary to objectify the hypothesis put forward by the author. Considering the substantial burden on health care systems and the expected high incidence of post-COVID-19 syndrome, coupled with the currently extraordinarily long courses of therapy and their unpredictable results, this treatment approach is worth investigating further. The low therapeutic effort of a nicotine patch and the easily controllable side effects of a well-known substance seem to justify carrying out larger, double-blinded and randomized investigations based on the described hypothesis. Considering that the previous attempts at explaining the etiopathogenesis of long-haul COVID, and developing appropriate therapeutic efforts, have been speculative, it is worth looking into this hypothesis more closely. Nicotinic AChRs and specifically the a7nAChR play a major role in the vagus nerve regulation of inflammation through the efferent arm of the inflammatory reflex (Wang et al. Post-COVID-19 syndrome is well explained in its pathogenesis and clinical manifestation, with cholinergic neuromodulation disorder due to partial or complete blockage of nicotinic acetylcholine receptors by the SARS-CoV-2 virus playing a potentially important role. In all four of the cases we studied, transcutaneous use of nicotine led to a near immediate improvement in symptoms and rapid restitutio ad integrum. The course of symptom improvement was as distinct as the clinical presentation of post-COVID-19 syndrome in each patient. The ease of implementation and the good controllability of the minor side effects make randomized, double-blinded studies to investigate this treatment option more closely seem feasible. Based on the results of this case study, this treatment option—using nicotine patches to combat long-haul COVID—seems far superior to the time-consuming, often underwhelming or disappointing, costly and complex rehabilitation measures currently available to these patients.Additional file 1.Additional file 2.Additional file 3.Additional file 4.


Image-based cell sorting is essential in biological and biomedical research. The sorted cells can be used for downstream analysis to expand our knowledge of cell-to-cell differences. We previously demonstrated a user-friendly image-activated microfluidic cell sorting technique using an optimized and fast deep learning algorithm. Real-time isolation of cells was carried out using this technique with an inverted microscope. In this study, we devised a recently upgraded sorting system. The cell sorting techniques shown on the microscope were implemented as a real system. Several new features were added to make it easier for the users to conduct the real-time sorting of cells or particles. The newly added features are as follows: (1) a high-resolution linear piezo-stage is used to obtain in-focus images of the fast-flowing cells; (2) an LED strobe light was incorporated to minimize the motion blur of fast-flowing cells; and (3) a vertical syringe pump setup was used to prevent the cell sedimentation. The sorting performance of the upgraded system was demonstrated through the real-time sorting of fluorescent polystyrene beads. The sorter achieved a 99.4% sorting purity for 15  The isolation of interested cells from the heterogeneous populations is essential in biological and biomedical research ,7,8,9,10Conventional cell isolation techniques, for example, fluorescence-activated cell sorting (FACS), rely on the light scattering intensity and fluorescent bio-markers. These techniques offer several limitations ,4,11. ScThe advent of image-based cell isolation techniques addresses the limitations of the conventional cell isolation techniques by providing information-rich cell images ,5,6,7,12However, the development of a deep learning-enabled image-based FACS-like sorting system is challenging because of the short span  A high-resolution linear piezo-stage to obtain focused cell images, (2) an LED strobe light to acquire the blur-free image of fast-flowing cells, and (3) a vertical syringe pump setup to overcome the cell sedimentation. The obtained results can afford solutions to the practical problems related to cell sorting experiments.Polydimethylsiloxane (PDMS)  sorting chip was fabricated using soft lithography. The 5:1 PDMS mold was cured at 80 ing chip . Subsequple flow .TM 1 mL Syringe and 10 mL Syringe, BD Plastics, UK). The sample and sheath fluids are injected into the microfluidic sorting device using three syringe pumps at constant flow rates  and sends them to the image processing thread with a capture time. Then, in the image processing thread, a background image is subtracted from the acquired microscopic image, such that only cells remain in the image. A region of interest (ROI) is established for a microchannel to reduce the processing time. Upon the completion of this step, a Gaussian blur is applied to remove the noise in the given image, and then thresholding generates a binary image of the cells. The application of the morphological opening to the binary image removes noise. Contours are located to identify each cell in the image, and then the cell images are cropped from the original color image. These cropped images are used to determine the cell types through a convolutional neural network (CNN) with NVIDIA TensorRT implementation in a classification thread, and the coordinates of the centroids of the cells are used for multiple cell tracking with a hard-coded tracking algorithm. A bounding box and trajectory for each cell are drawn on an original color image.To prepare the training dataset for the convolutional neural network (CNN), unsigned 8-bit 50 × 50 × 3-pixel images of fluorescent polystyrene beads of 15 ResNet18  coded wiThe real-time cell sorting mechanism used in the upgraded system  is identat 100 V . An AntiThe upgraded system uses a higher performance multi-core processor  and graphic processing unit  as compared to the previous system . This reAcquiring in-focus cell images is very important to separate the target cells from two samples of similar cell sizes with a high sorting purity. For the same cell, different cell images were taken by changing the distance between the objective lens and the 3D-focused flowing cells . FurtherAcquiring blur-free images of the fast-flowing cells without sacrificing imaging sensitivity is also important and challenging. In the previous system, the blur-free cell images were obtained by decreasing the exposure time of the Imaging Source camera. This leads to images with low sensitivity. Conversely, in the upgraded system, microscopic images of fast-flowing cells were obtained by using strong LED strobe light with a duration of 10 l images B. Considng cells . By furtTM, a biocompatible density gradient medium, can be used to prevent cell sedimentation [TM is mixed with a sample fluid, it was observed that clear images of the hydrodynamically focused sample stream were obtained by increasing the concentration of OptiPrepTM  is determined by Stokes’ law  to he fluid , and (3)entation . HowevertiPrepTM . This leTM. During the five consecutive bead sorting experiments, the throughput decreased slowly at about 20 eps (Therefore, in the upgraded system, the syringe pump was set vertically right above the sorting chip. Thus, the Tygon tube was set vertically straight to avoid particle sedimentation without using OptiPrept 20 eps . This obReal-time sorting of fluorescent polystyrene beads was conducted to evaluate the performance of the upgraded system. The 15 erformed . The sorThe sorting results were analyzed by manually counting the numbers of sorted and unsorted beads using a fluorescence microscope . AccordiOur previous user-friendly image-activated microfluidic cell sorting technique successfully demonstrated the real-time sorting of beads and cells with a high sorting purity. We herein present a recently upgraded user-friendly image-activated cell sorting system. A high-resolution linear piezo-stage and LED strobe light were newly added to the upgraded system in order to obtain in-focus blur-free images of the fast-flowing cells. In addition, a syringe pump for sample injection was vertically installed to prevent the particle sedimentation. Several experiments confirmed that the sorting throughput of the upgraded system slowly decreased over time. The proposed system can be easily implemented using commercially available items. However, the moving speed of the flowing cells is limited to less than half of the horizontal field of view divided by the frame interval to measure the moving speed of cells using a CMOS camera. Real-time bead sorting also demonstrated that the upgraded system achieved 99.4% sorting purity and 94.4% yield for 15


As the proportion of older people increases, it is necessary to evaluate their health and well-being to identify measures to promote healthy ageing. Moreover, the COVID-19 pandemic has impacted older adults’ health- not just through the infection itself, but also due to infection protection ordinances.LAB60+ is a population-based cross-sectional study investigating, among other things, the physical and mental health of older adults. Residents of Dresden aged 60 years and older were invited to participate in the first half of 2021. Participants answered questions on their habits, health status and wellbeing, using, among others, the Short Form-8 Health Survey and the WHO wellbeing index.2399 people participated in the study (40% response). Participants assessed their physical health similar to the German population. The most common chronic conditions were hypertension (54%), chronic pain (32%) and osteoarthritis (31%). 42% of the participants were overweight and 20% were obese. One-fifth did not engage in physical activity: this number increased with age and decreased socioeconomic status. Participants reported lower levels of wellbeing compared to the German population (58 vs. 67 pts.). One-third had higher levels of depressiveness and half reported an increase in their experienced loneliness due to the pandemic. 34% participated in risky alcohol consumption, but it did not markedly change during the pandemic. The greatest negative impact of the pandemic on health behaviors was physical activity: more than one-third exercised less compared to the time before the pandemic.Physical health was comparable to the German population, while depressivity was higher, perhaps due to the pandemic. Age-appropriate interventions should especially target an increase in physical activity. It is important to take measures to reduce the possible negative effects of the pandemic, such as increased loneliness or reduced physical activity.• This is the first study on health and wellbeing on older adults (60+ years) in the city of Dresden, Germany.• The COVID-19 pandemic had a high impact on older adults’ physical activity and loneliness.


Falls and mobility deficits are common in people with multiple sclerosis (PwMS) across all levels of clinical disability. However, functional mobility observed in supervised settings may not reflect daily life which may impact assessments of fall risk and impairment in the clinic. To investigate this further, we compared the utility of sensor-based performance metrics from sit-stand transitions during daily life and a structured task to inform fall risk and impairment in PwMS. Thirty-seven PwMS instrumented with wearable sensors (thigh and chest) completed supervised 30-second chair stand tests (30CST) and underwent two days of instrumented daily life monitoring. Performance metrics were computed for sit-stand transitions during daily life and 30CSTs. EDSS sub scores and fall history were used to dichotomize participants into groups: pyramidal/no pyramidal impairment, sensory/no sensory impairment and high/low fall risk. The ability of performance metrics to discriminate between groups was assessed using the area under the curve (AUC). The feature that best discriminated between high and low fall risk was a chest acceleration measurement from the supervised instrumented 30CST (AUC = 0.89). Only chest features indicated sensory impairment, however the task was different between supervised and daily life. The metric that best discriminated pyramidal impairment was a chest-derived feature (AUC = 0.89) from supervised 30CSTs. The highest AUC from daily life was observed in faller classification with the average sit-stand time (0.81). While characterizing sit-stand performance during daily life may yield insights into fall risk and may be performed without a clinic visit, there remains value to conducting supervised functional assessments to provide the best classification performance between the investigated impairments in this sample. I.Multiple sclerosis is an immune-mediated disease that causes inflammation, demyelination and neurodegeneration of the central nervous system leading to compromised nerve signaling between the brain and body. The disruption in signal transmission of the sensorimotor systems lead to a high incidence of balance deficits, mobility problems, and elevated fall risk in people with multiple sclerosis (PwMS) , 2] acr acr2] acWhile there is ample evidence that interventions across a spectrum of disability levels lead to improvements in balance, physical functioning and decreased fall risk –13], es, es13], Thus, we posit that there may be benefits to both supervised and unsupervised assessments of functional mobility incorporating wearables. To our knowledge no previous study has directly compared supervised and unsupervised performance during a structured task to a similar task performed during daily life to investigate specific contributions to impairment and fall risk. In this study we identified sit-stand and stand-sit transitions performed during daily life during two days of unsupervised monitoring and compared performance metrics derived from wearable sensors to those from a supervised and unsupervised 30-second chair stand test (30CST). Specifically, we sought to understand how performance in each context may inform fall risk, sensory and pyramidal impairment.II.A.Forty PwMS  were recruited from the University of Vermont Medical Center Multiple Sclerosis Center and dichotomized by fall status . Fallers were identified with a questionnaire asking if they had sustained a fall in the previous 6-months where a fall was defined “as an event where you unintentionally came to rest on the ground or a lower level”.Participants were instrumented with two inertial sensors  adhered directly to the skin; one sensor was located on the midpoint of the right thigh approximately aligned with the femur and the second sensor was located on the chest located approximately one inch distal to the sternal notch. The sensors recorded triaxial accelerometer data  while participants performed one trial of the 30CST in which they completed sit-to-stand transitions from a 17-inch chair as quickly and safely as they felt comfortable with arms crossed over their chest. Participants completed standardized outcome measures related to fall risk , 32] in in32] inB.Participants completed approximately two days of daily life unsupervised monitoring immediately following the supervised session. Prior to leaving the laboratory new sensors (sampling rate 62.5 Hz) were placed on the right thigh and chest in the same location and a 30-second static standing calibration trial was performed. The participants were provided with a smartphone and oriented to an application that interfaced with the MC10 sensors  to facilitate unsupervised data collection. The sensors are waterproof thus participants wore the sensors continuously during the unsupervised period and all data were stored in the sensors’ local memory. Accelerometer data were uploaded to a secure MC10 cloud-based database once the sensors were returned via mail, and the data were downloaded to a local server for processing. During unsupervised monitoring participants were asked to complete bi-hourly 30CSTs (timeframe 07:00 to 21:00) and an alarm was enabled on the smartphone at the requested task completion times to facilitate adherence. Study personnel provided a handout with instructions and reviewed the 30CST technique which included employing the same technique as performed during the supervised session, the type of chair to use and how the chair should be positioned against a stable surface for safety.C.The raw accelerometer data for all 30CSTs (supervised and unsupervised) were processed using a fully automated Matlab algorithm . The algorithm used only the thigh accelerometer signal to delineate the sit-to-stand (si-st) and stand-to-sit (st-si) phases of each 30CST repetition and has been previously detailed , 38]. F. F38]. FD.Performance metrics extracted for the supervised session included temporal and acceleration-related features from each of the triaxial acceleration components. Sit and stand events extracted from the CC component of the thigh acceleration were used to compute si-st and st-si duration times for each transition. Then temporal features were computed which included the average, median, maximum, and minimum si-st and st-si transition times across all repetitions of one 30CST as well as the number of 30CST repetitions performed . Triaxial  peak and minimum thigh and chest accelerations were extracted within the first and second half of each 30CST transition  from rawE.Participants had to complete a minimum of four 30CST assessments during the unsupervised period for inclusion in the analysis for statistical analysis. The raw accelerometer data for each 30CST was processed using the same algorithm as described for the supervised 30CST to delineate each 30CST assessment into si-st and st-si components. The minimum, maximum and average si-st and st-si times were computed for each 30CST. As there were varying numbers of 30CST assessments completed by each participant, the performance metrics reflected summary statistics across all the 30CST assessments performed  and included: overall average and median of si-st time across all 30CSTs, overall average and median of st-si time across all 30CSTs, average 30CST performance (number of repetitions), average of the maximum and minimum si-st and st-si times, median of the maximum si-st and st-si times, 5th percentile si-st and st-si times across all 30CSTs, 95th percentile si-st and st-si times across all 30CSTs, and median of the average si-st and st-si times . Similarly, the acceleration-related metrics reflected summary statistics across all 30CSTs for each component  for the thigh and chest for the first and second halves of each si-st and st-sit transition . For example, for the AP component of the thigh this included the average and median of the peak acceleration, average and median of the minimum acceleration and the 5th and 95th percentile acceleration value across all 30CSTs.F.the CC-component LPF signal had to pass through 0.5 g ,the CC-component LPF signal had to demonstrate >0.5 g of total range  and,STS duration had to be less than 4.5 seconds , 41]..41].The model was then leveraged to identify all sitting bouts completed by participants during the 48-hour free-living period see . All sitAny potential window not meeting these criteria were discarded from further analysis. Approximately one-third of the participants’ data were visually inspected to ensure the automated algorithm was correctly discarding windows that did not contain a transition.G.The minimum, maximum, average, median and coefficient of variation (CV) si-st and st-si times were computed across all sit-stand and stand-sit transitions identified during daily life . Triaxial  peak and minimum thigh and chest accelerations were extracted within the first and second half of each sit-stand and stand-sit transition similar to the 30CST data. The average, median and CV of the peak and minimum accelerations as well as the 95th percentile and 5th percentile acceleration values across all sit-stand and stand-sit transitions in the first and second halves of the sit-stand and stand-sit transitions were computed and used as the performance metrics for the analysis .H.Independent sample Student’s t-tests and Wilcoxon Rank Sum Tests  were used to evaluate differences between fallers and non-fallers, non-pyramidal and pyramidal impairment and sensory and non-sensory impairment for all clinical outcome measures and accelerometer-derived thigh and chest performance metrics with a threshold of p<0.05. Then for all accelerometer-derived metrics demonstrating statistically significant differences between groups, non-parametric receiver operating characteristics (ROC) analyses with age-adjusted covariates were used to classify fall risk status (high/low), no pyramidal vs pyramidal impairment (NPI/PI) and no sensory vs sensory impairment (NSI/SI). The area under the receiver operator characteristic (ROC) curve (AUC) was used to quantify each performance metrics’ ability to distinguish between groups and enables a quantitative comparison across all three conditions  . We rankIII.A.B.nd half of the sit-stand transition (Avg of Min CC Accel Si-St (2), AUC = 0.89, p = 0.003, d = 0.96, A total of 9 features  including chest and thigh derived performance features  were statistically significantly different  discriminated between participants with and without pyramidal impairment with AUC > 0.70  and p<0.D.Only chest derived performance features discriminated between participants with and without sensory impairment . The feaIV.In this study we directly compared the ability of sit-stand and stand-sit performance metrics to discriminate impairment and fall risk in PwMS during instrumented structured and unstructured tasks in supervised settings and daily life. Our findings are consistent with recent findings in gait analysis that group discrimination is optimized by different features and is context dependent . HoweverThe instrumented 30CST as a functional assessment to identify specific modes of impairment could lead to improved ability to target and individualize therapeutic interventions prior to a fall occurring. The original (non-instrumented) 30CST has been historically associated with lower extremity functional strength in older adults –43], th, th43], Given the constraints of relatively short and infrequent clinical visits to observe and quantify behavior that translate to increased fall risk, we expected that performance metrics during daily life would outperform supervised performance metrics. We hypothesized that daily life metrics would capture the inherent variability associated with task performance, for example divided attention, fluctuating symptoms, and environmental factors. While sit-stand time discriminated fall risk with a relatively high AUC  assessments and unsupervised (daily life) monitoring of sit-stand and stand-sit transitions. The findings of this study suggest that to optimally identify fallers, pyramidal impairment, and sensory impairment, it is best to use an instrumented 30CST performed in-clinic based on this cohort of PwMS and feature set. Unsupervised sit-stand and stand-sit transitions were still able to seperate groups with high performance in classification and group difference implying that this approach could still be useful for quantifying patient symptoms outside of the clinic. Additionally, variability measures of daily life performance did not strongly distinguish between groups. Thus, when supervised monitoring is not available, a shorter unsupervised monitoring period may suffice.


Alphaherpesvirinae subfamily of Herpesviridae. Establishment of its productive infection and progression of disease pathologies depend largely on successful release of virions from the virus-producing cells. HSV-1 is known to exploit many host factors for its release. Recent studies have shown that heparanase (HPSE) is one such host enzyme that is recruited for this purpose. It is an endoglycosidase that cleaves heparan sulfate (HS) from the surface of infected cells. HS is a virus attachment coreceptor that is commonly found on cell surfaces as HS proteoglycans e.g., syndecan-1 (SDC-1). The current model suggests that HSV-1 during the late stage of infection upregulates HPSE, which in turn enhances viral release by removing the virus-trapping HS moieties. In addition to its role in directly enabling viral release, HPSE accelerates the shedding of HS-containing ectodomains of SDC-1, which enhances HSV-1 release via a similar mechanism by upregulating CREB3 and COPII proteins. This review outlines the role of HPSE and SDC-1 as newly assigned host factors that facilitate HSV-1 release during a lytic infection cycle.Herpes Simplex Virus 1 (HSV-1) is a neurotropic human virus that belongs to the  Alphaherpesvirinae subfamily of Herpesviridae. It is a ubiquitous pathogen that affects 50–90% of the global population [Herpes simplex virus 1 (HSV-1) is a highly infectious, neurotropic human pathogen. It is a double stranded DNA virus that belongs to the pulation . The pripulation , but to The establishment of a successful infection and progression of HSV-1 pathology is largely dependent on the release of progeny virions from infected cells. The lytic cycle of HSV-1 in a host cell is represented by several key steps, namely, attachment of HSV-1 to a host cell, fusion of its envelope with the plasma membrane, entry of viral capsid into the cytosol, migration of the capsid to the nuclear membrane followed by the delivery of viral genetic material into the host nucleus, DNA replication and viral gene expression, assembly, and release of the virions from the infected cell . HSV-1 eThe family of herpesviruses has more than 100 members with their hosts ranging from oysters to human beings. HSV-1 is a member of the alphaherpesvirus subfamily, which is comprised of neurotropic viruses known to cause multiple diseases such as mucocutaneous lesions, ocular keratitis, skin infections as well as meningitis and encephalitis . These eIn their quest to complete their lytic cycle, herpesviruses attempt to completely control host cell machinery causing cell lysis at the end of the infection. HSV-1, being an enveloped virus, penetrates into the cell by inducing fusion of the viral envelope with the host cell membrane ,18,19. DAfter entry, HSV-1 releases its genetic material into the cytoplasm of the cell that ultimately reaches the nucleus for replication. Successful entry of the virus into the host cell also marks the halt of normal cellular functions and host immune responses to support the initiation of the viral replication process. To reach the nucleus, the capsid is driven by cellular motors on microtubules and delivered to the nuclear pores for uncoating of the viral genome ,24 AfterFollowing viral gene expression and genome replication, the packaging of HSV-1 genetic material into preformed capsids in the nucleus ensues . The pacOn completion of genome packaging and capsid assembly inside the nucleus, the subsequent nucleocapsids must leave the boundaries of the nuclear envelope but face the obstacle of being surrounded by a phospholipid bilayer. The mechanism for crossing the bilayer is a multistep process. The first step of nuclear exit is envelopment at the inner nuclear membrane and then fusion with the outer nuclear membrane ,31.The fThe release of HSV-1 from infected cells is known to be affected by different host and viral factors with HSV-1 exploiting different host factors to facilitate its release. Among the major factors known to hinder the release of progeny virions are the same HSPGs that initially facilitated viral entry. The HS moieties need to be cleaved off for viral release. HSV-1 exploits the host machinery by selectively upregulating HPSE, a HS-degrading enzyme of the host to facilitate its release. Recent findings have demonstrated that HPSE acts as a molecular switch between a virus-permissive ‘attachment mode’ of host cells to a virus-deterring ‘detachment mode’ . In addiHPSE is an endo-β-D-endoglycosidase that has a crucial role in the degradation and remodeling of the extracellular matrix (ECM). It is the only mammalian enzyme that has the potential to cleave HS moieties ,33. The HPSE is selectively upregulated in HSV-1 infected cells. This was established when attempts to develop novel interventions against HSV-1 using anti-HS peptides . resulteIncreased expression of HPSE coupled with a decline in the surface levels of HS indicates that a viral or host factor is likely responsible. One such mechanism is proposed by Hadigal et al.  which stHPSE mediates multiple non-enzymatic activities by stimulating intracellular signaling to promote phosphorylation of various proteins such as Akt, ERK, p38, and Src ,44. ReceThe identification of viral factors implicated in infection induced HPSE upregulation is important. HSV-1-infected cell protein (ICP) 34.5 has been involved in governing interferon responses and viral release ,47 HSV-1HSV-1 is known to modulate numerous host factors to improve its replication and release from the host cells. Recently, Yadavalli et al.  reportedSyndecans are a small family of transmembrane proteoglycans that network with a variety of ligands through their core proteins and glycosaminoglycan (GAG) chains, which includes HS . They arHSV-1 entry is facilitated via interaction of its glycoproteins, specifically gB and gC, with HS moieties present on HSPGs. Cell surface syndecan expression increases during viral entry . HoweverThere exists a possibility that enhanced SDC-1 shedding is due to an increase in its synthesis in the infected cells, as shown in HeLa cells by Bacsa et al. , but thiRecently, multiple reports have established the relation between HPSE and SDC-1  are a family of endopeptidases with 23 members that are sheddases capable of cleaving syndecans from the cellular surface . Past stvhs) RNase plays a key role in this process. The vhs protein is responsible for efficiently cleaving host mRNAs [Although it has been specifically shown with the HCE cell line that MMP-1 and MMP-3 transcripts increase during viral entry, the increase is likely time dependent. There are multiple reports suggesting that MMP transcripts decrease with HSV-1 infection during early infection time points i.e., up to 8 hours post infection, and the virion host shutoff  are some of the reported compounds involved in enhanced SDC-1 shedding ,64. EGF Specifically, the authors treated HCE and HeLa cells with PMA (phorbol 12-myristate 13-acetate), a known shedding agonist of SDC-1, thrombin (protease), and a growth factor (EGF). They found that the agonists accelerated SDC-1 shedding in both HeLa and HCE cells. They also demonstrated that increased SDC-1 expression in the supernatant was due to its loss from the cell surface. Their plaque assay results showed that PMA, thrombin, and EGF treated cells resulted in an enhanced HSV-1 release and increased number of extracellular viruses. Thus, they were able to demonstrate that agonist induced SDC-1 shedding leads to more viral release.Recent studies in the herpesvirus pathogenesis field have identified important roles for HPSE and SDC-1 in HSV-1 release. The data emphasize that HPSE is a key host factor that directly removes HS during viral release, and indirectly, regulates b-catenin and CREB3 activities as well as SDC-1 ectodomain shedding to promote viral release. In parallel, SDC-1 ectodomain can also be shed in response to other stimuli, promoting viral exit. The HPSE/syndecan axis has the potential to delineate host mechanisms that contribute directly to the release of several different pathogenic human viruses that use HS for attachment and entry into their host cells. While the host factors promoting HSV-1 egress are being increasingly well studied, imperative challenges persist, including characterizing any cell type-specific differences in virus release, the impact of HPSE activity and syndecan shedding in preventing viral entry into nearby cells, and the direct significance of HPSE and syndecan in cell-to-cell spread of HSV-1 in animal models. The aftermath of the highly pathogenic environment created by enhanced HPSE release and syndecan shedding is also poorly understood. In addition, the other members of HPSE and syndecan axis, for instance MMPs, also require additional studies for their roles in HSV-1 release. These and other developments in viral release mechanisms will help identify the best strategies for curbing HSV-1 release for therapeutic benefits and delineating the pathogenic roles of HPSE and syndecan during HSV-1 infection.