N‐(chlorothio)phthalimide (Cl‐S‐Phth) and arylzinc reagents afforded the corresponding Ar‐S‐Phth compounds. Subsequently, the S(II) atom was selectively oxidized to distinct fluorinated sulfur(VI) compounds under mild conditions. Slight modifications on the oxidation protocol permit the chemoselective installation of 1, 3, or 4 fluorine atoms at the S(VI) center, affording the corresponding Ar‐SO2F, Ar‐SOF3, and Ar‐SF4Cl. Of notice, this strategy enables the effective introduction of the rare and underexplored ‐SOF3 moiety into various (hetero)aryl groups. Reactivity studies demonstrate that such elusive Ar‐SOF3 can be utilized as a linchpin for the synthesis of highly coveted aryl sulfonimidoyl fluorides (Ar‐SO(NR)F).A convenient protocol to selectively access various arylsulfur(VI) fluorides from commercially available aryl halides in a divergent fashion is presented. Firstly, a novel sulfenylation reaction with the electrophilic  A divergent protocol for the synthesis of various (hetero)aryl S(VI) fluorides from the same starting material is reported. The protocol proceeds through a novel metal‐free Ar−S bond formation, followed by a mild oxidation. The careful tuning of the oxidation conditions dictates the chemoselectivity of the oxidation step. Tetrafluoro‐λ6‐sulfanyl chlorides (Ar‐SF4Cl) represent a class of compounds of high fluorination level (level 4), with 4 fluorines at the same S(VI) atom.en route to the highest level of fluorination (level 5): Ar‐SF5 compounds.[3).2 and NaF at −115 °C in CFCl3, obtaining a remarkable 20 % of Ph‐SOF3  represent a large portion of the molecular functionalities encountered in organic chemistry. From the venerable electrophilic properties of sulfonyl chloridesompounds.7c, 8 3 Figure . This co2NH2).2.4Cl mainly relies on the oxidation of the corresponding aryl disulfides.One of the main drawbacks associated to the synthesis of fluorinated arylsulfur(VI) compounds is the limited number of unified strategies using the same aryl synthon, that lead to different fluorination levels. For example, synthesis of aryl sulfonyl fluorides has mainly relied on the anion exchange from the parent arylsulfonyl chlorides.5a, 11from the same starting material, herein we present a strategy that enables access to Ar‐SOF3, Ar‐SO2F, Ar‐SF4Cl and Ar‐S(O)(NR)F, from the corresponding commercially available aryl halides , Ar‐SF4Cl (path b) and the underexplored Ar‐SOF3 (path c) in high chemoselectivity and yields. This protocol benefits from a high functional group tolerance, accommodating a variety of N‐containing heterocycles. Furthermore, addition of a primary amine into the Ar‐SOF3 in the presence of base affords the corresponding Ar‐S(O)(NR)F.With the aim of providing a unified approach to synthesize various fluorinated arylsulfur(VI) compounds s Figure . The met2PhN‐(arylsulfenyl)phthalimides (Ar‐S‐Phth) attracted our attention due to their thermal stability upon storage despite the weak S−N bond.2 or SO2Cl2.N‐(chlorothio)phthalimide2, Table 3) in good yields. It is interesting to note the chemoselectivity in favor of the displacement of the Cl over the good leaving group phthalimide. These compounds are indeed bench‐stable, easy to handle and the S atom is attached to a good leaving group (Phth), which is crucial in the forthcoming modification (vide infra).At the onset of this project, we envisaged that a divergent access to fluorinated arylsulfur(VI) compounds from aryl halides should rely on the construction of a common precursor: an “active” arylsulfur(II). Moreover, the method should be facile, robust and with a high degree of functional group tolerance. Inspired by previous work on electrophilic sulfur reagents3) in hand, we set out to explore the second step of the synthetic route. Inspired by the remarkable findings recently reported by Pitts, Santschi and Togni en route to fluorinated aryl‐S(VI),IV IV 3 (4 a),2F (5 a) and PhSF4Cl (6 a). The formation of 4 a together with unselective formation of 5 a and 6 a, suggested that access to different levels of fluorination at S(VI) could be within reach. A short optimization revealed that TCICA (9 equiv), KF (16 equiv) and TFA  afforded 4 a (Table 4 a:5 a=96:4). In the 19F NMR, a typical AX2 pattern appears at 64.5 ppm J(F=157.9 Hz) and 100.6 ppm F=157.9 Hz) with an integral ratio of 1:2, which is in agreement with a trigonal bipyramidal geometry (TBP) of the S(VI) where two fluorine atoms are placed in the apical positions.5.3.With the Ar‐S‐Phth precursors  and also provides a safer and synthetically useful platform to produce a variety of Ar‐SOF3 compounds (vide infra). Yet, such compounds exhibit extremely high reactivity and rapidly evolve into Ph‐SO2F upon exposure to traces of H2O, which made isolation attempts and crystallographic analysis completely unsuccessful.The high yields obtained for 4 a significantly decreased  as the main product (Table 2F (5 a) was obtained in almost quantitative yield (95 %) and selectivity (4 a:5 a=2:98). When the amount of oxidant and fluoride was increased,  and catalytic amount of TFA was used, the corresponding Ph‐SF4Cl (6 a) was obtained in high yield  commencing from the same starting material by simply tuning the oxidation conditions.Interestingly, this methodology is significantly sensitive to the amount and type of additives. When the loading of TFA was decreased, both yield and selectivity of ld Table , entry 93 was explored . On the contrary, the presence of electron‐donating groups such as methyl (4 e–4 f) and methoxy (4 g) significantly affected the reactivity, especially when at the ortho‐position . This is mainly due to the low conversion of the Ar‐S‐Phth to Ar‐SOF3. With the aim of having Ar‐SOF3 as potential scaffolds for organic synthesis, it is essential that the oxidative fluorination tolerates other functional groups. Indeed, this protocol permits the presence of nitro (4 h), nitrile (4 k), ester (4 l) and trifluoromethyl (4 i–4 j) as well as other aromatic (4 m and 4 n) groups. Remarkably, some heterocyclic halides were able to be transformed to the corresponding sulfinyl trifluoride. For example, unsubstituted pyridine (4 o), halogenated pyridines (4 p–4 q) and a pyridine bearing a trifluoromethyl group (4 r) were obtained in moderate to good yields. Of notice, the sulfinyl trifluoride could also be obtained for the challenging 2‐pyrimidine (4 s) albeit in low yields (15 %). Unfortunately, other heterocycles with pyrimidinyl‐ or thienyl groups resulted in no conversion toward 4 t or 4 u, respectively. When low‐yield or no conversion is obtained for heterocyclic substrates, higher amounts of Ar‐SF4Cl and Ar‐SO2F were observed. Monitoring the formation of 4 d by 19F NMR, indicated that Ar‐SOF is formed very rapidly at the initial stages of the reaction in the presence of 2 equiv of TFA. This intermediate is then oxidized further and after halogen exchange it affords 4 d (SI for details).Under the optimized conditions in Table d Scheme . Using a2F compounds (5). Of importance is that either electron‐withdrawing  or electron‐donating groups (5 d–5 e) presented similar reactivity, with yields ranging from 53 % to 81 %. Furthermore, aryl groups having the reactive site between two bulky methyl‐ groups did not affect the reactivity, as shown by the 58 % yield of 5 e.N‐basic functionalities did not affect the outcome of the reaction as highlighted by the high yields obtained by pyridines 5 k and 5 l.As shown in Table 4Cl (6) was obtained selectively from (hetero)aryl halides  than aryl halides bearing electron‐donating groups (6 c–d). More importantly, heterocyclic substrates were smoothly converted, as exemplified by the good yields obtained using various pyridines  and pyrimidines (6 j).When increasing the loading of TCICA and KF in combination with catalytic amounts of TFA, ArSF3 compounds and their ability to rapidly engage with traces of H2O to forge Ar‐SO2F, we envisaged that synthesis of the important sulfonimidoyl fluorides (ArS(O)(NR)F) should be within reach when primary amines are used. Indeed, when 4 was reacted with a primary amine (7) in the presence of Et3N, smooth conversion to the corresponding sulfonimidoyl fluorides (8) was observed (Scheme 4 d with different anilines led to 8 a–8 c in high yields (63–70 %). Of particular importance is the tolerance of the styrenyl moiety in 8 c. Benzylamines or aliphatic primary amines also boded well with this protocol, affording good yields of the corresponding sulfonimidoyl fluorides (8 d–8 f).Based on the high electrophilicity exhibited by Ar‐SOF8 g–8 j). Due to the chiral nature of the S(VI) center in 8, compounds 8 h and 8 i were obtained as a mixture of diastereoisomers, with a d.r. of approximately 1:1, judging by the two different 19F NMR signal for each isomer.4 did not affect the reactivity dramatically, as judged by the good yields of 8 with different aryl (8 k–8 n) and heteroaryl (8 o–8 p) groups.Additionally, the steric hindrance on the amine partner was also explored. Gratifyingly, di‐ or tri‐ substituted amines did not pose any difficulties, affording the desired compounds in good yields  compound, namely the Ar‐SO(NR)F. Finally, the synthetic versatility of this protocol is represented by the >50 examples provided overall, including Lewis‐basic containing heterocycles. The operational simplicity of the protocol might become appealing for practitioners, and is envisaged to find applications in the rapid assembly of aryl S(VI) compounds.In conclusion, we have developed a protocol that enables access to four different fluorinated aryl S(VI) compounds from the same aryl precursor. The first step introduces the S atom selectively into the (hetero)aryl group by virtue of a novel reaction between an ArZnX and the electrophilic Cl‐S‐Phth. The second step consists in a chemoselective oxidation of the S(II) atom. Slight modification of the oxidation step leads to chemoselective synthesis of various fluorinated S(VI) compounds: Ar‐SOFThe authors declare no conflict of interest.As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer reviewed and may be re‐organized for online delivery, but are not copy‐edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors.SupplementaryClick here for additional data file.


Gait and balance impairments are common in neurological diseases, including stroke, and negatively affect patients’ quality of life. Improving balance and gait are among the main goals of rehabilitation. Rehabilitation is mainly performed in clinics, which lack context specificity; therefore, training in the patient’s home environment is preferable. In the last decade, developed rehabilitation technologies such as virtual reality and augmented reality (AR) have enabled gait and balance training outside clinics. Here, we propose a new method for gait rehabilitation in persons who have had a stroke in which mobile AR technology and a sensor-based motion capture system are combined to provide fine-grained feedback on gait performance in real time.The aims of this study were (1) to investigate manipulation of the gait pattern of persons who have had a stroke based on virtual augmentation during overground walking compared to walking without AR performance feedback and (2) to investigate the usability of the AR system.We developed the ARISE  system, in which we combined a development version of HoloLens 2 smart glasses (Microsoft Corporation) with a sensor-based motion capture system. One patient with chronic minor gait impairment poststroke completed clinical gait assessments and an AR parkour course with patient-centered performance gait feedback. The movement kinematics during gait as well as the usability and safety of the system were evaluated.The patient changed his gait pattern during AR parkour compared to the pattern observed during the clinical gait assessments. He recognized the virtual objects and ranked the usability of the ARISE system as excellent. In addition, the patient stated that the system would complement his standard gait therapy. Except for the symptom of exhilaration, no adverse events occurred.This project provided the first evidence of gait adaptation during overground walking based on real-time feedback through visual and auditory augmentation. The system has potential to provide gait and balance rehabilitation outside the clinic. This initial investigation of AR rehabilitation may aid the development and investigation of new gait and balance therapies. Many neurological diseases lead to impairments of gait and balance . ApproxiTherefore, improving gait and balance is one of the main goals of stroke rehabilitation. Repetitive practice is an essential ingredient of established evidence-based interventions  such as Considering the importance of performance feedback for motor skill learning , AR combHere, we propose a new method for gait and balance rehabilitation in patients who have had a stroke that has potential to provide challenging and personalized gait and balance therapy with auditory and visual performance feedback based on gait kinematics in an environment that is adjusted to the patients’ needs. We developed the Augmented Reality for gait Impairments after StrokE (ARISE) system, in which we combined a development version of a head-mounted system for real-time visual and auditory feedback and a commercially available sensor-based motion capture system. Subsequently, we evaluated the usability of the AR feedback prototype in a chronic stroke subject with minor gait and balance impairments. We hypothesized that this system is more capable of modifying gait kinematics than walking without the system.Ethical clearance to execute the experiment with the presented subject was provided by the Cantonal Ethics Commission of the Canton of Zurich, Switzerland (BASEC-Nr. Req-2019-00758). The participant received information about the experiments. Written informed consent in accord with the Declaration of Helsinki was obtained from the participant prior to performing the experiments.The patient was a right-handed man aged 74 years who had a right-hemispheric ischemic stroke in the thalamus, capsula interna, and right temporal lobe 7 years before participating in the experiment. Acutely after stroke, he had mild motor deficits in the left leg . At the time of this experiment, he had minor limitations of sitting and standing balance ; he also had mild limitations in motor function  and strength  of the affected left side. The patient walked independently without a walking aid , with a comfortable walking speed of 1.0 m/s and a step length of 0.56 meters as measured by the 10-Meter Walk Test. The patient had slight risk of falling (Dynamic Gait Index 19/24). He reported numbness in the feet and a feeling of wearing socks when he was not. In addition, a mild cognitive impairment was present .The ARISE system consisted of two essential components: an optical see-through head-mounted display (OST-HMD) and a sensor-based motion capture system (We identified the HoloLens 2 (Microsoft Corporation) as the most suitable OST-HMD, as it provides a wider field of view (43×29 degrees) compared to other devices and thus can display more virtual objects in a real-world environment. In addition, the HoloLens 2 is able to track head movements with an inertial measurement unit and has an intuitive hand-interaction user interface that is enabled through fully articulated hand tracking. The OST-HMD was used to visualize the AR parkour course  A-C. TheIn addition, the OST-HMD provided visual and auditive feedback based on real-time gait kinematic performance. An inertial measurement unit–based motion capture system, the Xsens MVN (Xsens Technologies B.V.), was chosen to track the kinematics of the lower limbs during gait. We strapped seven inertial measurement units on the pelvis and the lower extremity of the patient . The XseThe HoloLens 2 and Xsens systems were integrated by streaming movement performance data to the OST-HMD through a user datagram protocol client. To adjust for translational drift of the motion capture system in the ARISE system, the captured motion data were rigidly attached to the pose of the HoloLens 2. To synchronize the forward directions of both systems, we performed a short calibration phase where the user was required to align his head with his hips and feet. Once the 2 systems were coupled, we were able to provide subtle positive reinforcement of successful knee flexion (>45 degrees) by playing an ambient bird song sound through the HMD.To increase the difficulty of the tasks the subject was asked to complete, simple math calculations were presented visually  of the HoloLens 2 should be improved to increase the usability of the system. The field of view forced the patient to bend forward; this can induce adverse events, such as near-falls or neck pain, when using the system over longer periods of time.Through the coupling of the OST-HMD and the motion capture system, the patient perceived auditive feedback based on the kinematics of the knee (flexion angle). The OST-HMD provided feedback in the form of bird songs and a knowledge of results display. When the patient was given multimodal feedback, he changed his gait pattern. This is in line with previous results ,20. A trThe current AR parkour course has a size of 14×4 meters; therefore, it requires a large open space to operate. In future versions, the ARISE system will be able to generate a parkour course with an adaptable area depending on the local environment. This will provide the advantages of flexibility in choosing the test grounds and a variety of parkour designs. In future research, the impacts of different virtual obstacles or even obstacle themes  on the gait kinematics can be evaluated. Due to the high mobility of all involved components, our system can be used virtually anywhere, both indoors and outdoors and with different surfaces and distractors. The mobility of the system is also ensured through the web interface of the OST-HMD and the motion capture system, which allows remote access. Therefore, a telerehabilitation approach is conceivable.The present ARISE system is a prototype, and it requires technical support for setup and calibration. Therefore, a reduced sensor set and simplified calibration procedure would increase its usability and applicability. Furthermore, movement sensors are limited by orientation drift when they are used over a long period of time . In thisThe ARISE system combines an adjustable and personalized training environment with a feedback and monitoring system for gait and balance rehabilitation. This case study showed that use of the system by patients who have had a stroke and who have mild gait and balance impairments is promising. Compared to existing AR systems, the system utilizes the real physical environment to place virtual obstacles that are immediately and intuitively treated as real-world objects. This system can be used to provide feedback on a variety of gait parameters and to implement personalized  gait training environments.


Ankle injuries are among the most common injuries in sport and daily life. However, for their recovery, it is important for patients to perform rehabilitation exercises. These exercises are usually done with a therapist’s guidance to help strengthen the patient’s ankle joint and restore its range of motion. However, in order to share the load with therapists so that they can offer assistance to more patients, and to provide an efficient and safe way for patients to perform ankle rehabilitation exercises, we propose a framework that integrates learning techniques with a 3-PRS parallel robot, acting together as an ankle rehabilitation device. In this paper, we propose to use passive rehabilitation exercises for dorsiflexion/plantar flexion and inversion/eversion ankle movements. The therapist is needed in the first stage to design the exercise with the patient by teaching the robot intuitively through learning from demonstration. We then propose a learning control scheme based on dynamic movement primitives and iterative learning control, which takes the designed exercise trajectory as a demonstration (an input) together with the recorded forces in order to reproduce the exercise with the patient for a number of repetitions defined by the therapist. During the execution, our approach monitors the sensed forces and adapts the trajectory by adding the necessary offsets to the original trajectory to reduce its range without modifying the original trajectory and subsequently reducing the measured forces. After a predefined number of repetitions, the algorithm restores the range gradually, until the patient is able to perform the originally designed exercise. We validate the proposed framework with both real experiments and simulation using a Simulink model of the rehabilitation parallel robot that has been developed in our lab. Nowadays, robots are present in many different areas. For instance, rehabilitation devices can be used as therapy aids, e.g., for the development of adjustable devices for assisting different sensorimotor functions ,2, in scRehabilitation robotics brings scientists from human–robot interaction and biomedical engineering together with clinicians and therapists in order to develop the necessary technologies to improve patients’ quality of life. The main goals here are : (i) to In order to examine the patients’ level of adaptability while using rehabilitation devices, techniques such as passive exercise, active assisted exercise, active resistive exercise, active constrained exercise, and adaptive exercise  can be uAs mentioned above, the purpose of rehabilitation robotics is to design a device that mimics the work done by patient and physiotherapist during a rehabilitation session. In this paper, we propose to use a PR as a rehabilitation device. PRs have a high load capacity, stiffness, precision, compact structure, excellent energy/weight ratio, and provide better feedback control . InteresRegarding ankle rehabilitation systems, there are devices that generate ankle movements for neurological rehabilitation ,26,27 orThe characteristics of the exercises to be performed in each case are very different. For that reason, a reconfigurable device is introduced in order to adapt to each patient’s range of ankle motion . This roFor more recent approaches for ankle rehabilitation using PRs, readers may refer to ,40,41,42The main motivation behind this work is to improve the therapeutic resources that can be applied to people with locomotive disorders and to offer better rehabilitation results by providing different types of exercises. In this context, it is important to develop an appropriate low-cost mechanical solution that is able to adapt different rehabilitation exercises to different patients. Unlike the aforementioned rehabilitation devices, the proposed system not only has a suitable kinematic and dynamic design but also provides a control system equipped with a learning algorithm that monitors movements and forces that arise during the execution of the exercise and that can adapt to patients’ needs using a new Learning from Demonstration (LfD) framework . LfD is In this paper, we propose to exploit LfD to learn passive rehabilitation exercises and adapt them based on the patient’s needs by integrating Dynamic Movement Primitives (DMPs)  and Iter-Exploitation of force sensing in an LfD framework for ankle rehabilitation using a PR that integrates ILC and DMPs to learn different passive exercises and adapt them autonomously;-Implementation of soft emergency stopping due to the integration of DMP phase-stopping in the emergency button control loop in order to provide soft and smooth stopping;-Provision of a stability analysis of our learning control;-Provision of a brief review of ankle rehabilitation devices, injuries, and exercises;-Implementation of different experiments in order to validate our control scheme.This paper is an extension of a previous conference paper , where wThe human foot and ankle are composed of 28 bones: tibia, fibula, 7 tarsals, 5 metatarsals, and 14 phalanges. The human ankle joint is a very complex bony structure  that is y-axis, (ii) adduction and abduction movements in the transverse plane that occur around the z-axis, and (iii) inversion and eversion movements in the frontal plane that occur around the x-axis. The ranges and moment requirements are summarized in The ankle joint has rotations in the sagittal, frontal, and transverse planes. Ankle injuries are among the most common injuries in sport and daily life . Ankle sThe first ankle treatment after injury includes Rest, Ice, Compression, and Elevation (RICE) of the affected foot , which sAt present, different techniques are used for ankle rehabilitation; however, not all of them have the same effectiveness. Some techniques require the patient to be an active agent in the rehabilitation process . In thesIn this article, a number of references have been generated to rehabilitate an injured ankle with passive exercises. These passive exercises are used to train dorsiflexion/plantar flexion and inversion/eversion ankle movements. The rehabilitation exercises are performed using a three-PRS  PR, which is described in the following section.A three-df PR is used as a mechanical device for ankle rehabilitation. Its kinematic and dynamic models are explained in the following subsections.The PR has been modeled by means of a set of nine dependent coordinates, as can be seen in Explicit expressions can be obtained for the inverse kinematic problem. Given the location of the mobile platform, so that the position and orientation of the reference system The forward kinematics is solved using a geometric approach, taking into account that the length between any consecutive If we know the active generalized coordinates The velocity problems, both inverse and forward, are based on the following:By multiplying (dot product) both sides of Equation  by uBnPnFinally, taking into account that the parallel robot has three degrees of freedom, it is possible to obtain a relationship between the velocities of the mobile platform and the time derivatives of the roll, pitch, and heave of the reference system attached to the mobile platform and any choice of three of them forming the matrix This equation allows us to solve both the inverse and the forward velocity problems. In a similar way, the expressions for the acceleration can be obtained.As mentioned before, the parallel robot has been modeled through a set of dependent generalized coordinates, considering which the equation of motion will be as follows:ribed in .For control purposes, the generalized internal forces term is not convenient, so it could be canceled by multiplying both terms of Equation  by an orR . Thus, EBy considering the relationship between all the generalized coordinates and the active ones, Equation  can be wIn this section, we introduce our trajectory learning and adaptation algorithm for robots employed in rehabilitation activities. The proposed algorithm is general and can accommodate other robotics applications that involve contact with the environment, such as force-based trajectory tracking.Equation ), which In this section, the patient’s ankle reference exercise trajectory is designed and the robot learning procedure of the rehabilitation trajectory is described. The trajectory is designed by a medical professional, who guides the mobile platform of the PR while the patient’s foot is in the orthopedic boot . This meThe force sensor is located under the orthopedic boot  and, conAt this stage, the exercise reference trajectory is determined. Moreover, patients should be able to repeat the exercise without any danger, because they are doing a customized exercise designed for them. In order to make the exercise more comfortable for patients and reduce the maximum forces (pain) applied to them, the specialist marks a threshold a little below those maximum forces. Thus, patients would be able to repeat the exercise assisted by the PR with less pain. After several repetitions, patients may be able to repeat the reference trajectory perfectly without pain. Afterwards, the specialist would determine whether a new exercise reference trajectory should be designed or whether the treatment should end.In this paper, robot trajectories are encoded by DMPs. They have the ability to slow execution of the trajectory (exercise) down using a phase-stopping mechanism  whenevery is defined by the following nonlinear differential equations Z-transfoEquation ), the apng cycle :24)El=FEl=FZ-traz dependence into transfer functions and signals and substituting Asymptotic stability is assured if Equation , the conWith a proper selection of In this section, we develop different simulation examples as will as real experiments in order to validate the performance of our LfD framework. The trajectories used in these examples were obtained from the real robot by a medical professional guiding the moving platform of the robot, while the patient’s foot is installed in the boot, according to the procedure detailed in ® model. The model accurately imitates the real robot  s. and at time t =  s. The following figures show another application of the DMPs with the rehabilitation robot. In this case, the patient and the medical doctor have an alarm button  perform a clinical study, and (ii) speed-up the exercise execution based on the therapeutic recommendations; for example, when the patient repeats the original exercise, the algorithm starts to speed up the exercise.


Alcohol consumption was divided into non-drinkers and those who drank 2–3 times a month, 1–2 times a week, and ≥3 times a week. Smoking status was categorized as current smokers, past smokers, and non-smokers. The odds of obesity, alcohol consumption, and smoking with Bell’s palsy were analyzed using logistic regression analysis. BMI showed proportionally positive associations with Bell’s palsy . The odds of alcohol consumption with Bell’s palsy were 0.90  for 2–3 times a month, 0.77 (95% CI = 0.69–0.85) for 1–2 times a week, and 0.79 (95% CI = 0.71–0.88) for ≥3 times a week compared to nondrinkers (P < 0.001). Smoking did not show a relationship with the occurrence of Bell’s palsy. Obesity was related to the risk of Bell’s palsy in the population over 40 years old. On the other hand, alcohol consumption was negatively associated with the occurrence of Bell’s palsy.The aim of this study was to investigate the association of body mass index (BMI), alcohol consumption, and smoking status with the occurrence of Bell’s palsy. The Korean National Health Insurance Service-Health Screening Cohort of a ≥ 40-year-old population from 2000–2003 was used. A total of 5,632 Bell’s palsy participants were matched with 22,528 control participants in terms of age, sex, income, region of residence, and past medical histories of hypertension, diabetes, and dyslipidemia. Bell’s palsy was classified by a history of ≥2 diagnoses with ICD-10 code (G510) and steroid treatment. BMI (kg/m Approximately 11.5–53.3 per 100,000 people suffer from Bell’s palsy worldwide2. In Korea, approximately 0.057% of the population is diagnosed annually with Bell’s palsy3. The incidence of Bell’s palsy is not different between the sexes and covers all age populations, with the peak incidence observed in the population aged 15–50 years old5. Because it is diagnosed by exclusion of other organic causes, the exact pathophysiologic causes of Bell’s palsy remain unknown. Instead, several plausible causes have been proposed, including viral infection, autoimmune inflammatory disease, microangiopathic ischemia, and inflammatory neuritis6. Thus, a number of epidemiologic studies have investigated possible predisposing factors of Bell’s palsy, namely, cardiovascular and metabolic factors. Hypertension and diabetes were previously reported to be related to the occurrence of Bell’s palsy7. However, most previous studies were based on a small number of cases and lacked control groups.Bell’s palsy is one of the most common types of facial palsy, accounting for approximately 1 in 65 of lifetime prevalence8. Therefore, these other lifestyle factors could influence the risk of Bell’s palsy via increased cardiovascular and metabolic comorbidities. A previous study reported that obese patients exhibit a poor recovery from Bell’s palsy9. However, no prior studies included a normal control group to evaluate the risk of Bell’s palsy according to BMI. In addition, to the best of our knowledge, there has been no research into the association of lifestyle factors of alcohol consumption and smoking with Bell’s palsy. When PubMed and EMBASE databases were searched for articles with the terms “facial palsy [All Fields]” AND “alcohol”[All Fields], no articles were retrieved.Lifestyle factors including body mass index (BMI), alcohol consumption, and smoking status can influence the risk of chronic disorders such as hypertension and diabetes. For instance, BMI is predictive for the risk of hypertension after adjusting for other variables such as age, ethnicity, marital status, education level, smoking status, alcohol consumption, physical activity, and diabetesWe hypothesized that obesity, alcohol consumption, and smoking could elevate the risk of Bell’s palsy. To test this hypothesis, the matched control groups for age, sex, income, region of residence, and past medical histories of hypertension, diabetes, and dyslipidemia were compared with Bell’s palsy group for the odds of obesity, alcohol consumption, and smoking.The BMI distributions were different between the Bell’s palsy group and the control group P < 0.001, Table , Table 1Compared with normal BMI, underweight subjects showed decreased odds for Bell’s palsy  levels were related to the severity grade of Bell’s palsy 7. The elevated levels of inflammatory cells and inflammatory cytokines in diabetic patients could induce diabetic peripheral facial neuropathy10. No study has shown a relationship between BMI and the onset of Bell’s palsy. However, retrospective studies demonstrated that subjects with obesity demonstrated a lower recovery rate of Bell’s palsy than normal subjects12. In addition, patients with metabolic syndrome showed a lower recovery rate from Bell’s palsy than control subjects13.The adverse cardiovascular and metabolic effects of obesity might increase the risk of Bell’s palsy. Obesity is associated with numerous cardiovascular and metabolic diseases, including hypertension, diabetes, and metabolic syndrome. Because these cardiovascular and metabolic disorders were suggested as risk factors for Bell’s palsy, obesity could indirectly influence the risk of Bell’s palsy due to these cardiovascular and metabolic comorbidities. Several previous studies have reported that the risk of Bell’s palsy is associated with hypertension, diabetes, and metabolic syndromes14. A meta-analysis showed that multiple cardiovascular outcomes of coronary heart disease and stroke were decreased in moderate alcohol consumption groups15. Moderate alcohol consumption has been suggested to induce anti-inflammatory responses related to adenosine receptors, protein kinase C, nitric oxide synthase, and heat shock proteins, thereby resulting in cardioprotective effects16. In addition, alcohol exerted direct neuroprotective effects against ischemic, endotoxin, beta-amyloid, and neuroinflammatory proteins, probably by activating reactive oxygen species, a number of protein kinases, and heat shock proteins17. There has been some evidence supporting the neuroprotective roles of alcohol consumption in epidemiologic studies. For example, cognitive function showed a proportionally positive association with the amount of alcohol consumption in a cross-sectional study18. In summary, these cardiovascular and neural effects of alcohol could have led to the protective effects against Bell’s palsy observed in this study. Because only 21% of participants consumed alcohol ≥1 time per week in our cohort, the relatively moderate frequency of alcohol consumption of ≥1 time per week was used as the reference criterion for alcohol consumption. Thus, the negative effects of higher-frequency alcohol consumption could be masked due to the low threshold for alcohol consumption used in this study.Contrary to our expectation, alcohol consumption was negatively associated with the risk of Bell’s palsy in this study. It is possible that the biased control group may have affected the relationship between alcohol and Bell’s palsy. To minimize the potential selection bias of the control group, selection of the control group was repeated with a novel random number in this study. Results consistent with the low odds of Bell’s palsy with alcohol consumption were still observed when the new control group was used. The neuroprotective and cardioprotective effects of mild to moderate alcohol consumption may be linked to a reduced risk of Bell’s palsy19. Thus, further studies that include a sufficient number of participants who consume alcohol are warranted.In the subgroup analysis according to age and sex, obesity consistently increased the odds of Bell’s palsy. On the other hand, alcohol consumption decreased the odds of Bell’s palsy in men. However, no relationship between alcohol consumption and Bell’s palsy was found in women. The small number of participants with alcohol consumption ≥1 time per week may have weakened the statistical power in the women subgroup  in this study. The participants who did not undergo a health check-up before the index date were excluded.A large, nationwide, population-based cohort was used in the present study. The large number of participants enabled the selection of a sufficient number of control participants matched for age, sex, income, region of residence, and past medical histories. Because this study was based on health claim codes, matching of socioeconomic factors was crucial because these factors determine medical accessibility. In addition, the fidelity of the sample cohort was verified in a previous study21. Thus, the possible protective effect of caffeine consumption on the risk of Bell’s palsy could mediate the negative association between Bell’s palsy and alcohol consumption in this study.Nevertheless, a few limitations should be considered when interpreting the present results. On the one hand, because the diagnosis of Bell’s palsy was based on the ICD-10 codes and treatment histories, subclinical or spontaneous recovery cases were excluded from this study. On the other hand, acute facial palsy other than Bell’s palsy could be included in this study due to incorrect ICD-10 coding. In addition, the severity and treatment responses of Bell’s palsy could not be assessed. Regarding lifestyle factors, recall bias is possible for alcohol consumption and smoking because they were surveyed based on a questionnaire. In addition, the total amount of alcohol consumption and smoking could not be calculated because a categorical questionnaire was used. Finally, although this study considered the lifestyle factors of obesity, smoking, and alcohol consumption, possible confounders such as caffeine consumption still existed. Because caffeine consumption might be associated with alcohol reward or alcohol-seeking behavior, alcohol consumption could be correlated with caffeine consumptionIn conclusion, obesity was associated with higher odds of Bell’s palsy in the ≥40-year-old population. Alcohol consumption ≥1 time per week was related to lower odds of Bell’s palsy than alcohol consumption <1 time per week.The Ethics Committee of Hallym University (2017-I102) approved the use of these data. The study was exempted from the need for written informed consent by the Institutional Review Board. All analyses adhered to the guidelines and regulations of the Ethics Committee of Hallym University.22. This was a nested case-control study. The participants with Bell’s palsy were included in this study . The control subjects who were never diagnosed with Bell’s palsy were randomly selected from the entire population  and 1:4 matched with the Bell’s palsy participants. The matching variables were age group, sex, income group, region of residence, hypertension, diabetes, and dyslipidemia. The index date was defined as the date of diagnosis with Bell’s palsy. The index date of control participants was defined as the identical date of their matched Bell’s palsy participants. Bell’s palsy participants without health check-up data before index data were excluded (n = 439). Resultantly, 5,632 Bell’s palsy participants and 22,528 control participants were enrolled. The latest health check-up data before the index date were analyzed for the Bell’s palsy and control groups  2002–2013 was usedTobacco smoking was defined by current smoking state, duration of smoking, and amount of cigarette smoking (Supplementary Table 2) was categorized as <18.5 (underweight), ≥18.5 to <23 , ≥23 to <25 (overweight), ≥25 to <30 (obese I), and ≥30 (obese II) following WPRO 200023.Drinking alcohol was categorized as frequency and the amount of alcohol consumption . The region of residence was grouped into urban and rural areas.The participants’ prior medical histories were evaluated using ICD-10 codes. Hypertension (I10 and I15), diabetes (E10-E14), and dyslipidemia (E78) were classified based on the number of treatments (≥2) in their medical history.Bell’s palsy was defined using ICD-10 code (G510). We only included participants who were treated for Bell’s palsy ≥1 time with steroid treatment.Chi-square tests were used to compare the general characteristics between Bell’s palsy and control groups.To analyze the odds ratio (OR) of smoking, drinking alcohol, and obesity with Bell’s palsy, conditional logistic regression analysis was used. Models were stratified by age, sex, income, region of residence, hypertension, diabetes, and dyslipidemia. In this analysis, a crude (simple), adjusted model  was used. The 95% confidence interval (CI) was calculated.For the subgroup analyses, we divided the participants according to age and sex . The age threshold for age groups was determined as the median value of the total number of participants.Two-tailed analyses were conducted, and P values less than 0.05 were considered to indicate significance. The results were statistically analyzed using SPSS v. 22.0 .supplement tables.


Downregulation of lnc-GNAT1-1 was observed in cancerous tissues from patients with liver cancer and in liver cancer cell lines, and low expression levels of lnc-GNAT1-1 were related to advanced TNM stage. Lnc-GNAT1-1 knockdown promoted invasion, migration, and proliferation of liver cancer cells and inhibited apoptosis, while lnc-GNAT1-1 upregulation exerted the opposite effects. The expression levels of lnc-GNAT1-1 negatively correlated with in vivo tumor growth in a xenograft nude mouse model. Mechanistic experiments revealed that lnc-GNAT1-1 exerted anti-tumor effects in liver cancer cells by inhibiting EMT. In conclusion, this study suggests that lnc-GNAT1-1 suppresses liver cancer progression by modulating EMT.Recent studies have investigated the modulatory roles of long non-coding RNAs in the onset and progression of liver cancer. The present study aimed to elucidate the role of lnc-GNAT1-1 in liver cancer development and to explore the underlying mechanisms. Quantitative real-time polymerase chain reaction was performed to measure the expression levels of lnc-GNAT1-1 in cancerous tissues from patients with liver cancer and in liver cancer cell lines. The proliferative ability and apoptotic rates of liver cancer cells were measured using the counting kit-8 (CCK-8), colony formation, and flow cytometry assays. The abilities to invade and migrate were measured using Transwell assays. Epithelial–mesenchymal transition (EMT)-related proteins, E-cadherin, N-cadherin, and vimentin, were measured using western blotting. A nude mouse model was injected with xenografts to evaluate tumor growth  Liver cancer was the fourth leading cause of cancer death in 2018 . It was Long non-coding RNAs (lncRNAs), that is, those containing more than 200 nucleotides, are a type of non-coding RNA that regulate the initiation and development of various cancers . SeveralIn vivo studies showed that increasing the expression levels of lnc-GNAT1-1 inhibited the growth of xenograft tumors and that lnc-GNAT1-1 knockdown contributed to cancer development. We also found that lnc-GNAT1-1 exerted anti-tumor effects and may be a new effective therapeutic target for liver cancer.Previous studies have indicated that lnc-GNAT1-1 plays an anti-tumor role in malignancies of the digestive tract, including colorectal  and gastA total of 42 paired normal–cancer liver tissues were obtained during surgery from the same patients. The target specimens were washed in DPEC water, cut using special scissors, and immediately stored in liquid nitrogen until RNA extraction. The diagnosis of liver cancer was confirmed through postoperative pathology and all patients were staged on the basis of the World Health Organization criteria for the classification of liver cancer. Before collecting these specimens, no patient had received anti-tumor therapy. Consent was obtained from all patients. We received approval from the ethics committee of the Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, Guangxi Zhuang Autonomous Region, China.2 and cultured target cells at 37°C. Female BALB/C nude mice (28–35 days old) were provided by the Animal Core Facility  and housed at 25°C under pathogen-free conditions.The normal human liver cell line LO2 and cancerous cell lines QGY-7703, SMMC-7721, Huh7, Hep3B, and GSG7701 were purchased from the Shanghai Cell Bank. Cells were grown in Dulbecco’s modified essential medium containing 10% fetal bovine serum (FBS) and 100 μg/ml penicillin/streptomycin. We used a special incubator containing 5% COTotal RNA was extracted from cancerous tissues of patients with liver cancer and from liver cancer cell lines using TRIzol reagent , following the manufacturer’s protocol. qRT-PCR was performed using SYBR II Premix Taq  according to the manufacturer’s protocol. GAPDH mRNA was used as the internal reference. All experiments were carried out in triplicate. The PCR primers used were designed as follows: lnc-GNAT1-1 forward: 5′-ATGTGTCCCCAGGTTCCTGTT-3′; lnc-GNAT1-1 reverse: 5′-CCCCTGAGGACTTGAGTAGC-3′; GAPDH forward: 5′-CTGGGCTACACTGAGCACC-3′; GAPDH reverse: 5′- AAGTGGTCGTTGAGGGCAATG-3′.The lnc-GNAT1-1 expression vector LV-lnc-GNAT1-1 was provided by Genepharm . The sh-RNA used to silence lnc-GNAT1-1 in liver cancer cell lines and corresponding sh-NC were also purchased from Genepharm. The transfection was carried out using Lipofectamine 2000  according to the manufacturer’s protocol. The QGY-7703 cell line was transfected with LV-lnc-GNAT1-1 to construct cell lines overexpressing lnc-GNAT1-1 and was screened with 2.0 μg/ml puromycin for 14 days. Sh-RNA was transfected into the SMMC-7721 cell line to construct cell lines silencing lnc-GNAT1-1 and these cells were also screened with puromycin (2.0 μg/ml) for 14 days. Fluorescence was measured after 48 h.After transfection, SMMC-7721 and QGY-7703 cells were seeded into 96-well plates containing approximately 1,000 cells per well. Then, we added 10 μl CCK-8 reagent to each well and used a microplate reader  to measure the optical density at 0, 24, 48, 72, and 96 h. This experiment was carried out three times.The transfected SMMC-7721 and QGY-7703 cells were seeded into six-well plates at 500 cells per well and were cultured for 7 days. After visible colonies were formed, 2 ml of 4% paraformaldehyde was added to each well for 15 min. After washing with phosphate-buffered saline (PBS), the wells were stained with a Giemsa stain kit for 30 min. The colonies were counted using an ordinary optical microscope.5 cells per well for 24 h and then harvested and washed twice with PBS. Subsequently, the cells were suspended in 400 μl binding buffer and we added 5 μl propidium iodide and Annexin V-FITC into the cell suspension. Cells were incubated in the dark for 15 min at 37°C. Then, flow cytometry was used to measure the apoptotic rates of these transfected cells.The apoptotic rates of target cells were measured using an FITC/Annexin V Apoptosis Detection Kit  on the basis of the manufacturer’s protocol. SMMC-7721 cells transfected with sh-lnc-GNAT1-1 or LV-lnc-GNAT1-1 were seeded into six-well plates with 4 × 105 cells per well and cultured with serum-free medium to carry out the invasion  and migration assays. Medium containing 20% FBS was added into the lower chamber to serve as a chemoattractant. Using cotton swabs, we removed the non-invading cells and stained invasive or migrated cells with hematoxylin–eosin in the membranes after 24 h incubation.The invasion and migration assays of SMMC-7721 cells transfected with sh-lnc-GNAT1-1 and QGY-7703 cells transfected with LV-lnc-GNAT1-1 were performed using Transwell chambers with 8 μmol/l pore size . The target cells were seeded into the upper chamber at 1 × 10Twenty-four mice were randomly divided into four groups. Sh-NC- or sh-lnc-GNAT-1-transfected SMMC-7721 cells and LV-NC- or LV-lnc-GNAT1-1-transfected QGY-7703 cells were seeded into the subcutaneous area of the necks of the nude mice. The tumors were dissected from the mice and the tumor volumes were measured from 12 to 30 days at 3 day intervals. Tumor volume was calculated as (width × length × height)/2. Approval for all animal experiments was obtained from the Institutional Committee for Animal Research.6 cells per well. Cells were collected and washed with PBS three times. Using RIPA lysis buffer , total protein was extracted from target cells according to the manufacturer’s protocol, and the protein concentration was measured using a bicinchoninic acid protein assay kit (KeyGen BioTech). Subsequently, 30 μg of protein was separated using 12% sodium dodecyl sulfate–polyacrylamide gel electrophoresis at 120 V for 1.5 h. Then, the proteins were transferred onto polyvinylidene difluoride membranes  at 300 mA for 1 h. After blocking the membranes with 5% non-fat skimmed milk for 1.5 h at 20°C, the membranes were incubated with the primary antibodies for 12 h at 4°C. Primary antibodies against GAPDH, N-cadherin, vimentin, and E-cadherin were purchased from Cell Signaling Technology . The next day, the membranes were further incubated with anti-mouse or anti-rabbit secondary antibodies for 1 h at 20°C. Following three washes with TBS-T (10 min per time), expression levels of these proteins were measured using an enhanced chemiluminescence detection kit .Cell suspension was added into 60 mm dishes at 1 × 10t-test was used to analyze significant differences between groups. Significant differences are shown as P < 0.05.All data were analyzed using SPSS 19.0 software  and are expressed as means ± standard deviation. The paired Student’s We carried out qRT-PCR to measure the expression levels of lnc-GNAT1-1 in 42 paired normal–cancer liver tissues. Significant downregulation of lnc-GNAT1-1 was observed in liver cancer tissues . Low lncWe constructed an lnc-GNAT1-1-silencing vector (sh-lnc-GNAT1-1) and used an empty vector for comparison. Expression levels of lnc-GNAT1-1 in the control group were approximately fivefold higher than those in the silencing group . The CCKLV-lnc-GNAT1-1 was transfected into the QGY-7703 liver cancer cell line to upregulate the expression of lnc-GNAT1-1 . The proSMMC-7721 cells transfected with sh-lnc-GNAT1-1 or sh-NC and QGY-7703 cells transfected with LV-lnc-GNAT1-1 or LV-NC were injected into the subcutaneous area of the necks of nude mice. After dissection, tumor volume was measured, and a greater tumor volume was observed in the sh-lnc-GNAT1-1 group than in the control group . SimilarThe expression levels of EMT-related proteins in SMMC-7721 cells were measured using western blotting assays. Downregulated expression levels of E-cadherin and upregulated expression levels of vimentin and N-cadherin were found in the sh-lnc-GNAT1-1 group . UpregulMyc gene, acting as a molecular sponge of various microRNAs (miRNAs) and modulating gene transcription and protein expression . Among these cell lines, lnc-GNAT1-1 showed higher expression levels in SMMC-7721 and lower levels in QGY-7703. We carried out lnc-GNAT1-1 knockdown in SMMC-7721 cells and overexpressed lnc-GNAT1-1 in QGY-7703 cells. Functional assays showed that downregulation of lnc-GNAT1-1 promoted proliferation, invasion, migration, and EMT is crucial for metastasis and invasion of various cancer cells, and upregulation of EMT has been observed in many types of cancer, including liver cancer . E-cadheLnc-GNAT1-1 plays an anti-tumor role in digestive tract cancer development and exerts tumor inhibitory activity to suppress cell proliferation, invasion, and migration and to induce apoptosis in liver cancer cells. We found that lnc-GNAT1-1 inhibited liver cancer progression by regulating EMT. Lnc-GNAT1-1 constitutes a new potential target for improving the quality of life of patients with liver cancer.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Affiliated Hospital of Youjiang Medical University for Nationalities. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by Affiliated Hospital of Youjiang Medical University for Nationalities.JW and JP designed the study and wrote the manuscript. WW, QT, and LL carried out the experiments. ZL, WL, and YL contributed to data analysis. JP had overall responsibility for the research. All authors approved the final manuscript version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The paradigm of how we manage allergic rhinitis is shifting with a growing understanding that it is a complex process, requiring a coordinated effort from healthcare providers and patients. Pharmacists are key members of these integrated care pathways resolving medication-related problems, optimizing regimens, improving adherence and recommending therapies while establishing liaisons between patients and physicians. Community pharmacists are the most accessible healthcare professionals to the public and allergic rhinitis is one of the most common diseases managed by pharmacists. Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines developed over the past 20 years have improved the care of allergic rhinitis patients through an evidence-based, integrated care approach. In this paper, we propose an integrated approach to allergic rhinitis management in community pharmacy following the 2019 ARIA in the pharmacy guidelines. Allergic rhinitis (AR) is the most common form of noninfectious rhinitis and is one of the most common chronic diseases globally ,2,3,4. CThese considerations highlight the importance of effective, evidence-based advice and support being provided to AR patients at the community pharmacy level. The need for greater healthcare professional involvement is particularly important for people with other comorbidities, as AR is frequently associated with asthma and/or conjunctivitis . InsuffiInitiated in 1999, in collaboration with the World Health Organization (WHO) ,24,25, tIt is now critical to put these guidelines into practice in the community pharmacy setting. AR is a complex chronic condition, and implementing clinical practice guidelines for AR management in the community pharmacy is particularly important, as most patients do not consult a medical practitioner when selecting medication for their AR ,20,34. TWith the high level of self-diagnosis, the ability of pharmacists to identify AR is critical. In an Australian study of patients with moderate asthma, 46% of those who also had AR did not have a physician diagnosis . MoreoveAR patients may have multiple nasal symptoms , a large percentage have ocular symptoms  and many patients also have asthma . AlthougOcular symptoms are commonly associated with nasal symptoms in AR  and can The co-existence of poorly controlled rhinitis is associated with poor asthma control in adults, adolescents and children ,43,44 anThe ARIA guidelines propose a classification of AR based on symptom control, quality of life and daily impact as well as duration ,18,20. AComputer-based pharmacy systems have been used globally for decades, but they refer mainly to drug-drug interactions, adverse effects and drug allergy ,47,48,49Symptom severity in AR can be measured using total symptoms score, but this is not a simple test. The visual analogue scale (VAS) is a simple, validated quantitative measure, which can be used in a wide variety of languages and which is responsive to change . The VAS“How much are your nose symptoms bothering you today?”For patients with simultaneous asthma and rhinitis, a previous study conducted in community pharmacies showed that a simple self-assessment questionnaire, the Control of Allergic Rhinitis and Asthma Test (CARAT) , can helMinimizing the impact of AR symptoms is the most important endpoint for the pharmacist, and is used to initiate treatment and maintain appropriate medication/strategies over time. AR symptoms can be used to evaluate the efficacy of the treatment and the patient’s quality of life. By evaluating the impact of AR on day-to-day living, a VAS as per  can be uAR treatment encompasses three different aspects—(1) avoidance of allergen exposure; (2) pharmacotherapy; and (3) allergen-specific immunotherapy (AIT). Pharmacists have an opportunity to deliver patient education in terms of avoidance of allergen exposure, disease information, as well as medication recommendations and use, including nasal medication administration and adherence .(1) With regard to allergen avoidance and environmental control, these strategies can diminish AR symptoms, reducing the need for medication . However(2) When it comes to medications, guidelines consider a range of medications that can be used in the treatment of AR, based on symptom severity, duration and on the impact of symptoms on day-to-day living ,58,59,60(3) AIT helps to reduce the severity of AR symptoms by modifying the immunological response and inducing tolerance to the causative agent . Product1-antihistamines are still largely used by many patients and may be sufficient to control mild AR. The intranasal combination of azelastine and fluticasone propionate is available OTC in New Zealand. Therefore, a broad understanding of the local context should be taken into consideration when recommending treatment.INCS are the most effective treatment for AR, especially in patients with co-existing asthma ,34,61 anStudies reporting interventions targeting nasal inhaler medication administration techniques for AR management are missing. However, the results of bronchial inhaler community-pharmacy interventions used for COPD and asthma have been encouraging ,66,67,68Some INCS reduce eye symptoms as well as nasal symptoms, although the combination of INCS and ocular antihistamines is more effective on both nasal and ocular symptoms ,71,72. MHowever, none of the medications currently used to treat AR can cure this condition and many patients still suffer from uncontrolled disease either because they are not adherent to treatment or medications cannot fully control the disease . As such“How much are your nose symptoms bothering you today?”VAS nose: “How much are your eye symptoms bothering you today?”VAS eyes: Antihistamines and decongestants are frequently used for the treatment of AR . HoweverIntranasal decongestants can be used for short-term and possibly episodic treatment of nasal congestion, but prolonged use may lead to rhinitis medicamentosa (RM) . RM is aA community pharmacy-based study has indicated that overuse of nasal decongestants is prevalent in patients self-medicating persistent rhinitis . TherefoSelf-management plays a particularly important role in the management of AR and is a major challenge for four key reasons—(1) patients often underestimate their symptoms; (2) trivialize their condition; (3) do not adhere to medication; and (4) fail to review treatment to assure that it is working ,55. MoreAR has a significant impact on individuals, creating an important economic burden with substantial direct  and indirect  costs . ApproprmHealth tools have conquered the general public and an enormous number of monitoring applications, that are freely available, user friendly and intuitive are currently being used. Self-management, outside the confines of formal healthcare, but supported on mHealth tools, may ensure that the patient is properly informed and educated about his/her disease and can apply a course of action to ensure optimal outcomes .Mobile technology may help to better understand the low adherence to treatment in allergic diseases and asthma ,91. ManyAdherence is a dynamic phenomenon and optimal adherence is crucial for treatment success. Community pharmacy-led interventions can improve patient adherence to medications and contribute to better COPD and asthma control ,94. To tMASK-air is a very usable app, specific for AR monitoring which has been validated with published results, being implemented in 23 countries and 17 languages ,95,96. TThe integration of all of the stakeholders proposed by ARIA in a common integrated pathway can improve disease outcomes ,28. Give


The number of days of previous statin use for 2 years before the onset of Bell’s palsy was analyzed using conditional logistic regression. Subgroups of age, sex, obesity, smoking, alcohol consumption, total cholesterol, and blood pressure were analyzed for any association between Bell’s palsy and prior statin use. The Bell’s palsy group reported greater statin use than the non-Bell’s palsy group  vs. 74.4(SD = 189.4), p = 0.009). Previous statin use was associated with Bell’s palsy in the crude model . However, this relationship disappeared when the possible covariates were adjusted for in model 2. All subgroups showed no increased odds for Bell’s palsy in previous statin users. We did not find an association between Bell’s palsy and previous statin use in this Korean population aged ≥40 years.We intended to determine the relationship between previous statin use and Bell’s palsy in a large study population receiving statins for the past 2 years. The Korean National Health Insurance Service—Health Screening Cohort data from 2002 to 2015 were collected. Participants with Bell’s palsy ( A growiBell’s palsy is characterized as an acute peripheral facial palsy or paresis without known organic causes (idiopathic) . The preWe hypothesized that the positive relationship between Bell’s palsy and statin use might have been overestimated in the previous study. To assess the impact of statin use on Bell’s palsy, a longer period of statin use was selected (2 years). In addition, a matched non-Bell’s palsy group was compared with a Bell’s palsy group to determine any association with previous statin use. Past medical history, life-style factors, and laboratory measures were adjusted to alleviate possible confounder effects.The ethics committee of Hallym University approved the present study (23 October 2019) and waived the requirement for written informed consent. The Korean National Health Insurance Service–Health Screening Cohort (NHIS-HEALS) data were used in the study . Participants who were treated for the ICD-10 code G510  from 2002 to 2015 were excluded from the non-Bell’s palsy group (n = 4071). Patients who were first diagnosed with this condition between 2002 and 2003 were excluded from the Bell’s palsy group (n = 260). Participants who were previously diagnosed with head trauma (ICD-10 codes S00 to S09) two or more times and underwent head and neck computed tomography evaluations  were excluded . Participants with brain tumors (ICD-10 codes C70 to C72) two or more times were also excluded . One participant from the Bell’s palsy group was excluded owing to missing data on total cholesterol levels. The remaining 480,360 participants in the non-Bell’s palsy group were enrolled for matching. The Bell’s palsy group was matched (1:4) with randomly chosen non-Bell’s palsy participants for age, sex, income, and region of residence. Finally, 3203 patients with Bell’s palsy and 12,812 non-Bell’s palsy participants were included . Patients with Bell’s palsy with a history of two or more treatment events and those who were prescribed steroids were selected, according to our previous studies ,27.Age groups were categorized with five-year intervals. Income groups were classified into five levels. The regions of residence were divided into urban and rural areas ,27.2) groups were collected, as previously described , systolic blood pressure (mmHg), diastolic blood pressure (mmHg), blood glucose (mg/dL), and hemoglobin (g/dL) measured on the health check-up date before the index date. Dyslipidemia was confirmed if participants were treated according to the ICD-10 code (E78) before the index date. For accuracy of diagnosis, dyslipidemia history was assigned to patients with a history of two or more treatment events.The Bell’s palsy group was compared with the non-Bell’s palsy group using Chi-square test for categorical variables and independent t test for continuous variables. The ORs and 95% CIs for statin use per year were calculated for patients with Bell’s palsy by conditional logistic regression. A crude model, model 1 , and model 2  were analyzed. The age, sex, income, and region of residence of the participants were stratified. Age (<60 years and ≥60 years), sex , and obesity status  were sub-grouped and analyzed.p values less than 0.05 were considered significant. The analyses were performed using SAS version 9.4 .Two-tailed analyses were performed, and results with p = 0.009) (p = 0.009). Total cholesterol, SBP, DBP, blood glucose, and hemoglobin levels were different between the groups. The distributions of obesity, alcohol consumption, and CCI score were different between the groups . The Bell’s palsy group showed a higher rate of obesity and higher CCI scores than the control group. The rate of alcohol consumption was higher in the Bell’s palsy group than in the control group.The number of days of statin use was higher in the Bell’s palsy group  vs. 74.4 (SD = 189.4), = 0.009) . In the p = 0.006, p = 0.038 for ≥200 to <240 total cholesterol and adjusted OR = 0.87, 95% CI = 0.77–0.99, p = 0.037 for <100 fasting blood glucose; The Bell’s palsy group demonstrated 1.11 times higher odds of previous statin use in the crude model (95% CI = 1.03–1.19, We explored the relationship between previous statin use and Bell’s palsy in participants who had used statins for 2 years prior to the onset of the disease and found no relation between prior statin use and Bell’s palsy.The results of the present study were consistent across various subgroups. We adjusted the models for laboratory measures and medical history based on health claim codes. In addition, the statin use history of participants during the previous 2 years was investigated to incorporate the potential residual effects of statins. This study helps to fill a gap in the existing research by demonstrating the associations between 2 years of statin use and Bell’s palsy in various subgroup analyses. This is the second and largest study evaluating the relation between statin use and Bell’s palsy.A previous health claim cohort study reported the relationship between 6 months of statin use and Bell’s palsy , in whicLipid-lowering and other pleiotropic effects could mediate the protective effects of statin use on Bell’s palsy. The neuroprotective effect of statins is exerted independently, different from the lipid-lowering effect ,33. RosuHowever, some previous studies have demonstrated the neurotoxic effects of statins, for example, an increased risk of Bell’s palsy. Axonal degeneration and segmental demyelination were suggested to be related to neuropathy following statin use . StatinsThe Bell’s palsy group was matched with a non-Bell’s palsy group in this study. Total cholesterol level, blood pressure, blood glucose, hemoglobin, obesity, smoking, alcohol consumption, CCI score, and dyslipidemia were adjusted for analyzing the relationship between statin use and Bell’s palsy. To exclude other causes of facial palsy, patients with a history of trauma or brain tumor were excluded. In addition, comprehensive subgroup analyses were conducted.Regardless, there are certain limitations to the present study, primarily owing to the lack of linked information in the cohort. First, because statin use was examined using prescription data, drug compliance could not be accounted for in this study. Second, information on statin type could not be obtained. The impact of statin use on Bell’s palsy might vary according to the types of statins used. The use of lipophilic statins is more closely associated with peripheral neuropathy than the use of less lipophilic statins . Third, We found that previous statin use was not associated with Bell’s palsy in this population ≥40 years old.


Typical AR methods have generic problems such as visual mismatching, incorrect occlusions, and limited augmentation due to the inability to estimate depth from AR images and attaching the AR markers onto physical objects, which prevents the industrial worker from conducting manufacturing tasks effectively. This paper proposes a hybrid approach to industrial AR for complementing existing AR methods using deep learning-based facility segmentation and depth prediction without AR markers and a depth camera. First, the outlines of physical objects are extracted by applying a deep learning-based instance segmentation method to the RGB image acquired from the AR camera. Simultaneously, a depth prediction method is applied to the AR image to estimate the depth map as a 3D point cloud for the detected object. Based on the segmented 3D point cloud data, 3D spatial relationships among the physical objects are calculated, which can assist in solving the visual mismatch and occlusion problems properly. In addition, it can deal with a dynamically operating or a moving facility, such as a robot—the conventional AR cannot do so. For these reasons, the proposed approach can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. Quantitative and qualitative analyses verify the advantage of the proposed approach compared with existing AR methods. Some case studies also prove that the proposed method can be applied not only to manufacturing but also to other fields. These studies confirm the scalability, effectiveness, and originality of this proposed approach. Recently, many studies have been attempted to increase productivity by building smart factories through the convergence of the Internet of Things (IoT) and information and communication technology (ICT) in traditional manufacturing systems ,2. As thAugmented reality is considered to provide user-centric information more easily in various environments by embedding visual information onto the real objects directly. In particular, the AR-based visualization of manufacturing information, called industrial AR, can provide more effective task assistance, which can reduce a worker’s cognitive load and increase work efficiency ,6,7.Typical industrial AR superimposes necessary manufacturing data around real equipment using AR markers for indirect object detection and visual registration. However, it is difficult to attach AR markers on the physical objects such as machines and facilities whose shapes are complicated. It is much more difficult to attach them if the configuration of the facility or equipment is dynamically moving during the operation. Note that it is challenging to acquire a 3D spatial relationship between physical objects from an RGB image using only one AR marker. Thus, it is necessary to attach multiple AR markers to them to solve this problem. However, it is sometimes infeasible to attach multiple markers. In addition, some of the markers cannot be adequately detected due to spatial occlusion when the viewpoint is changed. Therefore, visual mismatch and incorrect occlusion problems still occur in industrial AR environments, as shown in For example, although the manufacturing information can be visualized correctly from a particular viewpoint of the worker, as shown in For this reason, several previous studies have been conducted to support effective and user-friendly visualization by solving these problems in industrial AR ,9,10,11.In this study, we propose a hybrid approach to industrial AR, which can complement existing AR methods and provide manufacturing information more effectively through the deep learning-based instance segmentation and depth prediction of physical objects in the AR scene. Deep learning-based instance segmentation is performed to recognize physical facilities and to outline their regions in the AR view , and the depth prediction using another deep learning is simultaneously conducted to predict a 3D depth map of those facilities from the same AR view, as shown in The contributions of this study are as follows.(1)A new industrial AR method is proposed to provide manufacturing information more intuitively and accurately by solving visual mismatch and occlusion problems through the deep learning-based instance segmentation and depth prediction.(2)It is possible to handle dynamically moving facilities and visualize the manufacturing information more effectively.(3)The proposed approach can complement existing AR methods. Thus, it can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions.(4)The applicability and extensibility of this study can be confirmed through experiments and various viable implementations.The paper is organized as follows. Previous studies have shown that AR-based task assistance methods can reduce the worker’s mistakes more than text or video-based methods. Additionally, it is well-known that the provision of manufacturing information using AR is more effective in supporting the task of the worker ,14,15.Several previous AR studies have been conducted to provide useful and effective visualizations of manufacturing information, such as the real-time status of the facility or guided instructions with single or multiple AR markers ,17,18,19To visualize manufacturing information in AR environments, methods using markerless tracking systems without AR markers were also studied. Lima et al.  proposedIn typical AR, a real object and its corresponding virtual model are simultaneously visualized on the screen of a smart or wearable device. Due to the inherent rendering characteristic of AR, real objects on the AR view are obscured by virtual objects. In particular, the incorrect occlusion lowers the worker’s immersive feeling and also hinders task assistance in various industrial AR environments. Therefore, several methods have been proposed for handling occlusions between real and virtual objects in AR properly. Those can be divided into three approaches, a contour-based approach, a depth-based approach, and a 3D reconstruction-based approach.The contour-based approach traces the silhouette or edge of the object to handle the occlusion . The conIn particular, most of the previous studies were mainly applicable to a static environment wherein the real object could not move. In addition, most mobile devices do not have RGB-D sensors. Therefore, this study proposes a new industrial AR method using a single RGB image to handle visual mismatches and occlusions using deep learning in dynamic environments .IoT integrates the key technologies of industrial communication, computing, and control, and is providing a new way for a wide range of manufacturing resources to optimize management and dynamic scheduling . RecentlAR also plays an important role in IoT applications, such as smart homes, farming, and robot task planning. Seo et al. proposed a hybrid reality-based user experience and evaluation of a context-aware smart home . The useThis study proposes a new hybrid approach to industrial AR that can provide user-friendly manufacturing information to the worker more effectively and naturally by combining deep learning and augmented reality, which can complement existing AR methods. Instance segmentation is applied to the image of the AR view to detect actual equipment and tools and to segment their outlines from the AR image. Besides, depth information is predicted at the same time, using another deep learning approach. Then, the relative 3D spatial relationship between objects is calculated using the segmented object instances and predicted depth information. Finally, the manufacturing information is augmented on physical objects so that the worker can easily understand their tasks through AR scenes. The deep learning-based facility recognition and region extraction module applies the mask region-based convolutional neural network (Mask R-CNN ) to the The AR-based manufacturing information visualization module superimposes the required information onto the detected objects for task assistance. Firstly, it creates triangle meshes using the segmented and predicted 3D point cloud data. Then, a 3D spatial relation among real facilities is calculated from the constructed 3D meshes as the 3D meshes can be sorted in the ascending order in the depth map. Finally, a meshing rendering using a depth mask shader is applied to the 3D meshes for occlusion rendering, which makes the region of the object in the AR view depth-aware transparent. For example, the far object instance can be occluded by the near object instance, although there is no such information in the AR scene.The deep learning methods used in this study are difficult to be executed in mobile or wearable devices directly because of their hardware and software restrictions. For this reason, a client-server module was developed to solve this problem. The module consists of the AR client and the remote deep learning server, as shown in Although this study can solve the problems of existing AR, such as visual mismatches and incorrect occlusions, with deep learning it is difficult to guarantee real-time performance regarding providing manufacturing information to users. Therefore, the proposed approach can be utilized as a hybrid or complementing function to existing AR methods since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. In other words, the proposed method and the existing AR method can be used at the same time, so that they can be switched with each other as needed, thereby complementing each other. Since the technology of deep learning and the performances of mobile devices are rapidly developing, it is expected that deep learning will be executed in real time on smart devices rather than via server–client connections sooner or later.Note that the proposed approach can not only detect physical object instances but also segment the outlines of the objects whose configurations are dynamically moving and changing. Most of the previous AR works have not considered this issue. In addition, manufacturing information is augmented in the right position by overcoming visual mismatches and incorrect occlusions. For example, visual information of a certain facility that is far from the worker can be obscured by nearby facilities. Besides, manufacturing information of a nearby facility can be displayed in a larger and detailed form, and that of a remote facility can be displayed in a simplified and small form, which can provide a more intuitive and user-centric visual form.It is crucial to acquire 3D spatial information and the class and position of each equipment to provide manufacturing information appropriate for task assistance in mobile AR.TM (UR3) and its gripper from the AR view. Unlike object detection, which displays a detected object as a bounding box, instance segmentation accurately can render the region corresponding to the outline of the detected object. In particular, it recognizes the region as another object, even if it is classified into the same class. In this study, instance segmentation was conducted using the Mask R-CNN [Object instance segmentation identifies object outlines at the pixel level by detecting objects and segmenting their regions in the RGB image, as shown in sk R-CNN  to outliMask R-CNN extends Faster R-CNN  by addinMask R-CNN defines a multi-task loss on each sampled RoI as follows (Equation (1)).p and t represent the size and position of the predicted classes and bounding box, and u and v represent the size and position of the real class and bounding box.The classification loss er R-CNN  as folloFinally, the mask loss By conducting the instance segmentation mentioned above, it is possible to calculate 2D spatial relations, such as relative positions between real objects. However, since the depth information is unknown, a 3D spatial relation cannot be derived, which can cause visual mismatch and occlusion problems. To calculate the 3D spatial relationships between objects from the AR view, depth information must be predictable. Note that mobile AR also utilizes a single image so that it cannot percept depth information from the single image without AR markers. In this study, depth information was predicted through an hourglass network by training MageDepth Dataset ,39. DeptL (Equation (3)) combines three terms as follows [The scale-invariant loss function  follows .(3)L= LL be a predicted log-depth map and i.n is the number of valid depths in the ground truth depth map.The scale-invariant data loss 1L penalty on differences in log-depth gradients between the predicted and ground truth depth map as follows.i and scale k.The scale-invariable gradient matching loss i and j (i is further than j and −1 otherwise).The ordinal depth loss As a result, the segmented 3D point cloud data of the detected facilities can be acquired by combining the predicted depth information with the outcome of instance segmentation. Since the dimension of the predicted information is the same as that of the RGB image, the segmentation of 3D point clouds corresponding to the detected facilities from the predicted depth map is straightforward.When information on the segmented 3D point cloud data is transmitted to the mobile device of the worker together with the classification information of the detected facilities, all the information is combined to handle visual mismatches and incorrect occlusions in manufacturing information visualization. Since segmented point cloud data do not contain surface information for rendering and occlusion handling, a triangular mesh is constructed from the segmented point cloud of each object instance. If there are multiple detected object instances, several triangular meshes are generated. Each triangular mesh can represent a detected object in the 3D AR space. A Delaunay triangulation was applied to construct a triangular mesh of the segmented 3D point cloud of each object instance ,42, as sAs 3D spatial relation can be derived from the 3D meshes of segmented instances, the location and orientation of a visual information panel or object can be easily synchronized with the detected real facility. In particular, even if the actual equipment is dynamically operating or moving by changing its configuration, the manufacturing information can be positioned around the equipment properly by updating its location, as the proposed approach can detect and segment facilities and predict their 3D depths and spatial information. On the other hand, when the existing AR marker is used, there is no problem in visualizing fixed and stationary equipment, but visual mismatching occurs when the position and configuration of the equipment are changed. We implemented the proposed industrial AR, which can segment actual facilities and predict their 3D depths from the AR view for task assistance. Instance segmentation and depth prediction can run on either TensorFlow  or PytorTM) and another AR method using a smartphone with an RGB-D camera (Google TangoTM). In the case of AR marker-based methods, the 3D model is overlaid on the AR marker when the AR method recognizes the marker. In the case of the method using the RGB-D camera, the outline of the facility is segmented using the Mask R-CNN used in the proposed approach, but only the point cloud data corresponding to the segmentation are extracted from among those obtained by the RGB-D camera. Two experiments were conducted to evaluate three methods. First, we examined the effectiveness of the recognition of real equipment according to the variable distance. Different color gradation is used to represent the distance from the AR system. For example, the color becomes darker when the detected object is far from the user. Second, we evaluated the recognition of dynamically moving equipment. Note that one of the main advantages of the proposed industrial AR visualization is that it does not require a depth sensor.We compared the proposed industrial AR with conventional AR marker-based methods  using a popular Android-based smartphone (Samsung Galaxy S9We evaluated whether each method can detect and superimpose a virtual model onto corresponding real equipment consistently and effectively depending on the distance between the AR camera and the equipment. For this purpose, each AR system was located at a distance of 1, 3, or 5 m from the UR3 robot and another robot prototype created using a 3D printer, as shown in First, the cylindrical AR marker-based method showed the worst performance. On the other hand, the proposed method showed the best performance without AR markers and an RGB-D sensor. When a cylindrical AR marker was attached to the physical object, the marker was recognized at a distance of 1 m, but the marker was not identified at distances of 3 and 5 m b. The siHowever, this attachment was not normal. When the marker was attached to the floor, its recognition rate became worse. As shown in We have also evaluated the capability for handling dynamically moving objects. As shown in Note that one of the advantages of using the AR marker is to detect actual facility fast and accurately. However, when the configuration of the facility is changed, or the facility is moving, it is almost impossible to detect parts or components attached to the facility without receiving additional information through other sensors. Furthermore, it is still difficult to detect and segment the facility itself, and their components as AR markers might be occluded when the facility and their parts are moving, as shown in To verify the advantages and applicability of the proposed industrial AR, several proof-of-concept applications were implemented.The manufacturing information visualization using the proposed industrial AR was implemented using robots in a controlled laboratory environment. In particular, the UR3 robot can move to pick up a part and place it to a specified location. During the robotic operation, the kinematic configuration of the robot is changed. However, the conventional AR cannot overcome the inherent occlusion problem shown in The proposed AR method can also be applied to a hybrid AR environment that fuses virtual and real objects. For example, it can be effectively applied to a process layout design where a new facility will be added to examine possible layouts or simulations with existing facilities. As can be seen in The second application was applied to the testbed of a smart factory . The tesIn addition to applying the proposed industrial AR to manufacturing information visualization, we have found that it can be applied to the visualization of smart appliances or devices in a smart home. In this application, a pre-trained network was utilized. As shown in The second application is to visualize augmented virtual objects between real objects in RGB images. As shown in Existing AR methods have difficulties in handling incorrect occlusions and visual mismatches and in estimating depth from AR images, which prevents the industrial worker from conducting manufacturing tasks effectively. To solve these inherent problems in existing AR methods, this study proposed a new hybrid approach to industrial AR for complementing existing AR methods using deep learning-based facility segmentation and depth prediction without AR markers and a depth camera.Several case studies and experimental analysis in Nevertheless, there is some room for improvement and investigation. The depth prediction does not always construct 3D depth maps accurately depending on the background color and its complexity, as shown in Nevertheless, the proposed approach and an existing AR method complement each other. That is, for ordinary situations, the existing AR method is used, since it can support real-time marker tracking. However, as the existing AR cannot handle incorrect occlusions and visual mismatches, the worker can switch to the proposed approach to understand the situation more effectively and intuitively.This paper proposed a new industrial AR method that can handle visual mismatches and incorrect occlusions of previous AR methods in representing manufacturing information by applying deep learning-based facility segmentation and depth prediction. From a single AR image, object instances are detected and segmented. At the same time, depth prediction is applied to the same AR image. Then, a segmented 3D point cloud for each detected object can be easily generated. Besides, a 3D triangular mesh is constructed from the segmented 3D point cloud, which makes it possible to find 3D spatial relations among the detected objects and render them in the 3D AR space rather than the image-based AR space. The constructed 3D mesh and spatial relation are used to solve visual mismatch and occlusion problems. Furthermore, the proposed approach can provide consistent AR visualization regardless of the movement of the physical object. Therefore, manufacturing information can be provided to the worker more intuitively and situation-dependently based on the estimated 3D spatial relation and depth perception. Note that the proposed approach can be utilized as a hybrid or complementing function to existing AR methods, since it can be activated whenever the industrial worker requires handing of visual mismatches or occlusions. For another possible storyboard, a facility manager can utilize the proposed approach, since the manager has difficulty in monitoring and maintaining the facility by looking at its outside or surface. In such a case, it would be more helpful to combine various IoT sensor data with the proposed AR system.In future research, we will improve the deep learning network architecture because it is affected by the performance of the deep learning network. In addition, the proposed approach will be applied to various industrial environments. Furthermore, we will also design more storyboards of actual and realistic industrial situations.