Traditional in-person psychotherapies are incapable of addressing global mental health needs. Use of computer-based interventions is one promising solution for closing the gap between the amount of global mental health treatment needed and received.Although many meta-analyses have provided evidence supporting the efficacy of self-guided, computer-based interventions, most report low rates of treatment engagement . The aim of this study is to investigate the efficacy of an adjunctive treatment component that uses task shifting, wherein mental health care is provided by nonspecialist peer counselors to enhance engagement in an internet-based, self-directed, evidence-based mindfulness intervention among Chinese university students.Be Mindful delivers all the elements of mindfulness-based cognitive therapy in an internet-based, 4-week course. Participants completed daily monitoring of mindfulness practice and mood, as well as baseline and posttreatment self-reported levels of depression, anxiety, stress, and trait mindfulness. We screened 56 volunteer peer counselor candidates who had no former training in the delivery of mental health services. Of these, 10 were invited to participate in a day-long training, and 4 were selected. Peer counselors were instructed to provide 6 brief (15-20 minute) sessions each week, to help encouraging participants to complete the internet-based intervention. Peer counselors received weekly web-based group supervision.From 3 universities across China, 54 students who reported at least mild stress, anxiety, or depression were randomly assigned to a 4-week internet-based mindfulness intervention (MIND) or to the intervention plus peer counselor support (MIND+), respectively. d) for mindfulness, depression, anxiety, and stress were 0.55, 0.95, 0.89, and 1.13, respectively. Participants assigned to the MIND+ (vs MIND) condition demonstrated significantly less attrition and more adherence, as indicated by a greater likelihood of completing posttreatment assessments  and a higher percentage of course completion , respectively. No significant between-group differences in daily frequency and duration of mindfulness practice were observed. Multilevel logistic growth models showed that MIND+ participants reported significantly greater pre-post improvements in daily stress ratings  and depression  than those in the MIND condition.For both conditions, participation in the internet-based intervention was associated with significant improvements in mindfulness and mental health outcomes. The pre-post effect sizes (Cohen This study provides new insights into effective ways of leveraging technology and task shifting to implement large-scale mental health initiatives that are financially feasible, easily transportable, and quickly scalable in low-resource settings. The findings suggest that volunteer peer counselors receiving low-cost, low-intensity training and supervision may significantly improve participants’ indices of treatment engagement and mental health outcomes in an internet-based mindfulness intervention among Chinese university students. Approximately 1 in 5 adults in the United States experiences mental illness annually . GloballTraditional psychotherapy training models  and psychotherapies (one-on-one and in-person sessions) are incapable of singularly closing the global mental health gap in LMICs. Fundamentally, new approaches are needed to increase access to effective mental health care in an economic, feasible, and scalable manner to address global needs , and comg) were reported for stress (g=0.51), depression (g=0.29), anxiety (g=0.22), well-being (g=0.23), and mindfulness (g=0.32), all with nominal statistical significance thresholds of P<.50 [Mindfulness- and acceptance-based interventions have been successfully used to address clinical dysfunction across a range of physical and mental health disorders. Specifically, systematic reviews and meta-analyses have demonstrated mindfulness and acceptance to be beneficial in treating physical health conditions, such as chronic pain , as wellof P<.50 . OverallPTSD Coach, an app developed and used by the Department of Veteran’s Affairs, was downloaded more than 150,000 times, fewer than 15% of the people used it within 1 week [Although technology-based mindfulness interventions can be effective, treatment engagement is a key barrier to the implementation of these approaches. High attrition and low adherence rates are commonly observed in research and practice. Nonadherence can diminish the effectiveness of interventions -21. For n 1 week .Adherence is especially relevant in mindfulness training because regular practice is thought to be essential for developing mindfulness skills. In their meta-analytic review of web-based mindfulness interventions, Spijkerman et al  reportedAlthough many web-based mindfulness interventions have been shown to be effective, about half of the published studies did not report treatment engagement outcomes, and of those that did, most reported low engagement (high attrition and low adherence). Researchers have repeatedly noted that in spite of the effectiveness of web-based interventions, it is a consistent challenge to reliably measure the amount and quality of mindfulness practice with which people engage ,24. Moreg=0.89 and g=0.43, respectively), than for those interventions without guidance . Although offering therapist guidance may potentially improve adherence and treatment outcomes, it is costly and may restrict the scalability of the intervention, particularly in LMICs. To overcome these barriers, some web-based interventions provide automated support, which has preliminary evidence supporting its efficacy [Previous research indicates that providing therapist support has a positive inﬂuence on adherence and enhances the effectiveness of web-based psychological interventions -28. Spijefficacy -31. For efficacy  suggest task shifting, wherein mental health care is provided by nonspecialist peer counselors , has recently been investigated as a promising strategy to overcome human resource shortages in LMICs. In this model of care, peer counselors receive training, supervision, and oversight from mental health care professionals . Task shifting has been shown to be effective in the treatment of mental health problems [Task sharing or problems ,34, and problems , child aproblems , and nonproblems ). Thus, The aim of this study is to examine whether an adjunctive, task-shifting component (MIND+) enhances treatment engagement in a mindfulness intervention for stress and depression among Chinese undergraduate and graduate students. Individuals were randomly assigned to a brief (4-week), self-guided, web-based, mindfulness intervention (MIND), or the intervention plus support from nonspecialist peer counselors (MIND+). Peer counselors were instructed to engage in brief (15-20 minutes) weekly meetings with MIND+ participants via text or phone call during the course of treatment, with the intention of supporting and encouraging participants to complete the internet-based intervention. It was hypothesized that at posttreatment, participants randomly assigned to MIND+ (vs those assigned to MIND) would show (1) less attrition (higher completion rates of assessment), (2) greater adherence (higher percentage of course completion), (3) greater reductions in stress and depression levels, and (4) greater increases in mindfulness.Participants were 54 currently enrolled university students  from 36 universities across China. Their mean age was 23.5 years (SD 3.17), and 74% (40/54) identified as female. Out of the 54 participants, 29 (54%) were master’s students, 21 (39%) were undergraduate students, and 4 (7%) were doctoral students. All participants reported having passed an English proficiency test: 11% (6/54) reported passing the College English Test ; 72% (39/54), the CET (level 6); and 17% (9/54), the Test of English as a Foreign Language. All participants denied currently receiving formal mental health treatment; 80% (43/54) reported no history of mental health treatment, 11% (6/54) reported formerly receiving therapy, 4% (2/54) reported formerly receiving medication, and 6% (3/54) reported formerly receiving both treatment and medication. Out of the 54 participants, 47 (87%) reported no previous mindfulness training, and 3 (6%) reported practicing mindfulness meditation in the past year.Participants were recruited via WeChat blogs, student club listservs, and university websites’ listing of available jobs and research opportunities. Interested individuals completed a web-based screening assessment. Eligible students were contacted by the study coordinator, who conducted phone interviews and orientation to the study procedures. Students who provided proof of student status and emergency contact information received a link to the baseline assessment measures. Students who completed the web-based baseline assessment measures were randomly assigned to a brief, 4-week internet-based mindfulness intervention (MIND), or to the intervention plus peer counselor support (MIND+). The inclusion and exclusion criteria have been provided in Inclusion criteriaIs currently enrolled in a university in China Has a smartphone and regular access to the internetDemonstrates the ability to read and understand MandarinReports passing at least College English Test (level 4)Experiences at least mild depression and anxietyExclusion criteriaIs aged <18 yearsDoes not provide proof of current student status and emergency contactCurrently experiences manic or psychotic symptomsExpresses suicidal or homicidal ideation during the intake phone interviewPeer counselors included 4 currently enrolled female students at 3 different universities in Beijing. At the time of recruitment, their mean age was 27.5 years (SD 6.8), including 1 undergraduate (psychology), 1 master’s (business), and 2 doctoral (nursing) students. None of the peer counselors reported formal training or experience in mindfulness practice or the provision of mental health services. All participants reported having passed at least the CET (level 6).Web-based advertisements were posted on university research, student club, and mindfulness listservs. A total of 56 candidates responded to the web-based survey, expressing interest in participating in the study as peer counselors. Those who met the inclusion criteria were contacted via telephone to screen for the exclusion criteria and confirm their understanding of the study and willingness to participate in the in-person training and orientation. Volunteer peer counselor candidates who met all the inclusion criteria were invited to the in-person training and orientation. After this training, participants were contacted via telephone to once again assess their willingness to engage in the study. We selected 4 individuals as peer counselors based on their English proficiency, reported level of enthusiasm for the project, and the researchers’ assessment of their nonspecific factors. Each individual was given access to the internet-based intervention and a 6-week period to complete the course. After completing the course, peer counselors were paired with study participants who were randomized to the MIND+ group. The inclusion and exclusion criteria for peer counselors have been illustrated in Inclusion criteriaIs currently enrolled in a university in Beijing Has a smartphone and regular access to the internetDemonstrates the ability to read and communicate in Mandarin and EnglishIs willing to provide brief (15-20 minute) peer-support chats per week per participantIs willing to participate in web-based group supervision for 1 hour per weekIs willing to complete the internet-based mindfulness interventionExclusion criteriaIs aged <18 yearsReports previous or current format training in mindfulness or psychotherapyReports current treatment (psychotherapy or medication) for a mental health problemIs unable to attend the day-long, in-person training in BeijingThe in-person training took place for 8 hours in Beijing. All lectures and discussions were conducted in Mandarin. Peer counselor candidates listened to lectures on topics related to peer counseling and the current research project. The candidates were given opportunities to practice using the skills in dyads and to receive coaching and feedback from the first author and research assistants.Training was didactic and experimental and included (1) mindfulness theory and practice (2 hours), (2) orientation to the study and role of a peer counselor (1.5 hours), ethics, confidentiality, and mandated reporting (30 minutes), (4) lunch break and personal introductions (1 hour), (5) fundamentals of counseling listening skills (30 minutes), (6) validation techniques (1.5 hours), and (7) motivational interviewing (1 hour). Weekly group supervision was attended by the research coordinator (MR), 2 research assistants, and the 4 peer counselors. Meetings were conducted in Mandarin and via a videoconferencing software  after peer counselors were matched with their first participant. The structure of the supervision meetings was modeled after the elements of dialectical behavior therapy consultation team meetings . The meeBe Mindful course is an internet-based mindfulness training program produced by Wellmind Media, with support from the UK-based charity Mental Health Foundation. Be Mindful delivers all the elements of mindfulness-based cognitive therapy in an internet-based course that can be completed in 4 weeks. It can be accessed through their website [Be Mindful course . The coBe Mindful course website reported that over 20,000 people had taken the course since 2011. The participants in this study were able to complete the course for free. Project staff received technical support and administrative access to randomize participants, track progress , and download data. All materials on the course were translated into Mandarin, including the videos, audio recordings, and homework assignments. Each week, the research coordinators emailed materials to the participants after they were ready to progress to the next chapter in the course. Furthermore, 6 weeks after initial enrollment, participants received an email thanking them for their participation and a link inviting them to complete the posttreatment assessment. If they did not complete the survey within 1 week, they were contacted via text message, WeChat, and email over the course of the next week. Participants were paid upon completion of the posttreatment questionnaire packet. When this study was conducted in May 2018, the Participants were compensated for completing the baseline questionnaire packet, posttreatment questionnaires, and for responding to each daily assessment; the total amount that the participants could make from this course was approximately US $28. This study received institutional review board approval from the Psychology Research Ethics Committee at the Beijing Institute of Technology, and all participants electronically signed a digital informed consent form.Participants randomized to the MIND+ condition (n=27) completed the same procedures as those in the MIND condition (n=27). However, those in the MIND+ condition were informed by the study coordinator via email that they were paired with a peer counselor who would provide them support and encouragement. Participants were instructed to contact their peer counselor within a week to schedule a time to chat. Peer counselors were instructed to contact their participants if they did not hear from them within 5 days. Peer counselors were encouraged to provide brief (15-20 minutes) weekly meetings to support and encourage participants in their completion of the internet-based intervention.very low, 5=very high). Daily questionnaires also assessed participants’ self-reported frequency and duration (in minutes) of mindfulness practice the previous day. Links to questionnaires expired within 4 hours if not completed.Daily assessments were completed using the Qualtrics software. Participants rated their state mindfulness and mood  on a 5-point Likert scale , as well as self-report data about the patient’s English proficiency, meditation experience (previous training and current practice), psychiatric diagnostic and treatment history, and emergency contact information.The 7-item Generalized Anxiety Disorder (GAD-7) questionnaire is a 7-item measure of the severity of anxiety symptoms in the last 2 weeks ,42. The The Patient Health Questionnaire-9 (PHQ-9) is a 9-item measure of the severity of depression symptoms in the last 2 weeks ,44. The The Five-Factor Mindfulness Questionnaire (FFMQ), originally developed by Baer, is a 39-item measure of trait mindfulness that is organized into 5 subscales , with 7 or 8 items in each subscale ,46. OnlyThe Depression Anxiety Stress Scale is a 21-item measure comprising 3 subscales  of 7 items each, which provide indices of depression . The CroPerceived Stress Scale (PSS) is a 14-item measure of perceived stress in the last month . The CroAll analyses were conducted in SAS .early study (days 1-11), mid study (days 12-23), and late study (days 24-35).To capture any nonlinear changes across the study, the phases were coded as follows: First, a chi-square analysis was used to test the hypothesis that participants randomly assigned to MIND+ (vs those assigned to MIND) would show less attrition as indicated by higher completion (vs noncompletion) rates of posttreatment assessment (yes or no).t tests were used to test the hypotheses that participants randomly assigned to MIND+ (vs those assigned to MIND) would show greater program adherence, as indicated by more frequent use of the course  and a higher percentage of the course completed.Second, independent samples, two-tailed Three multilevel models  were used to test the hypothesis that the randomization to the MIND+ condition would result in a greater increase in mindfulness across the trial, and greater decrease in depression and stress levels across the trial. Time was also alternatively defined by examining contrasts of the beginning of the study (days 1-11) with both the middle (days 12-23) and end (days 24-35) of the study.Model fitting was accomplished using the −2 log likelihood model to determine model fit. Random slopes were retained when this improved the model fit. Person-standardized daily values  were used for graphical depictions of continuous outcomes to depict only the within-person changes in the outcome across the study, consistent with multilevel modeling results.d. For multilevel modeling outcomes, Cohen d was calculated for the group means of difference between scores on days in the early study phase and the late study phase.The size of group differences in each outcome, or change over time in each outcome, was estimated using Cohen The randomization sequence was sourced through random.org , an auto21=6.1; P=.01). Hypothesis 1 predicted that participants randomly assigned to MIND+ (vs those assigned to MIND) would show less attrition, as indicated by a greater likelihood of completing the posttreatment assessment . A chi-square analysis comparing dichotomous condition assignment (MIND vs MIND+) and posttreatment assessment (completed vs not completed) revealed a greater number of completers in the MIND+ condition . Hypothesis 2 predicted that participants randomly assigned to MIND+ (vs MIND) would show greater program adherence, as indicated by a higher percentage of course completion as a continuous, between-person variable. An independent samples Hypothesis 3 predicted that participants randomly assigned to MIND+ (vs those assigned to MIND) would show more robust improvements in stress, depression, and mindfulness levels across the trial . The results of the multilevel models testing this hypothesis are presented in The aim of this study was to investigate the efficacy of an adjunctive treatment component that uses task-shifting  to enhance engagement in a self-directed, web-based mindfulness intervention for stress and depression among Chinese undergraduate and graduate students.The results indicated that participants assigned to the MIND+ (vs those assigned to the MIND) condition showed significantly less attrition and more adherence, as indicated by a greater likelihood of completing posttreatment assessments and a higher percentage of course completion, respectively. In addition, individuals in the MIND+ condition reported significant improvements in daily ratings of stress and depression levels across the trial compared with individuals in the MIND condition. These findings suggest that volunteer peer counselors receiving brief training and weekly supervision may significantly improve participants’ indices of treatment engagement and mental health outcomes in an internet-based mindfulness intervention among college and graduate students in China.This study makes several unique contributions to the literature. First, an internet-based platform was used to deliver a mindfulness intervention in a sample of individuals from a non-Western LMIC. There have been no publications of results from randomized controlled trials investigating the efficacy of a self-guided, web-based, mindfulness intervention in China.Second, this study uses a task-shifting informed approach aimed at increasing retention and adherence to an existing evidence-based intervention. There have been no publications of results from randomized controlled trials investigating the efficacy of an adjunctive, web-based, peer support intervention component intended to enhance treatment engagement in a self-guided, web-based, mental health intervention in an LMIC. Furthermore, only 3 studies have been published on task shifting in mental health services of any type in China -52. Accosessions , lasting an average total of 120.85 minutes  per MIND+ participant. All peer counselors maintained full-time student status and part-time jobs throughout the course of volunteering for this study. Peer counselors reported completion of responsibilities for this study  and required, on average, less than 2 hours per week, when supporting 2 patients at the same time.Third, this study explored the effects of a very low-intensity, low-cost task-shifting intervention. Nonspecialist peer counselors received only 1 day of in-person training with ongoing web-based, group supervision once per week. Furthermore, each participant in the MIND+ group only received a mean of 4.69 peer counseling session audio recordings). Fourth, this study contributes new insights into the selection, supervision, and evaluation practices for task-shifting initiatives. According to a recent systematic review of 137 studies from 48 countries employing task shifting to deliver evidence-based mental health services in LMICs, fewer than 1 in 5 studies reported providing supervision on a weekly or biweekly basis . In thisand follow-up assessments; however, only 11% (3/27) of MIND participants and 15% (4/27) of MIND+ participants completed both.Completion rates in this study  appear to be lower than those in previous studies. In comparison, Querstret et al  reportednot at all, and 17 (40%) reported a little. However, 9% (4/43) of participants indicated that language was very much a barrier to completion. It is also possible that language was more of a barrier for the 11 participants who did not complete the posttreatment assessment. However, follow-up analyses did not reveal an association between language proficiency and course completion or engagement. Specifically, follow-up analyses revealed that self-reported baseline English proficiency and posttreatment perception of language as a barrier to completion were not significant predictors of treatment completion.One explanation for the lower completion rates in this study is that participants completed the course in their second language. Of the 43 participants who completed the posttreatment assessment, when asked the degree to which language was a barrier in completing the course, 16 (37%) indicated very motivated to learn and practice mindfulness, and 44% (24/54) reported being extremely motivated. However, across both groups, baseline self-reported energy to learn and practice mindfulness was predictive of failure to activate the Be Mindful course  and total login count .Another explanation for this difference is that participants in the studies by Krusche et al  and QuerP=.05), defined as never responding to the daily assessment or not responding for at least the last 3 weeks of the study. These findings suggest that a low-cost, low-intensity task-shifting component is promising as a feasible and scalable approach for enhancing retention in web-based evidence-based treatments. Previous research suggests that personalizing the contact  is associated with lower rates of treatment termination [Participants assigned to the MIND+ (vs those assigned to the MIND) condition showed significantly less attrition, as indicated by a greater likelihood of completing the posttreatment assessments in the internet-based course. MIND+ participants also demonstrated a nonsignificant trend toward lower rates of nonuse attrition  condition showed greater program adherence, as indicated by a higher percentage of the course completed. However, there were no between-group differences in attrition, as indicated by (1) more frequent log-ins to the course, (2) a less robust decrease in daily self-reports of mindfulness practice, or (3) a less robust decrease in daily self-reports of minutes of mindfulness practiced over the course of the treatment. Overall, these data suggest that the MIND+ task-shifting component increased participants’ likelihood of completing the program but not necessarily their likelihood to be more actively engaged in the program  or to report higher frequency or duration of mindfulness practice.highly stressed [moderately anxious [moderately depressed [It is worth noting that participants in this study presented with mean baseline PSS (stress), GAD-7 (anxiety), and PHQ-9 (depression) scores of 23.27 (SD 4.28), 9.90 (SD 3.98), and 11.31 (SD 5.06), respectively. These means are higher than the scores provided in published population norms for the PSS (between 11.9 and 14.7) , GAD-7 , medium (sometimes), and low (rarely or never) scale [sometimes, and in the 2012 study, 55% (55/100) of participants reported practicing sometimes. This study improves upon this approach by collecting daily data and having participants record the number of minutes practiced per day. However, future research would benefit from collecting separate data for formal and informal mindfulness practice, or by collecting data in real time .This study improves upon previous studies of daily practice in relation to the he et al ,64 askedd) for stress among the completers was 1.13. This was equivalent to those reported in previous studies of the Be Mindful course [The results of this study indicate that participation in the internet-based intervention was associated with significant improvements in pre to posttreatment stress outcomes. The pre-post effect size  for anxiety (GAD-7) and depression (PHQ-9) among completers were 0.89 and 0.95, respectively, which are equivalent to those reported in previous studies of the Be Mindful course and in-person mindfulness interventions [The pre-post effect sizes . These outcomes suggest that the effect of having peer support did not increase reported mindfulness as measured in daily assessments or in pre-post measures. Furthermore, it is unlikely that the effect of practice and change in trait mindfulness did not mediate the change in daily reports of stress and depression over the course of the treatment.MIND+ participants did not report significant improvements in daily ratings of state mindfulness across the trial compared with participants in the MIND-only condition. Instead, there was a main effect of treatment on improvements on daily mindfulness ratings. Similarly, there were no between-group differences in pre-post FFMQ scores, although there was a moderate main effect of mindfulness (FFMQ) among completers (Cohen d=0.78 or larger). The sample also consisted of a nonclinical sample of English-speaking university students. Before these findings can be generalized, this research should be replicated among participants using the internet-based intervention in their native language and among larger, more diverse samples. Related to this, the significant effects described here would not survive correction for the number of tests performed in this study; nonetheless, we believe that it is important to share our findings with the field. Second, there were insufficient follow-up data to be able to analyze whether the effects of treatment were sustained over time. Data related to peer counselors’ communication with participants were not included in these analyses. It is possible that the frequency and duration of peer counseling influences the effect of treatment conditions on engagement and mental health outcomes. Future studies should explore and detect the possible dosage effects. Moreover, future research would benefit from having more objective indicators of study, practice, and mindfulness meditation. For example, one patient might report practicing mindfulness once a day, but it could be a 45-minute body scan, and another could report practicing 35 times because they could have noticed their thoughts or body sensations that many times throughout the day. Finally, the exclusion of candidates who expressed suicidal ideation might have led to an underestimation of the overall treatment effect, because the cohort most severely affected by depression was not considered in the study.This study has several limitations. First, the sample was small, achieving 80% power to detect only moderately-sized group differences (ie, Cohen This study provides preliminary support for the effectiveness of a 4-week, internet-based mindfulness course for the reduction of self-reported symptoms of stress, depression, and anxiety among English-speaking university students in China. The effects were compared with those reported in other mindfulness courses delivered on the web and in-person. Furthermore, these results highlight the potential of leveraging task shifting to enhance treatment engagement in self-guided evidence-based treatments. The combination of these approaches may represent a financially feasible, easily transportable, and quickly scalable way to provide mental health services in low-resource settings.


The Surface-Enhanced Raman Scattering (SERS) technique is utilized to fabricate sensors for gas detection due to its rapid detection speed and high sensitivity. However, gases with similar molecular structures are difficult to directly discriminate using SERS gas sensors because there are characteristic peak overlaps in the Raman spectra. Here, we proposed a multiple SERS gas sensor matrix via a spin-coating functional polymer to enhance the gas recognition capability. Poly (acrylic acid) (PAA), Poly (methyl methacrylate) (PMMA) and Polydimethylsiloxane (PDMS) were employed to fabricate the polymer film. The high design flexibility of the two-layer film was realized by the layer-by-layer method with 2 one-layer films. The SERS gas sensor coated by different polymer films showed a distinct affinity to target gases. The principle component analysis (PCA) algorithm was used for the further clustering of gas molecules. Three target gases, phenethyl alcohol, acetophenone and anethole, were perfectly discriminated, as the characteristic variables in the response matrix constructed by the combination of gas responses obtained 3 one-layer and 3 two-layer film-coated sensors. This research provides a new SERS sensing approach for recognizing gases with similar molecular structures. Surface-Enhanced Raman Scattering (SERS) is a widely used sensing technique in which the Raman signal of molecules adsorbed onto noble metal surfaces (such as silver or gold) can be greatly enhanced ,2. The SMolecularly imprinted polymers (MIPs) are prepared using the target molecules as templates to produce receptor sites. After removing the template, the target molecules can be selectively captured ,19,20,21Herein, we propose a method of uncomplicated fabrication and wide-ranging application for constructing a SERS sensor array with different gas affinities, which was spin-coated by distinct functional polymer films for the recognition of gases with similar structures . FunctioPhenethyl alcohol was purchased from Kanto Chemical CO., INC. . Anethole was purchased from Nacalai TESQUE, INC. . Acetophenone, Poly (acrylic acid) (PAA), Poly (methyl methacrylate) (PMMA), ethanol, chloroform and hexane were purchased from Wako Pure Chemical Industries CO., Ltd. . Polydimethylsiloxane (PDMS) was purchased from Shin-Etsu Chemical CO., INC. . All reagents were used as received. RandaS SERS sensor was purchased from ATOID CO. (Japan). Fourier-transform infrared spectroscopy  was used to analyze the polymer film coated on the SERS substrate. Scanning electron microscopy  was used to identify the image sensor morphologies. Raman spectra were obtained by a Raman spectrometer , with a 532 nm excitation laser as a light source (power = 1.5 mW). The accumulation time was set as 10 s for data collection.Three polymer  solutions were prepared. Briefly, PAA (30 mg) was dissolved in ethanol (16 mL), PMMA (30 mg) was dissolved in chloroform (16 mL) and PDMS (2 mg) was dissolved in hexane (16 mL). The prepared polymer solutions were fully stirred before use.First, SERS substrate was cleaned by immersion in acetone, ethanol and ultrapure water sequentially. Then, the substrate dried using nitrogen stream. The SERS sensor without the spin-coated polymer film was used as a bare SERS sensor. Th spin-coating method was used to fabricate the SERS gas sensors with polymer film. For the one-layer polymer film-coated SERS sensor, the polymer solution (15 uL) was spin-coated on the SERS substrate and then dried in a vacuum. Spin-coating was performed at 500 rpm for 20 s, a slope of 500 rpm to 3000 rpm for 10 s and 3000 rpm for 30 s. The two-layer polymer film-coated SERS sensor was fabricated using the layer-by-layer method. The first polymer film was prepared on the cleaned SERS substrate, and after the first film was dried, the second polymer film was spin-coated.rD is the diffusion rate (ug/min), F is the flow rate of the dilute air (0.1 L/min) and k is the factor used to convert gas weight to volume, calculated by:t is the temperature in the gas detector cell (20 °C) and P is the gas pressure (760 mmHg). The phenethyl alcohol, acetophenone and anethole concentrations of the target gas were calculated to be 403.4 ppm, 510.2 ppm and 623.7 ppm, respectively.The schematic diagram of the gas generation and detection system is shown in A metallic cover was designed to prevent laser leakage, and an adjustable stage was manufactured to adjust the position and size of the laser focused on the SERS gas sensor. Raman spectra of the three target gases were recorded after the SERS gas sensor was exposed to each gas for a certain time. Besides, the gas detector cell was washed with air flow for 1200 s after gas detection.−1 and 1604 cm−1 were assigned to the ring breathing vibration and ring stretching mode [−1 and C-O-C stretching vibration at 1175 cm−1 of anethole gas could be clearly observed [−1, which could be used to distinguish the acetophenone and phenethyl alcohol gases. However, the two apparent peaks at 1007 cm−1 and 1604 cm−1 were both observed in the Raman spectra of acetophenone and phenethyl alcohol gases. Thus, it is difficult to directly distinguish these two target gases only through the position where the peaks appeared.The morphologies of the sensors are shown in ing mode   were set as the total sample, and the intensity values in the three selected peaks were considered as the characteristic variables. Hence, a response matrix As the Raman intensity results of one characteristic peak described before , the polnal data ,53. Prin−1 and 1605 cm−1, while the peak of anethole was observed at 1175 cm−1. Hence, the anethole gas could be discriminated from the phenethyl alcohol and acetophenone gases. Besides, a horizontal distribution of these three clusters was found, which indicates that the Raman intensity at 1175 cm−1 plays important role in PC1. The distribution of 90 samples collected from a one-layer polymer film sensor is plotted in the PC1-PC2 space, as shown in PCA score plots of the samples, as detected by the bare sensor, are shown in A and RB, then the gas response of the two-layer polymer A-B might be RA + RB (the combination of the responses of A and B) or RAB (a new gas response characteristic). Herein, the PCA method was utilized to determine the method with better recognition ability for the three target gases. The response matrix Since three kinds of target gases could not be recognized by the one-layer polymer-coated SERS gas sensor, the gas responses obtained from two kinds of polymers were used to conduct the gas recognition. The responses of two polymers can be collected two different ways: the Raman intensities recorded from (1) combinations of 2 one-layer polymer film-coated sensors, or (2) 1 two-layer polymer film-coated sensor. If the gas response of polymer A and B is defined as RThe response matrix constructed by the gas responses obtained from the multiple polymer film-coated SERS gas sensors was applied for gas recognition. Consequently, three response matrices In summary, multiple polymer film-coated SERS gas sensors were developed to distinguish gases with similar structures. Three gases consisting of a benzene ring and distinctive functional groups—phenethyl alcohol, acetophenone and anethole—were selected as target gases. PAA, PMMA and PDMS were employed to fabricate one-layer polymer films on the SERS gas sensors using the spin-coating method. Moreover, two-layer polymer film could be flexibly designed with 2 one-layer films using the layer-by-layer method. The Raman spectra of three target gases were obtained when they were detected by polymer-coated sensors with different gas affinities. Raman intensities at the selected characteristic peaks of target gases were used as characteristic variables in the response matrix for PCA analysis. Besides, characteristic variables could be changed using the Raman intensities detected by the different polymer film-coated sensors. It can be concluded from the PCA results that gas molecules with similar structures were accurately discriminated, and the two-layer film-coated sensor presented a new response property compared to the one-layer film-coated sensor. The best gas recognition result was observed when the response matrix was constructed by 18 characteristic variables according to the PCA score plot. Moreover, the gas recognition performance was improved by increasing the number of characteristic variables in the response matrix. This study verifies that the recognition of gases with similar molecular structures can be realized by SERS sensors spin-coated with multiple polymers possessing different affinities.


BackgroundThis study aimed to assess regional COVID-19 mortality rates and compare the five proposed business units (BUs). MethodsA cross-sectional study was conducted in the Ministry of Health (MOH) hospitals in the Kingdom of Saudi Arabia (KSA). We included 1743 adults (≥ 18 years of age) with COVID-19 admitted to any of 30 MOH hospitals.ResultsThe inpatients had confirmed mild to severe COVID-19 between March and mid-July 2020. The central BU (Riyadh) was used as the reference. MOH electronic health record data were reviewed and utilized, including variables reflecting hospital course . The primary outcome was COVID-19-related inpatient death. Covariates included patient demographics, pre-existing chronic diseases, and COVID-19-related complications. The data were analysed using univariate and multivariate logistic regression. KSA inpatient mortality was 30%. Univariate and multivariate logistic regression analysis suggested that COVID-19-related mortality was significantly higher in the northern and western BUs and significantly lower in the southern and eastern BUs than in the central BU. On controlling for other variables, adjusted odds ratios (AORs) for essential COVID-19 mortality predictors during admission, using the central BU as a reference, were as 9.90  and 1.55  times higher in the northern and western BUs, respectively, and 0.60  and 0.23  times lower in the southern and eastern BUs, respectively.ConclusionThe five BUs differed in COVID-19 mortality rates after adjusting for patient and disease characteristics, with the differences consistent with those in the regions comprising the BUs. These outcome differences apparently relate to differences in healthcare resources and quality. On 5 January 2021, the global mortality rates of the 2019 coronavirus disease (COVID-19) pandemic, caused by SARS-CoV-2, were approximately 2.2%, based on 1,864.933 deaths among 86,298,213 cases [Several international studies have identified risk factors associated with higher mortality from confirmed COVID-19 infection, including increasing age and pre-existing chronic conditions, such as Type 2 diabetes mellitus (DM2), cardiovascular disease, and obesity. However, a wide variation in global mortality rates has been reported , 7. StudThe present public healthcare system is no longer sustainable due to increasing demand for services, population aging, and an economic downturn . TherefoStudy design and populationWe conducted a cross-sectional study using national MOH electronic-health-record data on COVID-19-related deaths. Our study population comprised 1743 adults (men and women ≥ 18 years of age) with COVID-19 admitted to any of the 30 MOH hospitals in the 13 administrative regions of KSA. We investigated the mortality rates of inpatients with confirmed moderate-to-critical COVID-19 as defined by the MOH between March 2020 and mid-July 2020. A specific protocol was used to classify patients with COVID-19 in the KSA. The MOH provided classification protocols for the severity of COVID-19 cases based on the Centers for Disease Control (CDC) as follows: critical - respiratory failure, severe - low oxygen saturation, moderate - adequate oxygen saturation in the presence of lower respiratory disease, and mild - asymptomatic .Healthcare settings in KSAThe KSA is divided into 13 administrative regions that currently serve a population of 34,218,169 with a blend of public and private sectors. During the COVID-19 pandemic, all COVID-19 patients were treated free of charge at Public Health Healthcare Centers (PHCCs), which include both public and private hospitals. The 30 MOH hospitals were distributed throughout the present 13 health administrative regions of the KSA. We aggregated the data into the five proposed BUs that will be constituted under Vision 2030 to simulate mortality rates and quality-of-care projections under the new model of care (MOC).Data source and measures MOH electronic medical record (EMR) data on COVID-19-related mortality was reviewed and utilized. Data obtained for this study included the hospital clinical course . The primary outcome was COVID-19-related inpatient death and was coded as a binary variable for analysis purposes as follows: 0 = did not die in a hospital, and 1 = did die in a hospital. Covariates included the three categories of patient demographics, pre-existing chronic diseases, and COVID-19-related complications. Demographics included age, sex, and nationality. Pre-existing diseases included DM2, hypertension (HTN), cardiac diseases, obesity, acute respiratory distress syndrome (ARDS), and others. Complications from COVID-19 included ARDS, bacterial pneumonia, sepsis, multiorgan failure, and others. The BU or main region in which a patient was admitted was the main independent categorical variable of interest. BUs were coded as follows: 0 = Central (Riyadh and AL Qassim regions), 1 = Eastern (Sharqiyah region only), 2 = Western , 3 = northern , and 4 = Southern .Statistical analysis Data were analyzed using several statistical techniques as appropriate. The means and standard deviations of continuous variables were assessed using one-way ANOVA and independent samples t-test. The Chi-square test was used to compare the proportions of categorical variables. The primary outcome, COVID-19 mortality, was analyzed using multivariate and univariate logistic regression because of its dichotomous nature. Univariate analysis was conducted for BUs only because they were our primary focus. To understand the reasons behind any differences in mortality rate, we used multivariate analysis, where the covariates included sex, nationality, age group, history of chronic diseases, complications, and length of stay. We selected the central BU as a reference point because it has the most available resources, such that any resource disparity would be more discernible. STATA-14  statistical software was used for data analysis, and all tests were two-sided with statistical significance set at a p-value < 0.05.Ethical considerationThis study was conducted as per the National Committee of Bioethics (NCBE) guidelines, Saudi Arabia. Further, the Central Institutional Review Board provided ethical approval of the Saudi MOH study (reference number: 20-163E). The study relied on secondary data collected from the MOH, and the privacy and confidentiality of the data were strictly maintained. All data were fully anonymized before accessing them and the national NCBE waived the requirement for informed consent since data were retrieved from medical records.Table Table Table Among the deceased inpatients, there were statistically significant differences between those who had comorbidities and underwent ICU admission and those who did not. Compared to deceased inpatients not admitted to ICU, those admitted to ICU had 30 times the mortality rate (p <0.001). Compared to the deceased inpatients who did not have ARDS on admission, those admitted with ARDS had three and a half times the mortality rate (p <0.001). Compared to deceased inpatients without pulmonary diseases, obesity, cardiac disease, and immunocompromised conditions, those having such pre-existing conditions had nearly twice the mortality rate; moreover, they had more than one and a half times the mortality rate if they had HTN or diabetes.The prevalence of complications was significantly associated with the mortality rate. Compared to deceased inpatients without complications, those with the following complications had significantly higher mortality rates: ARDS (10 times), sepsis (5 times), multi-organ failure and acute kidney injury (4.5 times), gastrointestinal tract perforation and arrhythmia (approximately 3.5 times), hepatotoxicity (3 times), and bacterial pneumonia (2.3 times). Deceased inpatients were on average 11 years older than non-deceased inpatients, and they had a significantly longer hospital stay .The results of univariate and multivariate logistic regression analysis Table  suggesteThe new MOC's goal is to ensure that all Saudis have access to the best and most efficient quality of care while maintaining cost-effectiveness in a sustainable value-based healthcare system . This stA possible cause of this disparity is the present structure of healthcare in the KSA. All healthcare facilities are under the administration of the MOH, making them too large and cumbersome to manage efficiently. Saudi Arabia has already undertaken an initiative to restructure the healthcare system with a new Model of Care that will make each BU accountable for equitable access to a high quality of care in all regions within the unit. This simulation will also be instructive as a model for global attempts to restructure healthcare systems to be more responsive and resilient when the next crisis hits. The purpose of healthcare systems is to treat patients with the best standard of care on time. Crises such as pandemics highlight the weaknesses in healthcare systems and, if viewed as instructional, can reform our systems to be several magnitudes better.Our study's 30% mortality rate is higher than that from a study conducted at King Saud University Center Hospital, showing a mortality rate of 17.5% but shares the findings that variations in healthcare quality were observed in the KSA . Three fConsistent with other studies, our data showed a significantly higher risk of death in COVID-19 inpatients with pre-existing obesity and the COVID-19 complications of sepsis and multiorgan failure , 35. AmoRegarding the trajectory of the COVID-19 pandemic, global COVID-19 mortality rates were clearly affected by the timing and severity of infection rates and changed from pandemic phase to phase, for example, the experience in Italy and the UK where there were tremendous changes in mortality rate due to changes in preventive measures and treatment protocols , 39. ForThis is the first study to investigate COVID-19-related mortality as a measure of the quality of healthcare among all five BUs in the KSA, however, international studies have revealed regional disparities in mortality rates for other coronaviruses , 11. TheThe KSA has introduced Vision 2030, which intends to pursue a new MOC for the entire country. With demographic changes and increasing non-communicable diseases, the demand for more advanced healthcare services continues to rise throughout the KSA, and current projections foresee 44% of the population being over 40 and 14% over 60 by 2035 . The exiStrengths and limitationsThe interpretation of our findings needs to be tempered due to certain limitations. As COVID-19 spread throughout the KSA in the first few months, different regions had peak morbidity rates at varying times. Therefore, a snapshot of inpatient cases for a four-and-a-half-month period might not have captured an accurate picture of each BU. Factors other than those included in our studies, such as infrastructure or staffing, might have been associated with mortality rate. Finally, our research's cross-sectional nature limited the relationship between the variables; hence, could not deduce causality. To offset these limitations, the inclusion of inpatient characteristics regarding demographics, comorbidities, and COVID-19 complications rendered a high degree of validity to our study by adjusting for important health factors that could account for differences in mortality between the BUs. Therefore, the findings of our study potentially serve as a baseline for healthcare quality differences that will need to be considered when assessing BU performance under the new MOC of Vision 2030.Healthcare systems have been designed to treat patients who come into the system one at a time, even during times like flu season. However, the beginning of the SARS-CoV-2 pandemic resulted in large numbers of infected people requiring hospitalization simultaneously, overwhelming the capacity of both human and technical resources leading to excessive mortality. Although the pandemic challenged the healthcare system in the KSA, it did not become so overwhelmed that it collapsed like many others globally. Nevertheless, mortality rate variations across the five BUs appear to be related to healthcare quality disparities. The mean COVID-19 related mortality rate for all participants during our study period was 30%, with extremes ranging from a low of 8% to a high of 53%. Even after controlling for important patient and disease covariates, these factors could not explain this disparity in COVID-19 mortality rates, providing additional evidence that healthcare quality variation was the primary explanation for the differences in healthcare outcomes. Further investigation is required to identify the specific structural; resource, including both human and non-human; as well as distributional factors associated with regional differences in healthcare quality. Additional research should include longitudinal studies through December 2020 to verify the variations between BUs. This study provides the impetus to initiate the needed changes to realize the full potential of the new Model of Care under privatization.


We aimed to assess prevalence of IgG antibodies to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and factors associated with seropositivity in a large cohort of healthcare workers (HCWs).From 11 May until 11 June 2020, 3981 HCWs at a large Swedish emergency care hospital provided serum samples and questionnaire data. Presence of IgG antibodies to SARS-CoV-2 was measured as an indicator of SARS-CoV-2 exposure.The total seroprevalence was 18% and increased during the study period. Among the seropositive HCWs, 11% had been entirely asymptomatic. Participants who worked with COVID-19 patients had higher odds for seropositivity: adjusted odds ratio 1.96 . HCWs from three of the departments managing COVID-19 patients had significantly higher seroprevalences, whereas the prevalence among HCWs from the intensive care unit  was significantly lower.HCWs in contact with SARS-CoV-2 infected patients had a variable, but on average higher, likelihood for SARS-CoV-2 infections. On 27 February 2020 the first confirmed case of infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Stockholm, Sweden was diagnosed . The num3Supplemental Figure). Guidelines recommended the use of face shields, face masks and plastic aprons during direct contact with patients suspected to be infected. Aerosol filtering face masks were recommended during aerosol generating procedures, and in the intensive care unit (ICU). HCWs who experienced any symptoms of infection were advised to stay at home until feeling well for at least two days but were not routinely tested for SARS-CoV-2 during this period. HCWs who had an ongoing SARS-CoV-2 infection confirmed with a PCR test were to follow the same guideline and stay at home at least one week following onset of symptoms.This cross-sectional study was initiated as a part of a regional study of HCWs conducted in the major emergency care hospitals in Stockholm. Stockholm South General Hospital (Södersjukhuset) has one of the largest emergency care departments in Northern Europe with about 550 in-patient beds. The hospital provides both general and specialized acute as well elective care. From 27 February 2020, when the first case was verified in the region, until 30 June 2020, 1384 patients with confirmed SARS-CoV-2 infection had been admitted to the hospital  and self-suspicion of prior SARS-CoV-2 infection were collected on questionnaires at the time of sampling.Serum samples were prepared from whole blood, inactivated at 56°C for 30 min and stored at −20°C until analysis. IgG reactivity was measured towards three virus protein variants: spike trimers comprising the prefusion-stabilized spike glycoprotein ectodomain , spike SResults are presented as prevalence. Association between a seropositive test and age (categorized as < 40 years and ⩾ 40 years), sex , date of test  and active work with COVID-19 patients  was examined in multivariable logistic regression model and presented as odds ratio (OR) with 95% CIs. To analyse if workplace was associated with seroprevalence each department was related to all other hospital departments in separate regression models adjusted for age (continuous), sex , date of test (first/second/third to fifth week) and active work with COVID-19 patients (no/yes/do not know). Statistical analyses were performed in R  using thn = 26) had missing data in one or several of the variables collected on the questionnaire. Participants had a mean age of 45 years, 81% were female, and 64% responded that they had worked with patients with confirmed or suspected COVID-19 . Of all participants, 0.7%  were seropositive for IgG antibodies against SARS-CoV-2. The prevalence increased during the test period  and was Seroprevalence differed between departments: HCWs within the departments of Cardiology, Infectious Diseases and Internal Medicine had higher odds of being seropositive compared to HCWs at the rest of the hospital after adjustment for sex, age, date of test and active work with COVID-19 patients . In contSelf-reported suspicion of COVID-19 symptoms prior to the study was associated with higher prevalence of a positive test, 46% compared to 5.5% among HCWs who had not suspected previous infection. Among the seropositive HCWs, 11% had been asymptomatic (no suspicion of a previous SARS-CoV-2 infection).This study found a prevalence of 18% of IgG antibodies against SARS-CoV-2 among HCWs in a large cohort of HCWs from Stockholm, Sweden sampled during the later phases of the first wave of the epidemic. The seroprevalence was similar to the 19% reported among 2149 HCWs at Danderyd Hospital, a hospital of equivalent size in the Stockholm area , whereasSelf-reported high suspicion of infection has previously been associated with seropositivity –13. In oAs in previous studies –5, an inInterestingly, as in the study by Grant et al. , HCWs atDuring the spring, many HCWs were relocated within the hospital. Current workplace was self-reported, and a limitation of this study is that we were not able to fully distinguish primary (regular) workplace from workplace during the period of interest. Furthermore, we did not collect information regarding use of protective equipment or other potential exposures such as contact with infected persons outside work or with infected HCWs at work. The participation rate was high, but we do not have information enabling a description of non-participants. It is likely to believe that employees on parental leave and long-term sick leave to a high degree did not participate in the study since the sample collection was performed at the hospital. Comorbidities have been related to severe COVID-19 disease . In thisThe number of COVID-19 patients admitted to our hospital peaked in the weeks before this study. The fact that the seroprevalences increased with calendar time suggests that the first wave of the epidemic was still ongoing during the time of this study. However, PCR testing for the virus was not performed.The prevalence of SARS-Cov-2 IgG antibodies was higher in HCWs caring for COVID-19 patients. However, the risk was highly variable between departments suggesting that other factors are important for the risk of the infection.Click here for additional data file.Supplemental material, sj-tif-1-sjp-10.1177_14034948211022434 for Risk of SARS-CoV-2 exposure among hospital healthcare workers in relation to patient contact and type of care by Susanna Klevebro, Fuad Bahram, K. Miriam Elfström, Ulrika Hellberg, Sophia Hober, Simon Kebede Merid, Inger Kull, Peter Nilsson, Per Tornvall, Gang Wang, Kalle Conneryd Lundgren, Sari Ponzer, Joakim Dillner and Erik Melén in Scandinavian Journal of Public Health


HumanNet v3 supports a three-tier model: HumanNet-PI , HumanNet-FN , and HumanNet-XC . Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19.Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein–protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene–phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 ( Functional relations between highly wired genes underlie complex phenotypes of organisms. Hence, life scientists have tried to delineate interactions between genes and their products through diverse experimental and computational approaches. The integration of interactions inferred from various datasets and methods generally increases the reliability and coverage of a gene network . Many inhttps://www.inetbio.org/humannet/), which showed a significant performance improvement because of the inclusion of the new data and better network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI , HumanNet-FN , and HumanNet-XC . Users can select an appropriate tier of the network for their purpose of a study. Using multiple sources of disease gene annotations, we proved that HumanNet v3 outperforms HumanNet v2 and other integrated networks of human genes. In addition, we demonstrated that HumanNet-based prediction can prioritize human genes that are highly likely to be associated with COVID-19, suggesting its usefulness in COVID-19 research.Advanced high-throughput technologies accelerated data generation further and accumulated large amounts of functional 'omics data during the past few years. Therefore, updating HumanNet is a timely task for further improvement of network-based predictions of disease genes. Here, we present HumanNet v3 , domain profile association (DP), and GI were also improved by the enlarged data sources. Recently, the phylogenetic tree of prokaryotic species was expanded significantly by the addition of species identified by means of metagenome-assembled genomes ,21. HumaInterologs , proteinUsers may benefit from a network more appropriate for their research purpose. For example, a protein–protein physical interaction network will be more suitable for mode-of-action studies of disease mutations, and a network with no CC links may reduce over-evaluation of disease gene prediction by the literature bias toward disease studies. The previous HumanNet was based on four tiers including networks that contain interologs. As interologs are no longer incorporated into HumanNet, we offer a three-tier model for HumanNet v3: HumanNet-PI (protein-protein interaction network), HumanNet-FN , and HumanNet-XC (gene network extended by CC) Figure . HumanNeThe increases of each component network led to significant expansion of the integrated networks. The most inclusive network, HumanNet-XC, contains 1 125 494 links, which is more than twice the number of links for the largest HumanNet v2 (525 537 links). The coverage of the human protein coding genome also increased from 17 929 in HumanNet v2 to 18 462 genes in HumanNet v3, thereby covering 99.8% of protein coding genes of the consensus coding sequence (CCDS) r22 .Next, we systematically evaluated HumanNet v3 for disease gene predictions. We compared the previous HumanNet v2) with full size (XN)  and the  with fulWe first measured the percentage of links that shared the same disease annotations and the coverage for the disease gene set. For DisGeNET disease genes, among the three tiers of HumanNet v3, HumanNet-XC showed the highest precision, followed by HumanNet-FN and HumanNet-PI Figure . CompareP < 0.0001, two-tailed Mann–Whitney U test). Because network size also contributes to network-based gene prioritization, STRING may compensate for its lower network precision  analysis, and its results can be summarized as the area under the ROC curve (AUROC). Because we generally consider only the top hundreds of candidates for follow-up functional analysis, the AUROC for early retrieval is practically more important. Therefore, we assessed the disease predictions based on the AUROC up to a false positive rate of 1%. We found that HumanNet-XC and STRING share the first place in terms of performance among all the tested networks for the comparison with disease genes annotated by both DisGeNET and GWAS Catalog Figure , D. DiseThe HumanNet v3 web server largely inherited the user interface from the previous version. On the other hand, there are major improvements in network information. The most important update is the inclusion of literature data from PubMed that support PI and CC associations. In addition, all disease annotations were updated by means of the latest versions.We continue to offer two prediction modules on the HumanNet v3 web server: network-based disease gene prediction and network-based disease annotation prediction. In the network-based disease gene prediction, a user submits a known gene set, dubbed guide genes, for a disease of interest. Then, the user can examine network neighbors of the guide genes in a network view. The network view is implemented interactively; accordingly, the user can obtain detailed information on a link or gene of interest by selecting an object. In HumanNet v3, we reinforced the link information by presenting supporting evidence (publications) for PI and CC links. Next, the web server outputs metrics of how much the guide genes are interconnected in the network and predictive power of HumanNet for the guide genes according to ROC analysis. The web server also presents candidate genes for the given diseases; the genes are sorted by network prioritization scores. In network-based disease annotation prediction modules, a user submits a query gene(s). After that, the web server predicts the diseases potentially associated with the query gene by retrieving disease annotations from its neighbors. HumanNet v3 web server provides the latest versions of five gene annotation databases for pre-defined guide genes and prediction interpretation: GOBP , GWAS Cahttps://covid19.who.int/). Many human genes are involved in infectious diseases. Therefore, identification of host genes associated with COVID-19 will facilitate development of strategies for its prevention and treatment. To demonstrate the utility of HumanNet in COVID-19 study, we performed web-based disease gene prediction with guide genes that are known to be associated with COVID-19. Recently, international consortium of COVID-19 Host Genetics Initiative published results from genome-wide association studies (GWAS) comprised >49 000 patients (P < 0.0001 by permutation test). HumanNet-XC prioritized a total of 4418 candidate genes by connection to the 43 guide genes.COVID-19 is a highly contagious disease by severe acute respiratory syndrome coronavirus (SARS-CoV-2), resulting in more than 4.7 million deaths worldwide as of September 2021 (patients . We compTo confirm the validity of the network-based gene prediction, we utilized a community-wide collection of 722 COVID-19 related gene sets  derived In this report, we present an updated HumanNet version with major expansion of network information. Interologs were not integrated into HumanNet v3 because we noticed a decrease in the accuracy of the network for disease gene associations. This finding implies that protein-protein interaction mapping during the past few years filled out a large portion of the human interactome, which has been supplemented by network information transferred from other species only. Despite the exclusion of interologs, we expanded HumanNet by more than twofold as compared to the previous version. We found that HumanNet v3 outperforms both the previous HumanNet and most of the integrated human gene networks currently available publicly. Finally, we demonstrated that HumanNet can predict host genes associated with COVID-19. These results together support that the improved HumanNet will continue to provide an effective resource for the study of a wide variety of human diseases.https://www.inetbio.org/humannet. The data can be accessed through the following web browsers: Google Chrome, Microsoft Edge, Apple Safari, Mozilla Firefox.HumanNet v3 is available under the Creative Commons Attribution-ShareAlike 4.0 International License at gkab1048_Supplemental_FilesClick here for additional data file.


The emerging novel coronavirus disease 2019 (COVID-19) has become one of the leading cause of deaths worldwide in 2020. The present systematic review and meta-analysis estimated the magnitude of sleep problems during the COVID-19 pandemic and its relationship with psychological distress.Scopus, PubMed Central, ProQuest, ISI Web of Knowledge, and Embase) were searched. Observational studies including case-control studies and cross-sectional studies were included if relevant data relationships were reported . All the studies were English, peer-reviewed papers published between December 2019 and February 2021. PROSPERO registration number: CRD42020181644.Five academic databases . Sleep problems were associated with depression among healthcare professionals, the general population, and COVID-19 patients, with Fisher's Z scores of -0.28, -0.30, and -0.36, respectively. Sleep problems were positively (and moderately) associated with anxiety among healthcare professionals, the general population, and COVID-19 patients, with Fisher's z scores of 0.55, 0.48, and 0.49, respectively.168 cross-sectional, four case-control, and five longitudinal design papers comprising 345,270 participants from 39 countries were identified. The corrected pooled estimated prevalence of sleep problems were 31% among healthcare professionals, 18% among the general population, and 57% among COVID-19 patients (all Sleep problems appear to have been common during the ongoing COVID-19 pandemic. Moreover, sleep problems were found to be associated with higher levels of psychological distress. With the use of effective programs treating sleep problems, psychological distress may be reduced. Vice versa, the use of effective programs treating psychological distress, sleep problems may be reduced.The present study received no funding. The novel coronavirus disease 2019 (COVID-19) pandemic has caused psychological problems and sleep problems in different populations, including healthcare professionals, COVID-19 infected individuals, and the general population.Patients with COVID-19 infection had the highest prevalence of sleep problems, and healthcare professions had the second highest prevalence of sleep problems. Moderate associations between sleep problems and psychological distress (including depression and anxiety) were found.Patients with COVID-19 infection and health professions are at risk of having sleep problems, and that there are moderate associations between sleep problems and psychological distress.These data emphasize the need of programs and treatments to assist different populations in overcoming sleep problems and psychological distress, especially patients with COVID-19 infection and health professions.Alt-text: Unlabelled box1Prior to 2020, respiratory diseases were the fourth leading cause of death Prior research has found that the prevalence of COVID-19 is associated with major psychological distress and significant symptoms of mental health illness In addition to healthcare workers, the general population is likely to develop mental health and sleep problems due to the impacts of COVID-19 Different factors contributing to insomnia and psychological problems have been reported. The most important risk factors for insomnia and mental health problems during the COVID-19 pandemic are being a healthcare worker, having an underlying illness, living in rural areas, being a woman, and being at risk of contact with COVID-19 infected patients. Among non-medical healthcare workers, having an underlying disease is a risk factor for insomnia and mental health problems p<.01). Wang et al. reported higher prevalence of sleep problem among medical staff compared to non-medical staff comprising students, community workers, and volunteers  and frontline healthcare providers compared to non-frontline medical workers  Because sleep is important for human beings to maintain daily functions The quality of sleep during the COVID-19 pandemic and its related factors have been reported in an increasing number of studies. A recent study conducted a meta-analysis to understand the sleep problems during the COVID-19 pandemic 2The present systematic review was conducted utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines 2.1Scopus, PubMed Central, ProQuest, ISI Web of Knowledge, and Embase were searched systematically between February 17 to 19, 2021. The search terms were extracted from published reviews and primary studies in addition to PubMed Medical Subject Headings (MeSH). The main search terms were ‘sleep’ and ‘COVID-19’. The Boolean search method (AND/OR/NOT) was used to develop the search. Search syntax was customized based on the advanced search attributes of each database. The full search strategy for each database is provided in Supplementary Table 1. Additionally, further sources  were searched to increase the likelihood of retrieving relevant empirical studies.Five academic databases including 2.22.6 Data synthesis). English, peer-reviewed papers published between December 2019 and August 2020 were included. There were no limitations regarding participants’ characteristics.Observational studies including case-control studies and cross-sectional studies were included if relevant data relationships were reported . More specifically, if the studies were included if they estimated the prevalence of sleep disorders and/or examined the relationship between sleep and psychological distress using Pearson's correlation coefficient , extrinsic , and disturbances of circadian rhythm. Sleep problems had to have been assessed using valid and reliable psychometric scales or confirmed with defined cut-off points for characterizing as sleep problems. More specifically, Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to assess the primary outcomes because PSQI and ISI have items assessing the three major subcategories of the aforementioned sleep problems. For instance, a global score of 5 or more indicates poor sleep quality on the Pittsburgh Sleep Quality Index [44]2.2.2“a state in response to stressors marked by perceived discomfort and inability to cope”There were three secondary outcomes: (i) association of sleep problems with psychological distress in the context of the COVID-19 pandemic; (ii) heterogeneity and its possible sources; and (iii) moderator variables in association of sleep problems and psychological distress related to COVID-19 pandemic. Ridner defined psychological distress (PD) as: 2.3In the first step, title and abstract of all retrieved papers were screened independently by two researchers based on the inclusion criteria. The full texts of potentially relevant studies were further examined based on the aforementioned criteria. In this process, relevant studies were selected.2.4The Newcastle Ottawa Scale (NOS) was used to evaluate the methodological quality of the studies in observational studies. Three characteristics  were examined with the NOS checklist. The checklist has three versions for evaluating cross-sectional studies (seven items), case-control studies (eight items), and cohort studies (eight items). Despite a slight difference in number and content of items, each item is rated with a star, except comparability which can have two stars. This results in a maximum quality score of 9 for each study. Studies with less than 5 points are classified as having a high risk of bias 2.5A pre-designed form was prepared to extract data from included studies. Data including first author's name, collection date, study design, country, number of participants, gender, mean age, scales used to assess psychological distress and sleep problems, numerical results regarding the frequency of sleep problems, and relationship between sleep problems and psychological distress. It should also be noted that study selection, quality assessment, and data extraction were processes performed independently by two reviewers. Disagreements were resolved through discussion.2.62 index. Heterogeneity is interpreted as (i) mild when I2 is less than 25%, (ii) moderate when I2 is 25 to 50%, (iii) severe when I2 is 50 to 75%, and (iv) highly severe when I2 is greater than 75% A quantitative synthesis using STATA software version 14 was conducted. Meta-analysis was run using random effect model because included studies were taken from different populations, and both within-study and between-study variances should be accounted for Psychometrica website r correlation coefficient was converted to Fisher's z, due to the potential instability of variance. Consequently, all analyses were performed using Fisher's z values as effect size (ES) . p=0.12) and funnel plot (p<.001). Funnel plot after trimming is provided in The pooled estimated prevalence of sleep problems among healthcare professionals was 43% . The pooled estimated prevalence of sleep problems among the general population was 37% . However, a moderate correlation was found between sleep problems and anxiety with Fisher's z score of 0.55 . The forest plots are shown in The association of sleep problems with depression and anxiety among health professionals were reported in 14 and 15 studies respectively. The pooled estimated effect size showed poor correlation between sleep problems and depression with Fisher's z score of -0.28 . Also, a moderate correlation was found between sleep problems and anxiety with Fisher's z score of 0.54 . The forest plots are shown in The association of sleep problems with depression and anxiety among the general population were reported in 15 and 12 studies respectively. The pooled estimated effect size showed moderate correlation between sleep problems and depression with Fisher's z score of -0.30 [95% CI: -0.32 to -0.28, p=0.52). Although publication bias was not significant in association between sleep problems and anxiety (p=0.41), based on funnel plot, publication bias was probable. Consequently, fill and trim method was used to correct probable publication bias. After imputation of three studies, the association between sleep problems and anxiety was estimated as Fisher's z score of 0.48 (95% CI: 0.41 to 0.54).Based on Begg's test, publication bias and small study effect were not found in the association between sleep problems and depression  and healthcare professionals (43%). These findings concur with Jahrami et al. The nonsignificant finding for gender contradicts prior evidence showing that being female is a risk factor for insomnia and mental health problems , 56. ThiThe high prevalence of sleep problems found in the present review can be explained by fear of COVID-19 and sleep-related factors  Lockdown was found to be a significant factor in explaining sleep problems. However, this finding may be confounded by the different policies implemented to inhibit the spread of COVID-19 across the 39 countries analyzed in the present review. For example, mainland China launched a strict lockdown policy to prohibit almost all outdoor activities, while the lockdown policy in other countries was not as strict. Nevertheless, the present findings support prior evidence that lockdown negatively impacted individuals’ psychological health and sleep vice versa). Third, special attention may need to be paid to COVID-19 patients and older individuals because the present review showed a higher association between their sleep problems and psychological distress. Moreover, specific populations such as children and their caregivers should not be ignored regarding their psychological needs and sleep issues. Although the present review did not provide evidence on pediatric populations, the present findings concerning the specific group of older individuals may generalize to other specific populations. It is recommended that programs comprising psychological support for family having children to overcome the difficulties during COVID-19 pandemic are implemented There are several clinical implications from the present study's findings. First, government and healthcare providers worldwide need to design and implement appropriate programs and treatments to assist different populations, including healthcare professionals, patients, and the general population, in overcoming sleep problems. For example, effective programs  The present review has some strengths. First, the prevalence of sleep problems has been estimated across different populations and this information provides healthcare providers with a greater and more contextualized picture regarding the impacts of COVID-19 on sleep problems. Second, methodological quality of each analyzed study was assessed using the NOS checklist. Within the meta-analysis findings, subgroup analysis and meta-regression were used to provide thorough information and therefore the meta-analysis findings are robust. Third, generalizability of the present review's findings is good because the synthesized sample size was large  and the participants were recruited from 39 countries.time effect in the causal relationship. Therefore, the relationships between sleep problems and psychological distress found in the present review do not have strong causality evidence. Diverse evidence in the causality has been proposed. Using longitudinal designs, Vaghela and Sutin changes of sleep problems caused by COVID-19. Second, different measures were used in the studies that were evaluated . Given that different measures may have different features in capturing the severity of sleep problems, there may have some biases in estimating prevalence for sleep problems and effect sizes for the associations between sleep problem and psychological distress. All the studies evaluated here used self-report methods in assessing sleep problems and psychological distress. Therefore, findings in the present review cannot rule out social desirability and memory recall biases. Third, the impacts of COVID-19 on sleep and mental health problems are dynamic. That is, individuals may have different levels of sleep and mental health problems according to the severity of COVID-19 outbreak in their localities or countries. Moreover, the policies in controlling the COVID-19 outbreak are different across countries [The present review has some limitations. First, most of the studies adopted a cross-sectional design (n=56) and only seven studies  considered the ountries . TherefoIn conclusion, sleep problems appear to have been common during the COVID-19 pandemic. One in every three individuals reported the sleep problems. Nearly half of the healthcare professionals (43%) encountered sleep problems during the pandemic period. Healthcare providers may want to design appropriate programs to help individuals overcome their sleep problems. Moreover, sleep problems were found to be associated with higher levels of psychological distress (including depression and anxiety). Therefore, with the use of effective programs treating sleep problems, psychological distress may be reduced. Vice versa, the use of effective programs treating psychological distress, sleep problems may be reduced. However, it is possible that the association between sleep problems and psychological distress found in the present review is contributed by confounders. In other words, causality may not be happened between sleep problems and psychological distress. Therefore, more longitudinal studies and randomized controlled trials are needed to investigate the causality between sleep problems and psychological distress.Chung-Ying Lin was supported in part by a research grant from the Ministry of Science and Technology, Taiwan (MOST109-2327-B-006-005). All other authors have nothing to declare.


Coronavirus disease 2019 (COVID-19) has a myriad of different presentations and various complications. Aortitis is one of the less explored pathologies associated with COVID-19 infections. In this review, we searched PubMed/Medline, Web of Science, Google Scholar, and Scopus for case series and case reports involving adults patients who presented with aortitis and COVID-19. We found and reviewed four published case reports of aortitis in a setting of COVID-19 infection. The mean age of the four adult patients was 69 ± 1.732 years (range = 63-71 years), and all patients were males. Most of the patients (75%) did not have any preexisting comorbidities. All patients were treated conservatively and recovered with excellent outcomes. A novel coronavirus, first reported in Wuhan, China, on December 31, 2019, emerged to become a global pandemic, as declared by the World Health Organization (WHO) in March 2020. According to the Centers for Disease Control and Prevention, the illness caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can manifest in different organ systems, with a severity ranging from a mild to life-threatening illness. In 2020, coronavirus disease 2019 (COVID-19) was the third leading cause of death in the United States [Salmonella and Staphylococcus aureus infections is the most common form of infectious aortitis, whereas non-infectious aortitis includes Takayasu arteritis and giant cell arteritis [Aortitis is a pathologic term referring to all infectious and non-infectious conditions that lead to the inflammation of the aortic wall . Patientrteritis .Infectious aortitis refers to any inflammatory process of the aortic wall involving an infectious agent . Aortic MethodologyWe searched PubMed/Medline, Web of Science, Google Scholar, and Scopus until March 19, 2021, for case reports and case series using the following keywords: COVID-19, SARS-CoV-2, aortitis, and large vessel vasculitis. In the final analysis, we only included case reports published in the English language. Eligible case reports and case series were reviewed by two independent researchers, and any conflict was resolved by a third researcher. Our search identified 359 studies in total. After removing duplicates and selecting case reports or case series with individual patient-level data, we identified seven articles. Due to the young age of patients, we further excluded two articles. Another article was excluded due to the lack of viral and serologic evidence of COVID-19 infection. Finally, we included four articles . All patients were males (100%). Two of the reported cases were from the United Kingdom, one was from the United States, and one was from Japan. Race was not included in the analysis because it was not reported in all the case reports. We could not discern a distinct set of comorbidities that might predispose patients to aortitis.Overall, two (50%) patients presented with an active COVID-19 infection detected on polymerase chain reaction with COVID-19 symptoms at the time of presentation, while the other two had serological evidence of past infection with COVID-19. Regarding presenting symptoms, out of the four patients, two (50%) presented with fever. Further, three (75%) patients reported generalized weakness, three (75%) reported pain  (75%), and two (50%) presented with weight loss. Three (75%) patients manifested symptoms that triggered the search for an alternative diagnosis following the resolution of the respiratory symptoms. Physical examination was unremarkable in three (75%) patients and was only significant for abdominal discomfort on palpation in one (25%) patient.Patients consistently presented with a markedly elevated C-reactive protein at the time of diagnosis with a mean of 142.75 ± 23.3 mg/L . The immunologic screen was negative except for elevated immunoglobulin G4 in two patients who presented with an acute COVID-19 infection. CT was used in all four patients to detect inflammation in large vessels, and fluorodeoxyglucose positron emission tomography/computed tomography was performed for one (25%) patient. All four patients failed to illicit an infectious or rheumatologic cause for their aortitis, although one of them tested positive for human leukocyte antigen-DR4.Prednisolone (40 mg and 60 mg) was used in most patients 75% (n = 3), while one patient only received non-steroidal anti-inflammatory drugs (NSAIDs). Resolution of inflammation, as evident on the repeat CT scans, was reported in all four patients, with two patients showing complete resolution . The patDiscussionTo our knowledge, this is the first systematic review of COVID-19 patients developing aortitis. Several viral infections have been linked to aortitis. Fukunaga et al. reported a case of aortitis as a rare complication secondary to hepatitis C virus-associated cryoglobulinemia ,11. It iThe main findings of this review are that all four adult aortitis patients were males and older than 60 years. Only one of the patients had a current history of underlying cardiovascular comorbidities, namely, non-ischemic cardiomyopathy, hypertension, and diabetes. The time of presentation since the acute COVID-19 infection varied widely, with two patients presenting after two months of the acute infection while the other two presenting along with the onset of the acute infection.All three patients who received prednisolone improved rapidly with recovery times of less than two weeks. One patient was treated with NSAIDs because of the fear of COVID-19 reactivation early in the pandemic when data about the disease were lacking. However, he took approximately a month to recover. This highlights the importance of high-dose steroids in the management of aortitis in the setting of COVID-19. Furthermore, this was supported by the duration of symptoms before treatment in the patient who presented after three months of symptom onset and then improved shortly after starting steroids.We noticed that all patients who presented with the acute infection had their disease limited to shorter segments of the aorta on CT compared to patients with late presentation who had a more diffuse type of aortitis involving the entire aorta.Although the mechanism of aortitis in COVID-19 is not yet fully clarified, a histological case series found that SARS-CoV-2 can directly infect endothelial cells, probably through endothelial angiotensin-converting enzyme 2 receptors, causing endothelial inflammation . AlternaLimitationsCOVID-19 is known to produce a hypercoagulable state ; howeverDexamethasone has been shown to be beneficial in COVID-19 infection management  and has We propose screening patients with prolonged generalized symptoms, abdominal discomfort, unexplained persistent spiking fevers, or persistently elevated inflammatory markers for aortitis by abdominal imaging (CT scanning) because this condition is readily treatable in adults. It appears that high-dose steroids are effective in managing aortitis associated with COVID-19 infection. Further studies are needed to confirm this hypothesis; however, clinicians should be aware of this complication when managing COVID-19 patients.