To examine changes in COVID-19 stressors and symptoms of mental disorders in the Republic of Georgia.A longitudinal design was used. Following on from our study of May-June 2020, this follow-up study in January-March 2021 was conducted at: (i)an individual level with the same respondents involved in the May-June 2020 study (repeat responders/cohort); and (ii) at a population-wide level, using non-probabilistic sampling. Questionnaire sections covered: (i)demographic, socio-economic characteristics; (ii)level of burden caused by COVID-19-related stressors/concern; and (iii)symptoms of anxiety(GAD-7), depression(PHQ-9), PTSD(ITQ), adjustment disorder(ADNM8). Descriptive and multivariable regression analyses were conducted.Among population-level survey respondents(N=1195), the probability of reporting mental ill health symptoms increased in 2021 compared to 2020 for PTSD(OR1.82), depression(OR1.40), adjustment disorder(OR 1.80), and marginally for anxiety(OR1.17). For the individual repeat respondents(N=455), the probability increased for depression(OR1.88) and adjustment disorder(OR2.56). The perceived burden of pandemic concern worsened in 2021 compared to 2020 for almost all stressors, particularly around access to health care, infecting others, and conflict in the home. PTSD was associated with an increased concern score from 2020 to 2021. Our study highlights the need to strengthen response strategies to address the elevated mental health needs related to COVID-19 in Georgia. It recommends increasing accessibility of early interventions and the need to modernise mental health services to strengthen access to care. It also calls for monitoring patterns of mental health disorders for better understanding and responses to mental health needs in Georgia. The physical distancing measures can cause social isolation and a breakdown of social networks  while thThe Republic of Georgia took early public health measures to limit the spread of COVID-19 from early 2020 onwards, and this helped to suppress the virus when case numbers were still manageable, but this suppression was less successful by late 2020, which experienced a rise in cases and the re-introduction of public health strict measures to limit the spread of COVID-19 (see Supplementary File 1 for further information on these measures) , 16. The2A longitudinal design was used. Following on from our previous internet-based cross-sectional study in May-June 2020 using non-probabilistic sampling of the general population in Georgia aged 18 years and above [1). Second, questions on the level of the burden caused by COVID-19 related concerns (19 stressors) over the previous month , with response options ranging from ‘no concern at all’ (=1) to ‘strongly burdened’ (=4) resulting in a score range from 19 to 76. Third, symptoms of anxiety ; adjustscore >9 , 24), anscore >9 . DetailsEthics approval was provided by the National Centre for Disease Control and Public Health in Georgia.2.11) were compared using Chi-sq tests for the populations and exact McNemar tests for individual repeat responders. For the analysis of changes from 2020 to 2021 in perceived burden and mental health outcomes, multivariable regression analysis was used (Table 2), and unique IDs for each respondent were generated so the regressions could identify multiple responses belonging to the same individual. In this way, the population and individual results were pooled and modelled together to increase the power to detect effects. The population results were generated using a logistic regression model with cluster robust standard errors, where the ‘cluster’ is each individual. The ‘population change’ in outcomes from 2020 to 2021 was adjusted for age, sex, education, living location, perceived household economic situation and previous diagnoses of mental disorders. For the analysis of individual repeat responders, results were from a mixed-effects logistic regression model, adjusted for the same variables but with an additional ‘random intercept’ parameter to account for the non-independence of outcomes in the same individuals. This changes the interpretation so that the adjusted effect is for ‘an individual’s change’ in outcomes from 2020 to 2021.Descriptive data between the 2020 and 2021 studies (Table 2) after correcting for differences between the whole population and our survey populations. These proportions were calculated using coefficients estimated in the ‘population’ model: they represent the probabilities of a randomly selected individual in Georgia having each outcome. We calibrated the probabilities so that the age, sex and living location represent their distribution in the Georgian population  based on Georgian census data [i.e., used the observed proportions in this calculation).With the pooled data, we also estimated the proportion of the Georgian population having each COVID concern and symptoms of mental disorders  and a random slope  and an unstructured covariance between the random effects. The model adjusted for factors that may be associated with changes in covid concern score . The sample characteristics are provided in Table At the survey population level, levels of PTSD symptoms were higher in 2021 (24%) than 2020 (12%) (P<0.0001). Similarly, depression symptoms were higher at the population level in 2021 (33%) compared to 2020 (30%) (P=0.031), and this was the case for adjustment disorder symptoms as well . Anxiety symptoms were stable between the two years. For the individual repeat respondents, only adjustment disorder was significantly higher in 2021 (49%) compared to 2021 (39%) (P<0.0001).2), more change was evident. The probability among population-level survey respondents of reporting PTSD symptoms increased in 2021 compared to 2020 , along with depression , and adjustment disorder , while anxiety was only marginally higher . For the individual repeat respondents, the probability increased in 2021 compared to 2020 for reporting depression  and adjustment disorder . The probability of anxiety and PTSD symptoms did not show a statistically significant change between 2020 and 2021, although both were estimated to be higher in 2021. Pooled across both years and adjusted for other model factors, there were more symptoms of anxiety, depression and adjustment disorder in women compared to men and in 18-39-year-olds compared with the older age groups, and more symptoms of PTSD in 18-39-year-olds (not shown).However, after adjusting for differences in key demographic and socio-economic variables in multivariable regression analysis (Table 2) – were slightly lower than the observed estimates of 24%, 33%, 24% and 52% (Table 1). However, the increase in these symptoms from 2020 to 2021, as calculated from the re-calibrated change, is greater than the observed increase for all disorders except for PTSD, where the re-calibrated increase was slightly less than the observed data.After calibrating the probabilities of each disorder to the age, gender and living location distributions of the Georgian population, we estimated that the 2021 burden of anxiety, depression, PTSD, and adjustment disorder – 20%, 30%, 21% and 51%, respectively (Table 2). At the population-level, the probability of reporting a concern in 2021 compared to 2020 was highest for: ‘insufficient capacity of intensive care’ ; ‘access to routine health care’ ; ‘poor information from authorities about COVID-19 and related measures’ ; and ‘concern of infecting others with COVID-19’ . Among individual repeat responders, the probability of increased concern in 2021 compared to 2020 was highest for concerns about: ‘conflict at home’ ; ‘child care’ ; ‘insufficient capacity of intensive care’ ; concern of ‘infecting others with COVID-19’ , and ‘poor information from authorities’ . Only concern for ‘income loss’ significantly improved from 2020 to 2021, while some other specific concerns were not significantly different between 2020 and 2021 . In general, pooled across both years and adjusted for other factors in the models, there were higher levels of concern for most measures in women compared to men and in 18-39-year-olds compared with the older age groups, though not all comparisons were statistically significant (not shown). In 2021, we estimated the greatest absolute population burden  to be ‘loved ones getting infected with COVID-19’ (69%), followed by ‘infecting others with COVID-19’ (62%) and ‘restricted contact with family and friends’ (49%).The burden of concern about COVID-19 worsened in 2021 compared to 2020 for both population survey respondents and individual repeat responders for the majority of the causes of concern  and symptoms of anxiety  were associated with a reduction in COVID-19 stressors score from 2020 to 2021. Conversely, having symptoms of PTSD was associated with increased COVID-19 concern from 2020 to 2021 . The results of the full linear mixed model of factors associated with changes in COVID-19 concern between 2020 and 2021 are provided in Supplementary File 3.Three factors were independently significantly associated with 4We found persistently high levels of symptoms of mental disorders, with the probability increasing in 2021 compared to 2020 for anxiety, depression, PTSD and adjustment disorder for the population-level study, and for depression and adjustment disorder for individual repeat responders/cohort members. The burden of mental disorders associated with COVID-19 is also evidenced in studies from other countries , 7, 8, aIt is noteworthy that respondents in our study repeatedly reported high levels of adjustment disorder symptoms (40% in 2020 and 52% in 2021). Research on adjustment disorder during COVID-19 is rather scarce despite researchers expressing concern about it due to COVID-19 . We wereSeveral studies also indicated the changed trajectories of common mental disorders during the pandemic and related factors such as living in areas affected by lockdowns, struggling financially, having pre-existing conditions, or infection with COVID-19, while other studies documented a small increase in mental health symptoms soon after the outbreak of the COVID-19 pandemic that then decreased and was comparable to pre-pandemic levels by mid-2020. A recent study pointed to a significant decrease in depression and anxiety symptoms after the first shot of the vaccine. It seems that we are facing diverse and contrasting changes in mental health burden dependent on country-specific factors.e.g., through awareness raising and information sharing on common mental health conditions, increasing availability of psychoeducation for them, provision of self-help tips) and strengthening evidence-based treatment interventions , including trauma-focused CBT for PTSD). This also needs to be supported by a capacity strengthening program for both primary healthcare workers and mental health specialists for early identification and management of common mental health disorders. In addition, the mental healthcare packages offered by the central and local governments need to be strengthened, for example, by adding treatment for anxiety disorders and adjustment disorders which are currently not included (and so have to be paid for by patients). Ongoing monitoring is also required to detect changes in the patterns of mental disorders and ensure appropriate adjustments are made to the mental health care packages in Georgia.The increasing levels of mental health symptoms reported in our study are plausibly explained by the worsening COVID-19 infection rates in the country by the time of the second survey, along with much stricter measures that increased social isolation and the burden of stressors on the population and individual respondents (see Supplementary File 1). The findings from our study highlight the high and increasing burden of mental disorders in the country. The Ministry of Health in Georgia should recognise this in their annual mental healthcare program by providing promotional and preventive mental health services for the wider population in response to COVID-19  of respondents had a high level of fear of COVID-19 . Factorschanges in concern about COVID-19 from 2020 and 2021. Having symptoms of anxiety was associated with a smaller-than-average increase in COVID-19 concern. Conversely, having symptoms of PTSD and being an IDP were associated with greater-than-average increases in the COVID-19 concern score in our follow-up study. The findings suggest that COVID-19 related concerns may be exacerbated among IDPs and other forcibly displaced persons who have faced many years of extreme stressors and a high ongoing burden of mental health disorders [In our earlier study, we examined the factors associated with concern about COVID-19 , so in tisorders , 37. Resisorders , but ourisorders , COVID-1isorders -42.post-hoc analyses of our data, we found that healthcare workers had a significantly lower risk of depression, anxiety, PTSD and adjustment disorder than non-healthcare workers after adjusting for demographic differences between individuals. Despite this, we fear that the resilience shown in our study sample could rapidly deteriorate due to the length of the stress and unpredictable work-related burden caused by the pandemic, and urge healthcare management and policy-makers to adopt both preventive policies and treatment services [The international evidence highlights that frontline healthcare workers are among the most vulnerable groups affected by COVID-19 in terms of risk of developing mental health conditions such as depression, PTSD, anxiety and burnout syndrome -45. Howeservices .i.e., for addressing increased family violence problems, promoting mental wellbeing and developing prevention interventions, improving access to care for common mental disorders by mobilising resources at the primary healthcare level, and introducing capacity strengthening program for mental health specialists. This aligns with global calls for such activities to support mental health during the COVID-19 pandemic and re-balance mental health care towards community-oriented psychosocial perspectives, integrating mental health in plans for universal health coverage and addressing the needs of neglected populations to deal with disparities and inequality [This is one of the few follow-up studies to examine changes in the influence of concern about COVID-19 and its influence on mental health needs. Other follow-up studies have focused on specific groups, particularly those diagnosed with COVID-19 -49, rathequality .5The primary limitation is the use of non-probabilistic sampling due to the online survey methodology being used. This risks sample selection bias, for example, by excluding those without internet access who may have greater needs . Therefore, the findings cannot be interpreted to be prevalence data or as being nationally representative. However, basic descriptive analyses and explorations of potential associations can be appropriate in such surveys , and havOur survey in Georgia provides one of the few follow-up studies to examine changes in concern about COVID-19 stressors and mental health needs over time. It highlights persistently high and increasing levels of concern about COVID-19 and mental health symptoms. Government initiatives should consider tackling the most prevalent stressors related to COVID-19 to help strengthen their mental well-being of the Georgian population. Mental health infrastructure should be boosted to address the increased need for mental health services. This should include increased access to care for common mental health problems, providing preventive and early identification interventions, and using telephone and online services targeted and tailored to identified needs. The response should include mobilizing the primary healthcare level that is still divorced from mental health care in many post-Soviet countries, including Georgia. Public health researchers and clinicians also need to be mindful of COVID-19 and related responses exacerbating mental health disparities, and so vulnerable groups should be prioritised. Actions taken now may help prevent and mitigate the negative impact of COVID-19 on mental health in Georgia.


To better understand the efficacy of intravitreal dexamethasone implant (Ozurdex) versus antivascular endothelial growth factor (anti-VEGF) treatment in patients with diabetic macular edema (DME). A systematic review and meta-analysis. The study included randomized control trials (RCTs) and non-randomized control trials (Non-RCTs) before December 2021 that compare the efficacy of Ozurdex-related therapyand anti-VEGF therapy. We searched PubMed, Cochrane Library, and EMBASE. The quality of the included studies was assessed carefully. 30 studies were included. Regarding BCVA change, the overall result revealed no significant differences between Ozurdex and anti-VEGF therapies in patients with nonresistant DME, but Ozurdex group had significantly more VA improvement than anti-VEGF therapies in patients with resistant DME . In terms of central retinal thickness (CRT) decrease, there was a significant difference between Ozurdex therapy and anti-VEGF therapy in patients with nonresistant DME  and resistant DME . Overall, Ozurdex therapy resulted in significantly greater VA improvement and CRT decrease than anti-VEGF therapy in resistant DME patients. Ozurdex therapy was not inferior to anti-VEGF therapy in patients with nonresistant DME. Diabetic macular edema (DME) is a vision-threatening complication in patients with diabetic retinopathy3. DME occurs secondary to retinal barrier rupture and is caused by changes in blood sugar levels resulting from hyperglycemia. Vascular endothelial growth factor (VEGF) plays a crucial role in the pathogenic process of DME. This pathogenic process further leads to the accumulation of extracellular fluid2. In recent years, emerging evidence has revealed that inflammation is involved in the pathogenesis of DME. Inflammations initiated by microglial cells, Müller cells, astrocytes, and several cytokines have been reported to be associated with the maintenance of low-grade inflammation6. Furthermore, a previous study revealed both VEGF and cytokine levels to be significantly higher in patients with hyperfluorescent DME than in those with inactive DME7. Anti-VEGF therapy has been developed based on the aforementioned pathogenesis of angiogenesis. Previous studies have revealed anti-VEGF therapy to be superior to laser therapy in treating DME10. Currently, the intravitreal injection of anti-VEGF remains the first-line therapy for DME. However, some patients do not exhibit a good response to anti-VEGF12. A post hoc analysis of a randomized controlled trial (RCT) assessing the cumulative 3-year probabilities of chronic persistent DME reported that 40.1% of eyes had chronic persistent DME11.Diabetes is a chronic metabolic disease that leads to various microvascular and macrovascular complications. The number of people diagnosed as having diabetes mellitus has been estimated to increase to 700 million globally by the year 204513. The 0.7 mg intravitreal DEX implant Ozurdex®  was designed to deliver medication to the retina and could maintain the drug concentration in the vitreous body for up to 6 months3. Several research groups thereafter initiated head-to-head clinical trials to compare the efficacy of anti-VEGF therapy and Ozurdex therapy58. BEVORDEX, the first RCT to assess this, reported that Ozurdex therapy was not inferior to anti-VEGF therapy in terms of visual acuity (VA) changes and that it led to superior anatomical outcomes compared with anti-VEGF therapy at the primary endpoint35. However, other studies have reported heterogeneous results. The potential factors associated with the efficacy of Ozurdex and anti-VEGF therapies emerged as crucial challenges in DME treatment.The use of corticosteroids is another potential therapeutic option, as corticosteroids decrease VEGF synthesis and pro-inflammatory cytokine concentrationsTo the best of our knowledge, no synthetic evidence exists regarding the possible confounding factors affecting the efficacy of anti-VEGF and Ozurdex therapies. Therefore, this systematic review and meta-analysis aimed to quantify the effects of these two therapies. Moreover, meta-regression was performed to determine the possible confounding factors when comparing these therapies.This study was conducted in accordance with the PRISMA guidelines. As published data were used, our study was exempt from institutional review board approval. Our systematic review and meta-analysis aimed to assess the efficacy of anti-VEGF and Ozurdex therapies in treating DME and to determine the potential confounding factors affecting the therapeutic efficacy. The study was registered on Research Registry (Review Registry UIN:reviewregistry1422).Our meta-analysis included all RCTs and observational studies that met the following criteria: (1) the study recruited patients with DME and (2) the intervention consisted of anti-VEGF therapy and Ozurdex therapy. Studies that included patients with not only DME but also other specific ocular diseases, such as concurrent epiretinal membrane and gray literature that did not report details, were excluded. Some studies included specific patients with resistant DME, while others recruited patients with nonresistant DME. Most studies define the resistant DME as the DME with suboptimal treating response after three monthly anti-VEGF injections. A meta-analysis of these two groups was performed in our study. While Ozurdex monotherapy was used in some studies, combination therapy was used in others. A subgroup analysis was further performed in our study to assess the treatment modality.PubMed, Embase, and the Cochrane Library were searched for studies published before April 2021 without any language limitation. The search strategy consisted of the relevant terms anti-VEGF, Ozurdex, and DME in free text and Medical Subject Headings. The details of the search strategy are listed in Two reviewers (SCC and YNK) independently assessed the risk of bias of the included RCTs by using the Cochrane Risk of Bias tool. Non-RCTs are assessed using the Risk of Bias In Non-randomized Studies—of Interventions (ROBINS-I) tool. If any disagreement occurred regarding the quality assessment, it was resolved through discussion with another author (HYM).59.The following information was extracted by two independent reviewers (SCC and YNK): study year; study population; study location; and data, including the change in VA, decrease in central retinal thickness (CRT), safety outcomes (including intraocular pressure [IOP] change), and occurrence of severe ocular adverse events. The log minimum angle of resolution (logMAR) scale was used in this study. The Early Treatment Diabetic Retinopathy Study (ETDRS) letter scores, Snellen chart scores, and decimal acuity scores were converted to logMAR by using a previously reported conversion formulaOnly one anti-VEGF therapy arm was assessed if a study included two treatment arms using different anti-VEGF agents. Under the circumstances, we evaluated the treatment arm, which included more patients. The mean and standard deviation (SD) data for continuous outcomes and the event and total sample size data for binary outcomes were extracted. Regarding the outcome of VA improvement, relevant SD data could not be extracted from the original article of Callanan et al. Therefore, the data of the study was not pooled in the analysis. Moreover, the change in VA reported using Snellen chart scores in the study of Aksoy et al. could not be converted to logMAR. Therefore, the outcome of VA improvement in the study of Aksoy et al. was not included in our analysis.2 statistic was used for assessing statistical heterogeneity. An outcome was defined as highly heterogeneous if I2 was higher than 50%. Funnel plots and Egger’s test were used to assess the small-study effect. For determining potential factors that could affect the pooling results, subgroup analysis and meta-regression were performed to assess the effects in patients with nonresistant DME. In the meta-regression, the mean age, treatment duration, baseline best-corrected visual acuity (BCVA), baseline CRT, glycated hemoglobin (HbA1C) level, and lens status served as predictors. All statistical analyses were performed using R software (4.2.0).Quantitative data synthesis was performed using pairwise meta-analyses. A random-effects model was used in our meta-analysis because of conceptual heterogeneity. The mean differences (MDs) with 95% confidence intervals (CIs) were calculated for continuous outcomes, and the risk ratios (RRs) were calculated for binary outcomes. The IA total of 1,413 potential references were obtained from PubMed (n = 401), Embase (n = 911), and the Cochrane Library (n = 113). After the exclusion of 282 duplicate references, the remaining articles were assessed for eligibility. Finally, 21 articles from 10 RCTs, 3 prospective non-RCTs, and 21 articles from 17 retrospective studies were included in this meta-analysis Fig. .A total of 2,409 eyes were included in our study. The mean age of the patients was 62.19 years old (range 56.2–67.8 years old). The follow-up duration ranged from 1 to 12 months. The baseline BCVA ranged from 0.2 to 0.96 logMAR, and the baseline CRT ranged from 261.1 to 605.3 µm. Five studies included patients with resistant DME, while 25 studies included patients with non-resistant DME. Eight of these studies included patients with naïve DME. Details regarding the characteristics of the included studies are summarized in Table 2 = 97%, Figs. 2 = 0%, Fig. Overall, 27 trials reported the outcome of BCVA change. 4 of these trials included patients with resistant DME. The pooled results revealed no significant differences between Ozurdex group and anti-VEGF group, with high heterogeneity being noted in patients with nonresistant DME  tool. Overall, the level of evidence of included studies was downgraded due to the high risk of bias of confounding factors and the moderate risk of bias in the measurement of the outcomes. The detail of the risk of bias assessment was listed in the Supplement  did not reveal any reduction in the heterogeneity of BCVA change and CRT decrease.No significant difference was noted between Ozurdex therapy and anti-VEGF therapy in terms of IOP change. Pooled analysis revealed that Ozurdex therapy did not lead to a higher rate of severe ocular adverse events than anti-VEGF therapy. Overall, Ozurdex therapy was not inferior to anti-VEGF therapy in terms of VA improvement in patients with nonresistant DME. Although the number of studies was limited, the pooled results revealed that Ozurdex therapy was superior to anti-VEGF therapy in patients with resistant DME. Regarding anatomical outcomes, Ozurdex therapy was superior to anti-VEGF therapy in patients with nonresistant DME as well as in those with resistant DME.For determining the factors associated with the efficacy of Ozurdex and anti-VEGF therapies, meta-regression was performed on the mean age, treatment duration, baseline BCVA, baseline CRT, HbA1C level, and lens status in patients with nonresistant DME. However, no association was noted between these factors and BCVA change in the linear model. In the nonlinear meta-regression model, an association was noted between the MD in BCVA change and the MD in CRT change when comparing Ozurdex therapy and anti-VEGF therapy. Moreover, an association was noted between the MD in CRT change and CRT. As revealed by the parabola figure, Ozurdex therapy tended to be superior to anti-VEGF therapy if the baseline CRT was more than 410 µm. We thought this result may come from the disease severity. To our knowledge, CRT was the index of the disease severity of DME. In other words, Ozurdex therapy tended to be superior to anti-VEGF therapy in patients with moderate to severe DME. The other possible explanation was the role of inflammatory cytokines and chemokines in the pathogenesis of DME. The severity of the DME may be associated with the number of inflammatory factors. Therefore, Ozurdex therapy, which suppressed the inflammatory cytokines, may be superior to anti-VEGF therapy in patients with moderate to severe DME. Furthermore, Subfoveal serous retinal detachment (SRD), which was a potential factor affecting the efficacy of Anti-VEGF and Ozurdex treatment, was associated with high CRT. This novel finding suggests that clinicians can choose a combination therapy of Ozurdex + anti-VEGF or Ozurdex monotherapy depending on the baseline CRT. Furthermore, crucial factors, including biomarkers of spectral domain optical coherence tomography (SD-OCT) and cytokines in the vitreous body, were analyzed in our study. Unfortunately, sufficient data were not available from the head-to-head studies comparing Ozurdex therapy and anti-VEGF therapy.In the subgroup analysis of the treatment modality of Ozurdex (combination therapy or monotherapy) on nonresistant DME, the test of the subgroup difference showed no significant difference between combination therapy and monotherapy regarding BCVA change and CRT decrease. However, there was still high heterogeneity in the subgroup analysis. The subgroup analysis of the type of Anti-VEGF was performed to figure out the source of heterogeneity. Regarding the BCVA change, we detected the significant subgroup difference (p < 0.01) between Aflibercept, Ranibizumab, and Bevacizumab. The Aflibercept therapy contributed to more BCVA change  is an OCT finding that involves the accumulation of subretinal fluid and a detached retina with a hyperreflective signal64. Among the studies included in our analysis, those by Aksoy et al.26 and Vujosevic et al.30 reported that both Ozurdex therapy and anti-VEGF therapy significantly decreased the CT. However, Ceravolo et al.28 only reported a significant decrease in the CT in Ozurdex group. Disorganization of the retinal inner layers (DRIL) could be an important prognostic factor for visual outcomes in patients with DME65. Vujosevic et al.30 found that Ozurdex therapy decreased the extension of DRIL more significantly than anti-VEGF therapy. Hence, evidence to prove the correlation of changes in the extension of DRIL with visual outcomes after treatment is still limited.Choroidal thickness (CT) is thought to be associated with the severity of diabetic retinopathy. Diabetic retinopathy leads to an increase in the VEGF level, thereby increasing the CT66. It only included RCTs and included a total of 4 studies. The pooled results revealed that Ozurdex therapy and anti-VEGF therapy had a similar effect on VA improvement, but the former had a better effect on anatomical outcomes. This result was similar to that of our study. However, their study included a limited number of trials. Recently, Veritti et al.67 published a meta-analysis discussing the strategies and treatment options for DME. They included 45,032 eyes from RCTs and observational studies. Their study focused on 10 specific questions. The pooled results revealed no significant difference in terms of VA change in Ozurdex group and each type of anti-VEGF group between the RCTs and observational studies. Regarding the anti-VEGF regimen, the pooled results revealed that the fixed regimen was significantly better than the pro re nata regimen and that the frequency of treatment was significantly associated with the outcome of visual improvement. They further reported that aflibercept was significantly superior to bevacizumab and Ozurdex in both RCTs and observational studies. This finding suggested that the type of anti-VEGF could be a potential factor affecting the treatment outcome. Finally, they reported that some baseline characteristics, such as the patient's age, duration of diabetes, and baseline BCVA, were significantly associated with the visual outcome. This finding was not similar to that of our study, possibly because of the difference in the eligibility criteria of the two studies. Overall, Veritti et al.67 critically appraised the existing studies surveying DME management. A recent meta-analysis68 included the RCTs to compare the intravitreal steroids including triamcinolone acetonide and Ozurdex. They found the intravitreal steroid resulted in similar BCVA change and lower retinal thickness in DME patients. However, they reported that intraocular pressure-related adverse events were higher in the intravitreal group. In our study, the pooled results showed no significant difference in IOP change between Ozurdex group and anti-VEGF group. The different result may be due to the fact that they included not only Ozurdex but also triamcinolone acetonide. The previous study reported that the triamcinolone acetonide group had 2.4 times higher relative risk in IOP change than Ozurdex group. Compared with their study, we focused on the head-to-head analyses of Ozurdex therapy versus anti-VEGF therapy. We tried to answer the crucial clinical question of choosing the optimal intravitreal medication between Ozurdex and anti-VEGF. The nonlinear meta-regression showed the baseline CRT could be a critical factor affecting the anatomical outcome when treating nonresistant DME. We suggested clinicians chose Ozurdex-related therapy when the patient had a baseline CRT of more than 410 µm. In addition, clinicians should consider the predictive OCT biomarker to select the treatment.A previous meta-analysis of Ozurdex therapy versus anti-VEGF therapy was published in 2018Our study has some limitations. First, to analyze the potential factors affecting the effect of anti-VEGF therapy and Ozurdex therapy, we included both RCTs and non-RCTs. The included studies presented heterogeneity in terms of the population, follow-up duration, treatment modality, and trial design. Although we performed a subgroup analysis of the treatment modality, the heterogeneity remained high. Second, to the best of our knowledge, OCT biomarkers and inflammatory biomarkers are crucial factors affecting the effect of Ozurdex and anti-VEGF therapies in patients with DME. However, we could not perform a meta-analysis because of the limited data from the included trials. Therefore, we summarized the findings of the recruited trials. Third, because of the limited number of studies that recruited patients with resistant DME, we could not perform meta-regression to assess patients with resistant DME. Finally, the outcome measures of VA and CRT varied in the included studies. Some studies used Snellen charts for VA measurement, while others used ETDRS charts for VA measurement. Moreover, CRT measurements reported in these studies had different ranges.This systematic review and meta-analysis compared the efficacy and safety profile of Ozurdex and anti-VEGF therapies and determined the potential factors contributing to the therapeutic effects. Overall, in patients with resistant DME, Ozurdex therapy was superior to anti-VEGF therapy regarding BCVA change and CMT decrease. In patients with nonresistant DME, Ozurdex therapy was not inferior to anti-VEGF therapy in terms of VA improvement and CRT decrease. The meta-regression of patients with nonresistant DME revealed a novel finding: Ozurdex therapy tends to decrease CRT to a greater extent than anti-VEGF therapy if the baseline CRT is more than 410 µm. Several studies suggested that Ozurdex therapy was superior in DME patients with HRD and SRD. Nevertheless, further high-quality trials are warranted to discuss other issues, such as OCT and inflammatory biomarkers, in DME treatment.Supplementary Information.


Finally, we begin to test a subset of these candidate enhancer elements, within the organoid system, by perturbing the underlying DNA sequence and measuring transcriptomic changes during EF activation.Specification of the eye field (EF) within the neural plate marks the earliest detectable stage of eye development. Experimental evidence, primarily from non-mammalian model systems, indicates that the stable formation of this group of cells requires the activation of a set of key transcription factors. This crucial event is challenging to probe in mammals and, quantitatively, little is known regarding the regulation of the transition of cells to this ocular fate. Using optic vesicle organoids to model the onset of the EF, we generate time-course transcriptomic data allowing us to identify dynamic gene expression programmes that characterize this cellular-state transition. Integrating this with chromatin accessibility data suggests a direct role of canonical EF transcription factors in regulating these gene expression changes, and highlights candidate  Summary: Analyses of RNA- and ATAC-sequencing measurements of optic-vesicle organoid development robustly characterize the mammalian eye-field and generate specific hypotheses of cis-regulation of eye-field transcription factors. Xenopus laevis embryos . Mutations in at least three of the genes encoding orthologues of the Xenopus EFTFs can cause severe bilateral eye malformations in humans  . The eye field was first identified in  embryos  and exprand RAX) . It seemThe eye field has been difficult to study in mammals as it forms in early post-implantation embryos . The Sasai lab developed a simple defined organoid culture system  that supX. laevis. Furthermore, by integrating transcriptomic and chromatin-accessibility data, we show that these TFs likely regulate the stable transition of cells to an ocular fate by binding distal enhancers in genomic domains local to EF genes. By examining how chromatin accessibility, associated with key TFs, changes at individual genomic loci, we generate hypotheses of plausible cis-regulatory elements (CREs – enhancers and repressors) required for differentiation from pluripotency to eye-field cell states. Finally, we test a subset of these hypotheses by perturbing the underlying DNA sequences. In all, by exploiting the robust and reproducible model system offered by mESC-derived organoids, our study provides a first quantitative understanding of the regulatory mechanisms underlying mammalian eye-field specification.We have performed a functional genomic analysis of the eye field-like cells that appear in the very early stages of optic vesicle organoid differentiation. By performing computational analyses of the transcriptomic changes during OV differentiation, we find that establishment of the eye field in mouse ESC-derived OVs involves strong upregulation of a set of genes that includes the same key transcription factors identified in in vivo. We have exploited a reproducible, in vitro organoid model system enabling us to generate data from this cell-state transition and through computational analysis gain a quantitative understanding of the underlying regulatory mechanisms. We performed OV organoid culture using mouse embryonic stem cells (mESCs) that have a GFP fluorescent reporter cassette knocked into the Rax locus , and as such is extremely challenging to study ax locus . The expgenitors , althougthalamus . Rax-posthalamus A, and atpositive . By day positive . We perfpositive B.Rax, Pax6, Lhx2, Six3 and Six6, indicating that drivers of the optic-fate in mammals include most of the key TFs also discovered in Xenopus. Six6 was expressed slightly later, consistent with evidence that it is a downstream target of Lhx2 and Pax6  terms ‘mechanisms associated with pluripotency’ or ‘stem cell population maintenance’], and although they were downregulated across the state transition, they were also consistently downregulated across the full time course of organoid differentiation. This suggests that successful specification of the eye field requires both the network of eye-field genes to be turned on as well as genes controlling pluripotency to be switched off. It is noteworthy that Sox2 and Otx2, known to be crucial in eye development, are not differentially expressed across this crucial time point  across the day 3-to-day 4/5 transition . Many ofme point A, consisfication  and playfication , we founme point A.Rax, Lhx2, Six3 and Fezf1. The fact that these key factors are significantly upregulated so early in OV development , may point to these TFs acting as very early eye-field determining factors. Interestingly, 12 genes upregulated between days 2 and 3 actually overlapped with EF-down genes, including Wnt3, Wnt8a, Fgf8 and Lmx1b, pointing towards the eye-field state requiring repression of gene expression programmes that were turned on earlier in differentiation. This has close parallels with what is thought to happen in vivo, where, as well as promoting ocular fate, EFTFs are also involved in repressing gene expression programmes characterizing other neural cell states, such as diencephalic, mid- and hindbrain states, early in development  genes upregulated between days 2 and 3 overlapped with the EF-up genes, including the TFs elopment .Finally, to explore whether there are general patterns to the trajectories of differentially expressed genes, we performed a clustering analysis on the trajectories of the EF-up and EF-down genes B. This aChanges in the expression of genes characterizing cell-state transitions, in development and disease, are thought to be largely controlled by changes in DNA accessibility and binding of TFs at CREs genomically local to those genes . To gainWe used GREAT analysis  to compuRax, Pax6 and Lhx2, were accessible from day 0, despite very low or zero corresponding gene expression , trajectories of the latter were more variable across the time course   containipression . Indeed,Rax, Lhx2 and Pax6, whereas peaks with decreasing accessibility appear enriched for pluripotency factors motifs such as Pou5f1 and Nanog  the consensus motifs for Rax, Lhx2 and Pax6 , suggesting activator roles. The same analysis revealed potential repressive roles for the pluripotency factors Pou5f1, Nanog and Sox2, which displayed significant negative expression-accessibility correlation (P<10−10 Wilcoxon rank-sum test) for peaks within EF-up gene TADs. This is in line with evidence suggesting that, as well as being important for activating CREs maintaining pluripotency, these genes also act in a repressive manner to block activation of elements crucial for the upregulation of differentiation genes . This revealed that some of the largest increases in motif binding correspond to EF-up TFs, most notably Rax, Pax6 and Lhx2 motifs A, and, spression .We assume that a TF playing a regulatory role by direct binding to DNA should display well-correlated footprint-score and expression trajectories. To investigate this, for each motif we computed the correlation of the footprint score of each occurrence with expression of the corresponding TF. The set of motifs that displayed a median correlation >0.5 in EF-up-TAD peaks contained all key EF-up TFs E,F, plusAggregating ATAC-seq signal around multiple occurrences of a given motif allows visualization and quantification of TF footprints. To unpick large changes in footprinting between days 3 and 5 in an unbiased manner, we computed the depth and flanking accessibility for each motif, for genome-wide and EF-up TAD peak occurrences, on each day. Comparing the changes in footprint depth and flanking accessibility between these time points, we found that in EF-up peaks B as wellFinally, to confirm that the increases in footprint depth scores correspond to visually discernible footprints, we visualized the aggregate ATAC-seq signal at and around occurrences of a given motif. To pull apart changes between days, we compared the aggregate signal for motif occurrences that are predicted by TOBIAS to be ‘bound’ on day 3 and on day 5. Although there was little difference in aggregate signal between days, for occurrences predicted to be bound on day 3, we found a striking increase in footprint depths for Rax, Pax6 and Lhx2 motif occurrences predicted to be bound on day 5. This observation applied both to genome-wide peaks as well as to peaks contained in EF-up gene TADs C,D. ThisSox2, Otx2, Tcf3, Tcf7 and Tcf7l2. We performed this focused intra-TAD analysis for the five core EFTFs , looking for changes between days 1, 3 and 5 that either mirror the upregulation of the corresponding gene or which point to a loss of repression.The motif and footprint analyses described above provide consistent evidence that the canonical EFTFs Rax, Pax6 and Lhx2 play a direct regulatory role in establishing a stable eye field, specifically through binding non-promoter elements in accessible regions within TADs containing EF-up genes. Next, we moved from this broad picture of regulation towards identifying candidate gene-specific CREs through which these key TFs act. For a given EF-up gene, we approached this by searching for ATAC-seq peak regions within the TAD containing the gene, which displayed large changes in footprint scores for motifs of any of these three key TFs, as well as of Rax (Six6 (Rax TAD (Rax gene itself (Six6 TAD (Rax). We found similar signal patterns, highlighting a small number of peaks for each EF-up gene . The candidate peak selected for Six6 was in a closed chromatin state at day 1, became accessible by day 5 (Six6 TAD).As a step towards validating our approach for identifying gene-specific CREs, we selected two of the EFTFs for follow-up testing: ver time , the fooby day 5  and had Rax peak, we introduced a 113-bp homozygous deletion (chr18:65941339-65941452)  (We used CRISPR-Cas9  to intro5941452)  that dis Xenopus . In the 2852563)  disrupte2852563) B,E. The 2852563) , likely 2852563)  in triplRax and Six6, results in downregulation of the associated target gene . We highlight that developmental genes are generally regulated by more than one CRE  within a GRN. Interestingly, in line with the notion that the EFTFs play a role in suppression of the pluripotency programme, we found evidence of pluripotency genes (e.g. Zfp42 and Pou5f1) being more highly expressed in mutant compared with wild-type organoids. Conversely, markers of later eye development (e.g. Vsx2 and Vax2) were significantly downregulated in mutant organoids.Comparing the expression of key genes in wild-type and mutant organoids, we found that disrupting the candidate CREs for both  one CRE , and theRax, Pax6, Lhx2 and Six3 has been knocked out or rendered null, have shown that expression of the non-perturbed genes is activated in the appropriate regions  in which just one of the TFs  regions . MaintenRax being switched on, and specifically, the changes at CREs triggering Rax expression, do not necessarily involve other EFTFs . Related to this, the work of Xenopus animal cap cells, that Sox2 and Otx2 proteins interact to activate Rax expression, by co-binding a conserved 35-bp region within a CRE ∼2 kb upstream of the Rax promoter. The authors propose that activation of this element is sensitive to the ratio of Sox2 and Otx2 concentrations  and, in so doing, activate this putative enhancer and consequently also the expression of Rax.To gain further insights into the activation of this element, we mined the UniBind database  of TF–DNFurther experiments (in particular a CHIP-seq or Cut&Run time course for the relevant TFs) beyond the scope of our current study would be required to validate this hypothesis. We do, however, find it both fascinating and of considerable value that specific hypotheses of gene regulation can be pieced together through systematic and integrated analysis of data across modalities, such as the one presented above. We also point out that, similar to the mechanics of regulation we hypothesize above, Xenopus. Second, the patterns extracted from our RNA-seq data indicate that when this state transition occurs, not only is this core set of EFTFs upregulated, but, in parallel, other gene expression programmes, such as those controlling cellular pluripotency and cellular signalling, are downregulated or carefully balanced. Third, analysis of the dynamics and sequence composition of chromatin accessibility peaks strongly suggests that the key EFTFs – particularly Rax, Pax6 and Lhx2 – act to control the upregulation of the EF genes through binding to (primarily) non-promoter regulatory elements in the vicinity (TADs) of those genes. By performing footprinting analyses for key TFs in TADs of important genes, we have additionally identified putative gene-specific CREs that appear to be important for regulating the gene expression changes characterizing the onset of the eye field. Furthermore, by perturbing a subset of these candidate regulatory elements using CRISPR and generating mutant cell lines, we have started to validate the regulatory potential of these elements in controlling EFTF expression in OV organoids.By using an OV organoid model to enrich for cells transitioning to an optic fate, we have generated bulk transcriptomic and chromatin accessibility time-course data from a very early developmental event that is crucial for mammalian eye development. Joint computational analyses of these data have revealed three key messages regarding the molecular events controlling eye field specification. First, the transition to the eye field in mESC-derived OV organoids is characterized by the upregulation of a small set of genes, including a core set of TFs known to be necessary for eye development through studies in Xenopus, extends this characterization to mammalian models and begins to shed light on the roles of key EFTFs in the transition of cells to the ocular fate. Additionally, our work demonstrates the power and practicality of using an organoid system to generate and test specific hypotheses regarding the regulation of cell-state transitions relevant to crucial events in mammalian development.In all, our study complements the early characterization of the eye field from Rax, from the replacement of repressive factors (such as Pou5f1) with activating factors (such as Otx2) at regulatory elements that are ubiquitously open across the time course. We have also outlined that disentangling the mechanisms behind gene-expression or cellular-state changes that are triggered through the action of TFs at regulatory elements can indeed be very challenging to understand through standard analyses correlating peak accessibility with gene expression. However, footprinting analyses do have the potential to provide richer insights into these more subtle mechanisms of regulation.Although our data does not have the resolution to identify definitively what may initially trigger the expression of individual EFTFs, we have presented evidence to suggest that this may arise, at least in the case of The approach to characterize the OV-organoid eye field presented in this work does have some limitations, which indicate areas for future work. First, at each time point the organoids are likely to be composed of relatively heterogeneous collections of cells. As a result, the bulk RNA-seq and ATAC-seq datasets generated for this study are expected to be powerful enough to reveal the larger changes in gene expression programmes, such as the upregulation of the eye field programme or the suppression of pluripotency, but may be limited in their power to distinguish more subtle effects. To address the confounding issues introduced by cellular heterogeneity, an approach profiling the organoids at the single-cell level would be required. Second, although motif and footprinting analyses of our ATAC-seq data provide consistent evidence to build hypotheses regarding the putative regulatory roles and binding of important TFs, this evidence is indirect (the occurrence of a consensus TF motif within a region of enriched accessibility does not imply the binding of that TF at that genomic location). To gain more direct evidence of changes in TF binding it would be useful to perform time-course ChIP-seq or Cut&Run experiments for a set of TFs identified as important.in vivo and in the organoid system? Using a collection of markers Finally, in undertaking the work presented here we have encountered a number of intriguing open questions regarding eye-field specification that require further study. In particular, it is pertinent to ask whether the eye field directly stems, in a sequential manner, from a group of well-defined progenitor cells within the neural plate, or whether individual neuroectodermal cells spontaneously acquire ocular fate and are only then organized into a coherent eye field through migration and cell-signalling events? Furthermore, are these processes similar Rx-GFP mouse ESCs were maintained and SFEBq (serum-free floating culture of embryoid body-like aggregates with quick aggregation) differentiation of OV organoids was performed as described previously . BrieflyRax expression.Differentiation status was assessed using fluorescence imaging to detect the presence of GFP as a measure of On days 0-5 of optic vesicle differentiation, triplicate samples of cells were collected from 24 organoids, which were dissociated and sorted using FACS to select for live single cells. Samples at days 4 and 5 were also sorted on the basis of GFP expression giving a GFP-positive and -negative sample for each of these time points. The FACS gating placement was designed to maximize the number of cells in each sample, such that some cells with low GFP signal were included in the GFP-negative sample, and the GFP-positive samples contained cells with both high and moderate levels of GFP expression. Day 3 samples were analysed with FACS and found to contain a small proportion of GFP-expressing cells, but not enough to extract sufficient RNA. To obtain a more accurate view of the diverging cell types at this stage, all live cells from these organoids, regardless of their GFP expression were included in this sample. RNA was isolated using the Zymo Direct-zol RNA MicroPrep kit following the manufacturer's instructions. Quality and integrity of the RNA samples were analysed, libraries were prepared using the TruSeq kit (Illumina), and sequenced on the NextSeq 550 platform as per the manufacturer's protocols. For further details, see Coding regions of DNA and non-coding RNA from the mouse genome build 38 (mm10), downloaded from the Ensembl database, were used to create the transcriptome index. kallisto  was then+, day 4GFP−/day 4GFP+, day 5GFP−/day 5GFP+. Genes found to be significantly upregulated across all these comparisons were termed ‘EF-up’ genes, whereas those significantly downregulated across these comparisons were termed ‘EF-down’ genes. We also used DEseq2 to select a set of ‘housekeeping’ or stably expressed genes, by requiring these genes to display absolute log2-fold-change <0.1 for every successive day comparison, and have a mean (across days) normalized expression >30 (this procedure identified 190 such stably expressed genes).Differential expression analysis between time points and expression normalization was performed using DESeq2 . Specifiz-transformed log2 values of normalized gene expression for EF-up and EF-down genes. In detail, we used the GMM implementation available in the Python scikit-learn library  approach applied to  library , fittinghttps://metascape.org).We applied a GO enrichment analysis on the three sets of genes corresponding to the broad patterns discovered using clustering, using the Metascape online tool  and cutadapt (https://github.com/taoliu/MACS), with parameters -f BAMPE -g mm –keep-dup all -B –SPMR –nomodel, on paired-end bam files of each sample (day) separately. Using the narrowPeak macs2 peak coordinates, we created a consensus set of peaks with which to study accessibility dynamics across days, using the bedtools merge command. From this consensus set of peaks, we removed peaks overlapping blacklisted regions of the mm10 genome, as listed on http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/. We used conditional quantile normalization . We noted that there are often gaps between genomically adjacent TAD regions, and in these cases we took these inter-TAD regions to also define relevant regions to restrict the search-space of putative peak-gene links . EF-up and EF-down TADs were defined as those TADs containing the genes determined to be differentially up- and downregulated, respectively, across the transition from day 3 to day 5. Housekeeping TADs were defined as TAD regions containing genes that are stably expressed across the full time course.To assign peaks to TAD regions, we downloaded the coordinates for TAD regions from the work of http://great.stanford.edu) to generate region–gene associations computationally. We used the coordinates of dynamic peak regions (regions of increasing and decreasing accessibility across the transition from day 3 to day 5) as test regions, and the whole genome as the background regions (default setting of GREAT).To perform a first putative linking of dynamic peaks to genes we employed the online GREAT tool , and we scanned each peak region for occurrences of all motifs in the JASPAR2020 database (Mus musculus TF motifs), using the presence/absence of motifs for further downstream analysis. We also restricted our attention to motifs of TFs that were expressed in the OV system, which we defined to be the mean (across RNA-seq replicates) DEseq2-normalized counts of a TF's expression >50, at any point in the time course. To compute enrichment of motifs for our defined signal peak sets [peaks with increasing or decreasing accessibility signal above a log2-fold-change of 1.5], we employed the hypergeometric test (Fisher test) using the set of peaks in TADs of housekeeping genes as a background.We obtained the DNA sequence of each consensus peak using bedtools getfasta and the mm10 genome. Following this, we used fimo with parameters –text –max-strand –thresh 1e-4  using the presence of motifs corresponding to EF-up genes, EF-down genes, day2-day3 differentially expressed genes, as well as Sox2 and Otx2, as input features. Where there were multiple motifs for a TF, we collapsed the input feature into a single feature in which a TF motif was deemed to be present in a peak if that peak contained a significant occurrence of any of its possible motifs. We trained models on two sets of peaks: dynamic peaks [those with log2-fold-change >1] within TADs containing EF-up genes and genome-wide dynamic peaks. We first used 5-fold cross-validation to determine an appropriate regularization parameter for each model, and then trained models using these optimal parameters on the full sets of peaks. In this second step, we fitted ten models with different random initial seeds, and took the mean for each coefficient across each run. To perform this modelling, we used the ‘LogisticRegression’ functions implemented in the sklearn Python library , and specifically downloading data from the Mus musculus genome tracks.ChIP-seq evidence-backed sites of TF–DNA interactions were obtained from the UniBind database,  vector. Rx-GFP cells were transfected with the resulting plasmid using Lipofectamine 3000 and cells selected based on GFP expression from the plasmid 48 h later. Cells were plated at low density, individual clones were expanded and resulting cell lines were assessed for deletions over the CREs in question using Sanger sequencing -2A-GFP .Plots and visualizations were produced using the matplotlib Python  library Click here for additional data file.10.1242/develop.201432_sup1Supplementary informationClick here for additional data file.


The first case of COVID-19 in South Africa was reported in March 2020 and the country has since recorded over 3.6 million laboratory-confirmed cases and 100 000 deaths as of March 2022. Transmission and infection of SARS-CoV-2 virus and deaths in general due to COVID-19 have been shown to be spatially associated but spatial patterns in in-hospital deaths have not fully been investigated in South Africa. This study uses national COVID-19 hospitalization data to investigate the spatial effects on hospital deaths after adjusting for known mortality risk factors.COVID-19 hospitalization data and deaths were obtained from the National Institute for Communicable Diseases (NICD). Generalized structured additive logistic regression model was used to assess spatial effects on COVID-19 in-hospital deaths adjusting for demographic and clinical covariates. Continuous covariates were modelled by assuming second-order random walk priors, while spatial autocorrelation was specified with Markov random field prior and fixed effects with vague priors respectively. The inference was fully Bayesian.The risk of COVID-19 in-hospital mortality increased with patient age, with admission to intensive care unit (ICU) , being on oxygen  and on invasive mechanical ventilation . Being admitted in a public hospital  was also significantly associated with mortality. Risk of in-hospital deaths increased in months following a surge in infections and dropped after months of successive low infections highlighting crest and troughs lagging the epidemic curve. After controlling for these factors, districts such as Vhembe, Capricorn and Mopani in Limpopo province, and Buffalo City, O.R. Tambo, Joe Gqabi and Chris Hani in Eastern Cape province remained with significantly higher odds of COVID-19 hospital deaths suggesting possible health systems challenges in those districts.The results show substantial COVID-19 in-hospital mortality variation across the 52 districts. Our analysis provides information that can be important for strengthening health policies and the public health system for the benefit of the whole South African population. Understanding differences in in-hospital COVID-19 mortality across space could guide interventions to achieve better health outcomes in affected districts. Over the past 2 years, the world has grappled with COVID-19, a disease caused by a novel coronavirus, SARS-CoV-2. This was first noted in December 2019 in Wuhan, China, where a cluster of patients with pneumonia of unknown cause was identified  South AfLow- and middle-income countries reported large numbers of COVID-19 related hospitalizations and deaths. New Variants of Concern (VOC) emerged including Alpha, Beta and Delta, that were more transmissible and associated with more severe disease . Two OmiCOVID-19 mortality risks were highly disproportionate in South Africa, with the elderly, males, people of colour, those with comorbidities and those admitted at public health facilities and in certain provinces, being at higher risk . SeveralJassat et al. (2022) described the demographic and clinical characteristics of individuals admitted to hospital with laboratory confirmed COVID-19 throughout South Africa in first and second waves using the DATCOV surveillance data and also assessed risk factors for in-hospital mortality , 6, 8. IThe COVID-19 epidemic revealed strong spatial heterogeneity in the spread of infections in countries such as France and Italy  assessedJassat et al. , in SoutIn recent years, there has been a growing interest in the application of spatial analysis and modelling techniques as a tool for in-depth understanding of public health problems including identifying hotspots, spatial distribution, patterns and effects , 16–20. The data used in this study was obtained from the National Institute for Communicable Diseases (NICD). The data was collected using the Daily Hospital Covid-19 Surveillance (DATCOV) database, an active national COVID-19 hospital surveillance system. The database contains 486 344 hospitalizations with corresponding minimal key individual level data points including age, month and year of hospitalization, patient gender and clinical markers like being on ventilation, on oxygen and admission in ICU. The month of admission variable was included to capture temporal and wave effects on mortality risk. In order to track the epidemic waves and peaks, January 2020 was set to 1 and June 2022 was set to 30. The facility, subdistrict, district and province of the hospital where the patient was admitted are also recorded. We assessed district level spatial effects together with other important covariates that were chosen on the basis of biological plausibility and available evidence. These covariates include patient gender, and age, health sector type, having been put on oxygen, admission to ICU and having been put on ventilation. We used the month of admission as proxy for temporal and wave effects. These spatial effects need to be modelled and estimated simultaneously with linear and possibly nonlinear effects. We used district level effects to allow for spatial correlation and any other unknown regional heterogeneity of COVID-19 hospital deaths.Let This study assumes that the dependent variable, The link function in this equation is known as the logit link, approach , 23. Thea et al. , we consWe fit a generalized structured additive logistic regression model for COVID-19 hospital deaths using Markov chain Monte Carlo (MCMC) simulations.p-value of less or equal to 0.05 was considered to indicate statistical significance. The 95% credible intervals were reported with adjusted Odds Ratios for the full Bayesian inference.Statistical analysis was performed in R/RStudio v 4.1.0. Spatial distribution and patterns including Global Moran I and local Moran I for assessing autocorrelation and local clustering were assessed for district level aggregated risks. A conditional autoregressive (CAR) generalized structured additive logistic regression model with binomial link was fit using BayesX R package accounting for spatial effects . In addiEthical approval was obtained from the Human Research Ethics Committee  of University of the Witwatersrand for the DATCOV surveillance programme (M2010108).Our analysis included data from all provinces in South Africa over the period March 2020 to June 2022. The database contained 484 699 COVID-19 patients who were hospitalized in either private or public health care facilities. The patient data including hospitalization facility was reported at the individual and subdistrict level. The median age for patients who died was 63 years (IQR: 53–73) while for those who survived or were discharged alive was 48 years (IQR: 34–62). Over half of the patients, 60.9% , who died in hospital were admitted and received care from public health care facilities (Table District level spatial distribution of hospital mortality risks are described in Fig. Table Figure Figure We investigated the spatial effects using the structured additive logistic regression model and Fig. We examined factors associated with in-hospital COVID-19 mortality in South Africa between March 2020 and June 2022, adjusting for spatial autocorrelation at district level, fixed effects and some non-linear temporal and age effects. Besides confirming that older age, male gender, admission in ICU, being treated with supplemental oxygen and invasive mechanical ventilation, predisposed hospitalized COVID-19 patients to a higher risk of in-hospital mortality, our study highlighted substantial heterogeneity in mortality across districts.Our study describes the spatial distribution of COVID-19 in-hospital deaths in the whole population in South Africa adjusting for several factors including month of admission as a proxy for epidemic waves. The impact of spatial neighbourhood dependents and heterogeneity have not previously been explored at higher resolution in South Africa regarding COVID-19 in-hospital mortality.To respond effectively to new epidemics, it is essential to unpack the spatial dynamics of in-hospital deaths at higher spatial resolution such as at subdistrict or district level in order to identify priority areas for intervention to improve health outcomes. Our spatial model adjusted for temporal effects, suggested that age had a nonlinear effect on in-hospital mortality with increasing risk for increasing age as was determined in other previous studies , 26–29.The study also provides evidence that in-hospital mortality was clustered geographically with several districts in Eastern Cape and Limpopo showing elevated risk. Previous studies showed that hospitalized COVID-19 patients in the Eastern Cape and Limpopo provinces were at higher odds of death , howeverUnderstanding spatial heterogeneity in relation to the socio-environmental determinants and COVID-19 related outcomes is central to targeting interventions for vulnerable populations . There aA study that assessed inequalities in access to health care in South Africa showed large differentials in private health care admissions between people living in the poorer, more rural provinces like Limpopo, Eastern Cape and Mpumalanga compared to more urban provinces like Gauteng . We provBesides showing spatial structure in the COVID-19 in-hospital mortality in South Africa, our study using the non-linear effects of months as a proxy for temporal evolution of the epidemic highlight higher risk of deaths during the second and third waves. Jassat et al. similarly reveal in their study that in-hospital case-fatality ratio during the Omicron wave was 10·7%, compared with 21·5% during the first wave, 28·8% during the second wave, and 26·4% during the third wave –35. MassMajor strengths of this study include the application of flexible structured additive logistic regression model within the Bayesian framework which allows for exploration of spatial association with health outcomes at higher spatial resolutions as well as allowing for inclusion of non-linear effects and fixed effects. This approach is recognised as an important tool for providing reliable estimates for area characteristics under limited sample information. In addition, this study utilizes a COVID-19 hospital admissions high-quality national data repository with their associated individual level outcomes ensuring ample admission sample data as well as outcomes for analysis at district level. This study is not without some limitations. For this analysis, we adjusted for some of the known risk factors for COVID-19 in-hospital deaths, however, there may be other covariates which we may not have included. A further limitation may be that the DATCOV database does not distinguish between patients who were admitted with coincidental positive SARS-CoV-2 test and those with COVID-19. As highlighted in the preceding limitations, there was limited information on other important variables and ancillary predictors that can be used to model in-hospital mortality. Therefore, there is a need to utilize the same modelling framework to account for the impact of these and other factors especially aggregated at subdistrict or district levels. This data may also benefit from spatial–temporal modelling of deaths events at district level and adjust for population density as well as wave specific spatial effects.As in one Brazilian study , our finThe results from this study reveal substantial COVID-19 in-hospital mortality variation across the districts in South Africa. This highlights the importance of modelling spatial patterns simultaneously with fixed and nonlinear effects of continuous covariates to identify clusters at high risk of health outcome. The flexible approach to modelling data that has spatial patterns helps to account for possible loss of efficiency due to spatial correlation that spatial patterns can induce in data. Our analysis suggests notable COVID-19 hospital deaths clustering in some districts in Limpopo and Eastern Cape provinces and this information can be important in strengthening the public health and health systems policies for the benefit of the whole South African population. Understanding differences in in-hospital COVID-19 mortality across space could guide interventions to achieve better health outcomes.The findings of this analysis reveal that strengthening health systems, specifically critical intensive care, oxygen support, and availability of health care workers, could lead to substantial reductions in mortality risk in South Africa in the case of a resurgence of COVID-19 epidemic or new epidemics. It is also important for public health authorities to manage medical care effectively and in a timely manner, as well as to direct the intensity and type of interventions needed to overcome the pandemic.


The development of high-throughput automated patch-clamp technology is a recent breakthrough in the field of Brugada syndrome research. Brugada syndrome is a heart disorder marked by abnormal electrocardiographic readings and an elevated risk of sudden cardiac death due to arrhythmias. Various experimental models, developed either in animals, cell lines, human tissue or computational simulation, play a crucial role in advancing our understanding of this condition, and developing effective treatments. In the perspective of the pathophysiological role of ion channels and their pharmacology, automated patch-clamp involves a robotic system that enables the simultaneous recording of electrical activity from multiple single cells at once, greatly improving the speed and efficiency of data collection. By combining this approach with the use of patient-derived cardiomyocytes, researchers are gaining a more comprehensive view of the underlying mechanisms of heart disease. This has led to the development of more effective treatments for those affected by cardiovascular conditions. SCN5A) gene encoding the voltage-gated cardiac sodium channel NaV1.5 -amine (CyPPA) or hypothermia. Moreover, CyPPA impaired atrioventricular node and intraventricular conduction. This induced condition resembles BrS, which often includes bradycardia and conduction delay )mutation . In anottivation . These r+ voltage-gated channel subfamily D member 3 (KCND3) gene, responsible for the cardiac Ito [to levels by reducing the peak current by approximately 40%. This resulted in the effective reversal of the GoF abnormal AP [KCND3 gene. Finally, in a recent study by Zhong and colleagues [2+ voltage-gated channel auxiliary subunit β2 (CACNB2) gene, and the study aimed to evaluate the pharmacological effects of different compounds on the cellular model. The CACNB2 VUS was identified in a 55-year-old patient with recurrent sudden cardiac arrest who received an ICD that discharged appropriately after beta-blocker therapy was discontinued. The patient was then treated with a low dose of bisoprolol, despite the previous literature suggesting that it should be avoided in BrS, and did not experience any ICD discharges over a 5-year follow-up period. Cellular electrophysiological experiments revealed that the peak current density of the L-type Ca2+ current (ICaL) was smaller in patient-derived iPSC-CMs compared to healthy and isogenic controls, resulting in abnormalities in AP parameters and an increased incidence of arrhythmic events such as EADs. Low-concentration bisoprolol abolished arrhythmic events and reduced beat-to-beat interval variability, supporting the effectiveness of the low-dose therapy used in the patient. These findings suggest that patient-derived iPSCs can be used in preclinical studies to evaluate the effects of drugs that are traditionally avoided in BrS, which can lead to personalised treatment strategies based on gene variants. By highlighting the importance of gene variants in pharmacological evaluation, the study underscores the utility of hiPSC-CMs in advancing our understanding of disease mechanisms and developing personalised therapies.In the context of BrS being a multifactorial syndrome caused by a combination of genetic and environmental factors , the ultdiac Ito . The patormal AP . These flleagues , a celluThe implementation of personalised electrophysiological characterisation, which could lead to patient- or gene-specific pharmacological treatments, demands a high level of data generation and analysis that traditional electrophysiological techniques cannot provide. In the following paragraphs, we will examine the potential breakthrough represented by automated patch-clamp technology and its application in studying BrS in combination with hiPSC-CMs.SCN5A variants found in Brugada patients [V1.5 channel. They were able to study up to 83 SCN5A variants by plating five different stable SCN5A variant-expressing cell lines at the time on a single 384-well APC chip [SCN5A variants with a peak current density less than 10% compared to that of the WT. In a second study, the same research team applied the DMS and APC approaches to evaluate the dominant negative effects of previously characterised SCN5A missense variants related to BrS [SCN5A gene are more likely to result in BrS symptoms compared to other missense variants, with a 2.7-fold increased risk of symptomatic BrS compared to haploinsufficient variants [In recent years, the DMS approach has been used to evaluate the pathogenicity of patients ,95. In aAPC chip . At leasAPC chip . The 10 d to BrS . The resvariants . Despite2+ paradox-related injury, BB has been shown to enhance the viability of hiPSC-CMs and improve the quality of APC recordings [V1.5 channel [V1.5 and connexin-43 protein expression in patient-derived iPSC-CMs, leading to slower conduction and increased beat-to-beat variability compared to healthy controls in MEA-recorded field potentials. The mutation also affected various ion channels; in fact, in addition to a noticeable decrease in the INa peak density, accompanied by a rightward shift in the activation curve, there was an increase in the Ito peak density and in the ICaL window current, accounting for the slower maximal depolarisation velocity during spontaneous AP, prominent notch, and other AP irregularities such as EADs and delayed afterdepolarisations (DADs). APC was also used to study the pharmacological effects of two clinically used phosphodiesterase blockers, cilostazol and milrinone. These compounds are known to suppress hypothermia-induced ventricular tachycardia and ventricular fibrillation. Both cilostazol and milrinone reduced the incidence of proarrhythmic events in patient-derived iPSC-CMs by reducing the enhanced Ito, without affecting INa, suggesting their therapeutic potential in treating BrS patients.In the perspective of personalised medicine strategies for BrS patients and fulfilling the third step of the CiPA initiative, it is imperative to incorporate the complex cellular modelling provided by hiPSC-CMs into APC. The main challenge in this regard is the requirement of a large (and costly) number of hiPSC-CMs and the difficulty in manually selecting individual clones. Traditionally, APC systems necessitate a minimum of 25,000 to 150,000 cells per well for a successful catch rate . Howevercordings . As prevcordings ,67,68,69SCN5A variant has been studied in hiPSC-CMs using APC.To the best of our knowledge, this is the only published work in which the pathophysiological mechanism of a BrS-related The advancement of techniques such as the use of cardiomyocytes derived from patients and automatic patch-clamp technology in BrS are both contributing to significant progress in the field. Cardiomyocytes derived from patients provide a more accurate representation of human heart cells, allowing the study of disease mechanisms and the development of treatments in a more relevant and meaningful way. Meanwhile, high-throughput APC technology enables the rapid characterisation of electrical activity in multiple cells simultaneously, increasing the speed and efficiency of data collection. Moreover, it can be used to assess the effectiveness of new drugs by measuring their impact on the electrical activity of cells obtained from patients with this clinical condition. While MPC will always have a place in the cardiovascular research area, using both approaches with an eye on the future, investigators can gain a more comprehensive view of the underlying mechanisms of heart disease, and develop treatments that are better suited to the specific needs of individual patients.


This review summarizes current advances in the role of transcriptional stochasticity in HIV-1 latency, which were possible in a large part due to the development of single-cell approaches. HIV-1 transcription proceeds in bursts of RNA production, which stem from the stochastic switching of the viral promoter between ON and OFF states. This switching is caused by random binding dynamics of transcription factors and nucleosomes to the viral promoter and occurs at several time scales from minutes to hours. Transcriptional bursts are mainly controlled by the core transcription factors TBP, SP1 and NF-κb, the chromatin status of the viral promoter and RNA polymerase II pausing. In particular, spontaneous variability in the promoter chromatin creates heterogeneity in the response to activators such as TNF-α, which is then amplified by the Tat feedback loop to generate high and low viral transcriptional states. This phenomenon is likely at the basis of the partial and stochastic response of latent T cells from HIV-1 patients to latency-reversing agents, which is a barrier for the development of shock-and-kill strategies of viral eradication. A detailed understanding of the transcriptional stochasticity of HIV-1 and the possibility to precisely model this phenomenon will be important assets to develop more effective therapeutic strategies.  HIV-1 infections can be effectively controlled using combined antiretroviral therapy (ART). Yet, viral latency is a major challenge for viral eradication from patients. Latent viruses harbored by cell and tissue reservoirs are invisible to the immune system but inevitably cause rebound upon ART interruption. The establishment and reactivation of latency have stochastic components, and HIV-1 has evolved mechanisms to benefit from the stochastic nature of transcription. In this review, we will present the current knowledge on HIV-1 transcriptional noise and its role in latency regulation.Cells display phenotypic differences even within isogenic populations occupying the same environment. These differences are often caused by stochastic variations in transcription, also called transcriptional noise, which lead to fluctuations in mRNA and protein levels ,2,3. NoiSources of noise can be extrinsic or intrinsic ,7. ExtriIn the simplest model, when a promoter is at steady state and constitutively active, RNA polymerases can bind to it and stochastically initiate transcription, leading to a Poissonian distribution of the RNA number per cell . Such a Gene expression noise plays an important role in the phenotypic diversity of cells and organisms. It has been shown to have important consequences for biological processes as diverse as the adaptation of bacterial and yeast populations to environmental changes, cell fate specification during organism development, responses to signaling and to pathogens, as well as the penetrance of mutations and the phenotypic diversity of twins ,27,28,29+ T cells and is formed within a few days after infection . T. T21]. TThe HeLa cell line with the 128 MS2-tagged HIV-1 reporter was used to study the response of the viral promoter to TNF-α activation . In the Importantly, TNF-α was also found to induce heterogeneous transcriptional responses of the HIV-1 promoter in Jurkat T cells . In thisThe studies above demonstrated that the HIV-1 promoter is noisy and that this noise affects latency. To better understand this noise, the factors and processes creating or affecting it were characterized using three single-cell methods: indirect live-cell imaging of HIV-1 transcriptional activity using GFP-tagged viruses (mainly LTR-GP-IRES-Tat-LTR (LGIT) reporter or Nef-GFP viruses); direct live-cell imaging of transcription using arrays of MS2 tags; and single-molecule FISH (smFISH) in fixed cells. in vivo with a variety of techniques, such as FRAP, dynamic ChIP and single-molecule tracking . Thview see ,110,111)view see ,109,111.view see . Single-view see .TBP is an essential factor that binds with high affinity to TATA box sequence and nucleates the assembly of the pre-initiation complex. As mentioned above, the HIV-1 promoter contains a TATA box . The traThe Sp1 and NF-κB binding sites of the HIV-1 promoter play essential roles in basal and activated transcription  and immediately after Nuc-1;  73]. Th. Th73]. The role of chromatin in noise was first probed with a viral vector lacking Tat and encoding a destabilized version of GFP (d2GFP). This virus was integrated in 30 different genomic locations in Jurkat cells and the expression noise was measured via flow cytometry. It was found that the noise depended on the viral integration site, with the mean expression and noise levels varying independently between clones . ChromatThe role of chromatin was also studied in the context of GFP-tagged viruses having the full Tat feedback loop, using the LGIT reporter or full-length Nef-GFP virus and integrating them at various locations in Jurkat cells ,117,118.The main role of Tat is to recruit P-TEFb on nascent viral RNAs, leading to the release of the polymerases paused near the promoter. The effect of pausing on HIV-1 transcriptional noise was studied using MS2-tagged HIV-1 reporters under variable levels of Tat expression in trans . As mentThe dynamic binding of nucleosomes and transcription factors to DNA creates intrinsic noise in transcriptional output ,108. MatPromoters bind a multitude of factors and harbor a variety of chromatin marks and nucleosome positions. This molecular diversity largely exceeds the number of kinetic transitions that can be identified from the data, which rarely exceeds three or four. However, it is reasonable to admit that the experimentally identified transitions correspond to rate-limiting steps, which are often the key steps regulating promoter function. The study of a promoter under a variety of conditions can reveal additional limiting steps and enables the development of more complete models . In thisFor promoter modeling, important considerations are the experimental approaches used to measure noise and the acquisition conditions. Direct transcriptional imaging using MS2 arrays enables single-molecule sensitivity and yields extremely precise information on promoter dynamics. However, because the polymerase dwell time at the transcription site is at most a few minutes , this meIt is important to mention that the above approaches yielded different models of transcription. While a simple two-state ON/OFF (random telegraph) model A was ablModels describing the HIV-1 promoter in the absence of the Tat feedback loop have been derived from direct transcription imaging using the MS2 system, in basal conditions or in the presence of Tat, which was provided in trans, as well as under TNF-α activation. As mentioned above, the data were fitted with more complex three-state models with several topologies: linear, branched or circular B–E 20,2,23. The In the absence of Tat, traditional models of pausing in which all polymerases undergo a pause did not fit experimental data D. When cThe HIV-1 promoter was also modeled under nonstationary conditions during TNF-α activation. In this case, two-state models with their rates depending on NF-kB concentrations did not fit the rapid transcriptional activation and shut-off that were observed. Instead, a directional cyclic model with a refractory state could accurately fit the data E 23]. T. T23]. TThe studies above yielded promoter transition rates in the order of minutes for the fast transitions  and tens of minutes to hours for the slow transitions (pausing in the absence of Tat or chromatin opening in The fact that the Tat feedback loop drives two alternative viral states raises the question of whether this circuit, which fuels its own activity and lacks a virally encoded repressor, is bistable ,70. MechIn vitro experiments showed that Tat acts as a monomer and single-cell measurements indicate that the Tat circuit does not exhibit cooperative effects, therefore it is likely not bistable [bistable . Insteadbistable  and was bistable ,123,124.bistable ,129,130.bistable ,130, whibistable ,128,129.bistable ,90. Tat bistable .A numerical analysis using a promoter model with a single ON state showed that, even in this case, the Tat acetylation–deacetylation cycle is sufficient not only for bimodality but also to maintain the stability of the inactive loop state G, unlikeThe effect of the Tat feedback loop was also investigated using promoter models having two or three states and in which Tat increases the rates of one or more transition steps ,118,134.Transcriptional noise should be taken into consideration while searching for an HIV-1 cure. Two possible strategies of latent reservoir eradication are currently under investigation. The “block and lock” strategy aims to permanently silence all latent proviruses to prevent rebound upon interruption of the therapy , whereasPrevious studies led to two theories of latency exit: activation of latent memory T cells or spontaneous activation of the Tat feedback loop by the intrinsic noise of the viral promoter ( and refeFirst, matching the kinetic promoter states to known molecular states of the HIV-1 promoter remains challenging. Indeed, the molecular identity of the various kinetic states deduced from live-cell fluctuation analyses remains incompletely characterized. Recent approaches such as single-molecule footprinting  allow alA second issue is to describe HIV-1 transcriptional noise in the cell types representing the most important viral reservoirs, such as memory T lymphocytes and macrophages. Indeed, we know very little about HIV-1 transcription in these cells, as most studies on HIV-1 noise were performed in simpler models such as HeLa or Jurkat cell lines. The third, still poorly understood, question is the role of extrinsic noise, both in basal transcription and in the heterogeneity of the responses to activating agents. While it is clear that the molecular promoter status plays a role, the cellular status is likely to be equally important. T cells are indeed known to occur in different states that have different capabilities to sustain HIV-1 transcription ,142, andFinally, while it was proposed that HIV-1 splicing buffers transcriptional noise , we may


Neuromodulation technology has provided novel therapeutic approaches for diseases caused by neural circuit dysfunction. Transcranial focused ultrasound (FU) is an emerging neuromodulation approach that combines noninvasiveness with relatively sharp focus, even in deep brain regions. It has numerous advantages such as high precision and good safety in neuromodulation, allowing for modulation of both peripheral and central nervous systems. To ensure accurate treatment targeting in FU neuromodulation, a magnetic resonance acoustic radiation force imaging (MR-ARFI) sequence is crucial for the visualization of the focal point. Currently, the commonly used 2D Spin Echo ARFI (2D SE-ARFI) sequence suffers from the long acquisition time, while the echo planar imaging ARFI (EPI-ARFI) sequence with a shorter acquisition time is vulnerable to the magnetic field inhomogeneities. To address these problems, we proposed a spatiotemporal-encoded acoustic radiation force imaging sequence  in this study. The displacement at the focal spot obtained was highly consistent with that of the SE-ARFI sequence. Our research shows that SPEN-ARFI allows for rapid image acquisition and has less image distortions even under great field inhomogeneities. Therefore, a SPEN-ARFI sequence is a practical alternative for the treatment planning in ultrasound neuromodulation. In SPEN-MRI, the traditional RF pulse used to excite spins is replaced by a linear chirp pulse, and a spatiotemporal encoding gradient is applied in the phase encoding direction. As a result, the phase profile of the spins has a quadratic shape, which increases the bandwidth of acquisition gradient in the phase encoding direction. Only the phase stable point and its adjacent area contribute to the SPEN-MRI signal, which reduces chemical shift artifacts and distortions caused by inhomogeneous magnetic fields, as compared to traditional SE-EPI or GRE-EPI images. Similar to SE-EPI, SPEN-MRI requires continuous application of fast-switching magnetic field gradients, but SPEN-MRI uses a special chirp pulse , thenThe linear scanning pulse in SPEN-MRI produces a parabolic phase profile. Unlike RF pulses traditionally used in MRI sequences with a fixed central frequency, the central frequency of the chirp pulse used in SPEN-MRI sequences changes linearly with time, producing quadratic phase modulation  can then be expressed aswhere R = ΔO/T represents the rate of change of the frequency of the chirp pulse. The phase that is accumulated during the excitation and the magnetic field generated by the chirp pulse can be expressed asy  between the opening time of FU and the application of DEG was investigated to maximize the displacement encoding. The averaged displacement Δx corresponding to the DEG can be obtained according to the following equationThe incorporation of a Displacement Encoding Gradient (DEG) is crucial for SPEN-ARFI imaging , Shanghai, China] with a 32-channel RF head coil. The FU transducer used to induce local displacements was an 800 kHz single-element design  with a focal depth of 5 cm. The instantaneous input electrical power used to generate the ARF was set to 170 Watts. For both agar phantom and ex vivo porcine brain, the ultrasound transducer was fixed above the object to be scanned, the duration of the FU ARF pulse was 21.76 ms, and images were acquired with the FU system turned on and off.All of the experiments were conducted in a whole-body 3.0T MRI system [ex vivo porcine brain images was acquired in the coronal orientation to determine the location of the target, followed by acquiring images through the target in the axial orientation. Since imaging times were short (125 ms per slice), phase changes that may be potentially produced by temperature changes were insignificant. The resistance of SPEN-ARFI and EPI-ARFI sequences to inhomogeneous magnetic fields was then assessed using the same parameters, and the image distortions were visually evaluated. Finally, the quantitative comparison experiment of SPEN-ARFI and SE-ARFI sequence was conducted using the ex vivo porcine brain, the same slice was scanned, and the FU parameters were kept consistent throughout the experiment. The maximum displacement was determined by calculating the average phase difference of nine pixels at the focal point, and the resulting average values obtained by the SE-ARFI sequence and SPEN-ARFI sequence were compared.First, we aimed to evaluate the imaging quality of the SPEN sequence in comparison to commonly used sequences by scanning the same slice of a water phantom with a FU transducer, the parameters used in this experiment are detailed in ex vivo porcine brain imaging were kept consistent, TE1 55 ms, TE2 125 ms, TE ranging from 55 to 125 ms, chirp pulse duration Te 20 ms and bandwidth 30.7 kHz, Ge 3 mT/m, DEG 50 mT/m, DEG duration 6 ms, slice number 8, and spacing between slices 7.5 mm. The SPEN-ARFI, EPI-ARFI, and SE-ARFI in this study used these common parameters: field of view (FOV) 200 × 200 mm, flip angle 90°, slice thickness 5 mm, TR 1,000 ms, and acquisition matrix 64 × 64. The TE of SE-ARFI was 50 ms, and the TE of EPI-ARFI was 100 ms in the comparison experiments.The SPEN-ARFI sequence parameters used in agar phantom and a) in the y direction acquired at time ta  Core (TM) i7-10875H CPU @ 2.30 GHz and a Nvidia GeForce RTX 2060 4GB. Images were reconstructed offline from the K-space data sampled in Cartesian coordinates by using programs coded in MATLAB software. To obtain the baseline phase information, we calculated and compensated for the quadratic phase according to the corresponding chirp pulse parameters during image reconstruction. The signal S(tThe position-related quadratic term can be removed by the following equationa) is the signal acquired at time ta after removing the quadratic term that has the largest influence on the visualization of the focal point, ρ0(y) is the spin density at position y , it can be seen that a large bandwidth was chosen in this study, which allowed the SPEN-ARFI sequence to exhibit robustness against magnetic field inhomogeneities and obtain images with high spatial resolution albeit at the cost of reduced SNR in the images. Conversely, selecting a smaller bandwidth would diminish the benefits of SPEN-ARFI but improves the imaging SNR. Nonetheless, SPEN-ARFI has several limitations. Eddy currents can result in stripe artifacts on the phase map, as shown in The present study presents a novel technique for acoustic radiation force imaging called the SPEN-ARFI sequence. Compared to conventional acoustic radiation force imaging methods, SPEN-ARFI offers superior imaging speed and enhanced tolerance toward magnetic field inhomogeneity. Overall, the SPEN-ARFI sequence represents a promising development in the field of acoustic radiation force imaging.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.in-vitro porcine brain, commercially available at supermarkets) and so this did not need to be approved by the IRB and IACUC.Ethical review and approval was not required for the animal study because this study does not involve investigations in human subjects or living animals (we just use an JZ, HX, QH, and QG contributed to conception and design of the study. DK and XQ organized the database. XQ and YD did sequence tests. XQ wrote the first draft of the manuscript. JS, XH, and NR wrote some manuscripts. All authors participated in the revision, reading, and approval of the submitted version of the manuscript.