LEAFY and AGAMOUS. We selected events with previously characterized CRISPR-Cas9 induced biallelic changes then re-transformed them with the Arabidopsis thaliana FLOWERING LOCUS T (AtFT) gene under control of either a strong constitutive promoter or a heat-inducible promoter. We successfully obtained flowering in both a male and female clone of poplar, observing a wide range of inflorescence and floral forms among flowers, ramets, and insertion events. Overall, flowers obtained from the selected LFY and AG targeted events were consistent with what would be predicted for loss-of-function of these genes. LFY-targeted events showed small catkins with leaf-like organs, AG-targeted events had nested floral organs consistent with reduction in floral determinacy and absence of well-formed carpels or anthers. These findings demonstrate the great developmental plasticity of Populus flowers during genetically accelerated flowering, which may be of horticultural value. They also provide an informative early view of floral phenotypes and apparent sterility from knockouts of both these gene targets.Plant migration and gene flow from genetically modified or exotic trees to nearby lands or by crossing with wild relatives is a major public and regulatory concern. Many genetic strategies exist to mitigate potential gene flow; however, the long delay in onset of flowering is a severe constraint to research progress. We used heat-induced FT overexpression to speed assessment of the expected floral phenotypes after CRISPR knockout of poplar homologs of the key floral genes,  The movement or gene flow from genetically modified, domesticated, or potentially invasive plant species to wild lands or into sexually compatible relatives is a substantial public and regulatory concern. Many forestry and horticultural species are grown outside of their native range, and some have become invasive due to their ability to propagate within those environments . Many stLEAFY (LFY) and AGAMOUS (AG) have been at least partly successful in attenuating fertility in apple [As knowledge of the molecular biology of flowering has grown, methods that seek to suppress or eliminate the functions of key, highly conserved floral genes for genetic containment have grown. For example, RNAi directed against the floral genes in apple , sweetguin apple , and popin apple . Where tin apple , 9. Our in apple , 11 and in apple . In the Many strategies have been tried to obtain faster flowering in tree species. These include, altering the photoperiod , hormonePopulus, different clones showed different degrees of floral induction, even for the same genetic construct tested at the same location [LFY in Eucalyptus used two separate populations for this very reason; one set of trees with CRISPR-derived gene edits and Arabidopsis thaliana FLOWERING LOCUS T (AtFT) overexpression was used for evaluation of floral form, while CRISPR edited trees  was used for the analysis of overall juvenile tree form and growth [Most research on genetically-accelerated flowering relies on stable transformation, for which a variety of promoter and gene combinations have been employed to overexpress floral inductive genes . Nearly location , 40,  to suppress LFY and AG in poplar showed modification of female floral form and loss of seed formation under natural flowering in field conditions [LFY or both AG-like genes, and successfully obtained a large number of independent events with bi-allelic targeting of one or both target genes [FT transgenes. In prior work, we tested a variety of floral induction constructs to inform our choice of promoter and gene [AtFT system was the most efficient. Such an approach should reduce the strong impacts of FT overexpression on vegetative form [AtFT system has been previously used to evaluate male sterility in poplars [LFY and AG knockouts are expected to lack any pollen production. We report a high rate of successful flowering induction, and in knockouts we observed the expression of a wide range of floral phenotypes that are congruent with expectation for these genes and suggest that there will be a high rate of floral sterility in normally flowering trees.Here, our main goal was to use genetically-accelerated flowering to obtain an early view of floral morphology on male and female clones of poplar that have been CRISPR-mutated at the poplar nditions , 21, 42.et genes . Selecteand gene , for whiive form , 29, 35. poplars , 38. One poplars . However poplars . TherefoAtFT. Overall, female clone 717 had a lower rate of flowering than male clone 353. Of the two different Populus tremula x Populus tremuloides clones, we achieved flowering with clone 353 but not with clone T89. From these findings, we created an experimental plan to induce early-flowering in selected CRISPR trees in clones 353 and 717 by re-transforming selected events with either constitutive or heat-inducible floral constructs (We tested four different constructs for inducing early-flowering. We achieved flowering rates ranging from 0% to 48.5% of events (independent gene insertions) within each of the two tested clones . The pronstructs .LFY or to both AG genes. We selected a set of previously characterized Cas9 control and CRISPR events in male clone 353 and female clone 717 [LFY or bi-allelic changes in both AG1 and AG2 (AG events were generated using two sgRNAs and were named DAG events (for double sgRNA in AG). Chosen LFY targeting events either had one sgRNA and were named LIC events, or two sgRNAs and were named DL (for double targeting of LFY) events. For chosen LFY events, the single targeting site was located within Exon 1, while the second sgRNA target site was located prior to the coding region, such that events with large deletions no longer retained the start codon. For the AG events chosen, the sgRNA target sites were located within Exon 1. All selected events were used for two approaches  gave 52.2% and 83.3% flowering by sub-event . These carpels were typically present in the basal area of the catkin and were surrounded by anthers. Retransformation of AG events 142 and 167 led to production of atypical catkins  and clouds are sparse.We selected CRISPR events that had been previously characterized regarding allele changes in target genes but had yet to undergo floral phenotype evaluation . Chosen FT are used [FT system, both clones showed no significant difference in tree size between heat-induced flowering and non-flowering trees , as producing fertile heat-induced poplar flowers requires highly specific growth conditions . We instlone 717 , 7. Thes flowers . Howeverpromoter . As alsoAG1 and AG2 led to flowers with replicated floral structures in both our male and female trees, indicative of a loss of floral determinacy  depending on plant size and meristem position [FT [We observed striking variation in floral form, both within and between ramets and gene insertion events. Variable floral form may be of horticultural interest, as a single plant could exhibit great variation in floral form during the growing season under normal variation in temperature. This phenomenon has been observed in multiple species, with flowering differing within a single shoot, between shoots of a single plant, or between individuals in a single population . This ouposition , and thetion [FT . There mtion [FT .Chimerism for knockout mutations may be another cause of variation in floral form within trees and events. However, initial characterization of CRISPR lines used to select these particular events for re-transformation found a very low level of suspected chimerism and no evidence of off-target changes for a subset of CRISPR sites similar to those targeted . A priorAtFT-only flowering control and Cas9-only control trees. Such bisexual flowers on male clone 353 have been documented previously for genetically accelerated flowering trees in the greenhouse [LFY events in 353 as we previously observed in naturally flowering field-grown RNAi-LFY trees [We observed bi-sexual flowers in clone 353 . These feenhouse . We did FY trees . This diLFY and AG genes in poplar. The marked variability in floral form we observed shows the striking developmental plasticity of flowering onset and morphology and suggests possible new means to create floral diversity of horticultural value.Heat-induced rapid flowering enabled us to observe strong effects on floral form and fertility from knockouts of the www.expasy.org/translate). Predicted LFY peptides were aligned to compare WT LFY alleles of both 717 and 353 with mutants in those clones. Peptide alignments were created using Clustal Omega [The previously obtained allele sequence information  was usedal Omega .AtFT vector, the FT gene from Arabidopsis thaliana was cloned into the vector pCAMBIA under control of a heat-shock inducible promoter  using a meter stick. All ramets were screened for the presence or absence of catkins or catkin-like structures. Ramets with at least 1 catkin or catkin-like structure were scored as flowering. Events were scored as flowering if at least 1 ramet from that event was scored as flowering. Whole plants were photographed using a Canon Rebel XSI digital camera as were whole catkins. Detached catkins were imaged using a Keyence digital dissecting microscope.Web_Material_uhad132Click here for additional data file.


We report a case of impending central retinal vein occlusion (CRVO) due to antiphospholipid syndrome (APS) complicated by paracentral acute middle maculopathy (PAMM). A 42-year-old man with no medical history acutely presented with blurred vision in his right eye. The best-corrected visual acuity was 20/20 in the right eye, but the Goldman visual field test showed a dark spot over the superior nasal region of the right eye. Fundus examination showed dilated and tortuous retinal veins of the right eye with delayed filling of the inferior retinal veins on fluorescein angiography. Optical coherence tomography (OCT) showed a hyperreflective lesion confined to the inner nuclear layer (INL), consistent with PAMM. After several weeks, his symptoms improved, and the dilated retinal vein and the INL hyperreflexia on OCT were reduced. Multiple positive findings for anti-cardiolipin antibodies were confirmed; therefore, he was diagnosed with APS and treated with aspirin. If the impending CRVO is associated with visual impairment, the complication of PAMM should be considered. In the presence of retinal vasculopathy without atherosclerotic factors, APS should be considered. Paracentral acute middle maculopathy (PAMM) is a middle retinal layer imaging sign characterized by a hyper-reflective area of the inner nuclear layer (INL) on optical coherence tomography (OCT) . AlthougCentral retinal vein occlusion (CRVO) is a cause of sudden visual loss and is classified as either ischemic or non-ischemic depending on the presence of retinal ischemia. In some cases, macular edema may develop, thereby leading to visual dysfunction. Impending CRVO exhibits no hemorrhage or only a few hemorrhages with dilated and tortuous vessels and is rarely associated with visual disturbance . Risk faAntiphospholipid syndrome (APS) is an autoimmune thrombosis caused by antiphospholipid antibodies and often leads to various thrombotic events such as cerebral infarction, deep vein thrombosis, or complications during pregnancy. Several retinal circulatory disorders, such as CRVO or ischemic optic neuropathy, have been reported in association with APS .The present report describes a case of APS presenting with an impending CRVO with PAMM.A 41-year-old man with no relevant medical history noticed sudden blurred vision in the upper field of his right eye. As his symptoms did not improve, he visited our clinic on the third day since the onset. At the initial examination, the best-corrected visual acuity (BCVA) was 20/20 OU, and the intraocular pressure was 14 mmHg OU. A Goldman visual field test revealed a dark spot over the superior nasal region of the right eye Figure . Slit-laOCT revealed the presence of a hyper-reflective lesion that was confined to the INL in the parafoveal area of the right eye Figure , leadingBlood tests revealed elevated anti-cardiolipin antibodies at a level of 13.1 U/mL. As positive findings for anti-cardiolipin antibodies were recognized on three consecutive occasions at the Department of Internal Medicine, he was subsequently diagnosed with APS. To prevent a recurrence, the patient was treated with aspirin and has been free of thrombotic events to date.We observed a case of PAMM due to impending CRVO in an adult male without atherosclerotic factors. After the spontaneous resolution of the PAMM, his symptoms improved. After searching for the cause of the thrombosis, a diagnosis of APS was made. As impending CRVO is unlikely to cause vision loss , PAMM shThe retinal capillary network is a multilayered capillary network consisting of radial peripapillary capillaries (RPC), superficial capillary plexus (SCP), and deep capillary plexus (DCP) . PAMM isIn addition to CRVO, PAMM may be caused by localized retinal ischemia, which includes central retinal artery occlusion (CRAO), BRAO, diabetic retinopathy, hypertensive retinopathy, and Purtscher’s retinopathy ,9. SysteAPS can lead to a variety of ocular complications . The mosPAMM is a feature of ischemic retinal disease such as CRVO and should not be overlooked in the setting of visual impairment. APS should be considered during the search for the cause of retinal vasculopathy without atherosclerotic factors.


A previously healthy, 4-year-old boy visited our emergency department due to chest pain after a fall from a skate scooter. Physical examination revealed tenderness over the sternal body. Point of care ultrasound (POCUS) of the sternum demonstrated a discontinuation of a hyperechoic structure of the sternal cortex, suggesting a sternal fracture. POCUS did not detect intraperitoneal fluid, pericardiac effusion, or pneumothorax. Plain radiograph confirmed the diagnosis of isolated sternal fracture and the patient was discharged with conservative treatment. POCUS was useful not only in diagnosing a sternal fracture but also to rule out concurrent injuries. Sternal fractures in children are uncommon because of the marked chest compliance A previously healthy, 4-year-old boy visited our emergency department due to chest pain. Chest injury was sustained from hitting the handle bar while falling off a skate scooter. He denied any accompanying symptoms such as palpitation, syncope, or vomiting. He was alert and his vital signs were appropriate for his age. Physical examination revealed tenderness over the sternal body, but no tenderness over the ribs or abdomen. His lung auscultation was clear with bilateral equal air entry, and his heart rhythm was regular without murmurs. A pediatric emergency physician with five years’ experience using pediatric POCUS performed a scan using Sonosite EDGE II with a high-frequency linear transducer (8-13 MHz). The patient was placed in a supine position, and the transducer was placed transversely and longitudinally over the sternum  Based on the findings, the diagnosis of a non-displaced sternal fracture was made. Plain radiography of the sternum confirmed this . Pneumothorax or pulmonary contusion was not reported on the plain radiograph. Electrocardiogram (ECG) showed normal sinus rhythm with no arrythmias or ST-T wave changes. EFAST (extended focused assessment on ultrasonography for trauma) did not reveal pneumothorax or cardiac tamponade, and FoCUS (Focused cardiac ultrasound) showed good left ventricular contraction. The patient was diagnosed with an isolated sternal fracture. He was managed conservatively and discharged from the emergency department. The patient remained asymptomatic and had no complications when reviewed by the cardiac surgeon one week later.In our case presented, POCUS guided the diagnosis of a pediatric sternal fracture in the emergency department setting. Reports of ultrasound (US) use in diagnosing sternal fractures are scarce. A case-series study demonstrated two cases of pediatric sternum fractures caused by blunt chest trauma, with US performed by radiologists Sternal fracture in children is uncommon with its annual prevalence of 0.43/100,000 POCUS has the potential to be an invaluable tool in diagnosing sternal fracture in children. Ultrasonography is more sensitive for diagnosing sternal fractures compared to plain radiography. A meta-analysis of diagnostic accuracy for diagnosing thoracic bone fractures demonstrated that the sensitivity and specificity of US for diagnosing sternal and/or clavicle fractures were 77% (95% CI: 48-100%), and 100% (95% CI: 100-100%), although the patient population was adults and US was performed by radiologists in most of the studies POCUS can expedite and enhance management by evaluating for concurrent injuries associated with sternal fracture. As mentioned above, pneumothorax, rib fracture, cardiac tamponade, and abdominal injuries are known associates of sternal fracture, which necessitate rapid intervention Last but not least, POCUS is a non-invasive and radiation-free diagnostic modality. CT or MRI are at times required to confirm the diagnosis in patients with suspected sternum fracture despite a reportedly normal radiograph. However, these modalities often require procedural sedation and/or radiation exposure which increases children’s lifetime risk of malignancies Despite image acquisition and interpretation being operator-dependent and training and experience being required to ensure good quality image The present report did not receive any specific grant from any funding agencies in the public, commercial or not-for-profit sectorsThe authors declare that there are no conflicts of interest associated with this manuscriptWritten informed consent to publish details of this case was obtained from the patient’s mother.Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.


The COVID-19 pandemic has necessitated the rapid development and implementation of whole-genome sequencing (WGS) and bioinformatic methods for managing the pandemic. However, variability in methods and capabilities between laboratories has posed challenges in ensuring data accuracy. A national working group comprising 18 laboratory scientists and bioinformaticians from Australia and New Zealand was formed to improve data concordance across public health laboratories (PHLs). One effort, presented in this study, sought to understand the impact of the methodology on consensus genome concordance and interpretation. SARS-CoV-2 WGS proficiency testing programme (PTP) data were retrospectively obtained from the 2021 Royal College of Pathologists of Australasia Quality Assurance Programmes (RCPAQAP), which included 11 participating Australian laboratories. The submitted consensus genomes and reads from eight contrived specimens were investigated, focusing on discordant sequence data and findings were presented to the working group to inform best practices. Despite using a variety of laboratory and bioinformatic methods for SARS-CoV-2 WGS, participants largely produced concordant genomes. Two participants returned five discordant sites in a high-Cτ replicate, which could be resolved with reasonable bioinformatic quality thresholds. We noted ten discrepancies in genome assessment that arose from nucleotide heterogeneity at three different sites in three cell-culture-derived control specimens. While these sites were ultimately accurate after considering the participants’ bioinformatic parameters, it presented an interesting challenge for developing standards to account for intrahost single nucleotide variation (iSNV). Observed differences had little to no impact on key surveillance metrics, lineage assignment and phylogenetic clustering, while genome coverage <90 % affected both. We recommend PHLs bioinformatically generate two consensus genomes with and without ambiguity thresholds for quality control and downstream analysis, respectively, and adhere to a minimum 90 % genome coverage threshold for inclusion in surveillance interpretations. We also suggest additional PTP assessment criteria, including primer efficiency, detection of iSNVs and minimum genome coverage of 90 %. This study underscores the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria. It demonstrates the potential for enhancing public health responses through improved data concordance and quality control in SARS-CoV-2 genomic analysis during pandemic surveillance. The authors confirm that all supporting data, code and protocols have been provided within the article or through supplementary data files.Amidst the COVID-19 pandemic, a unique collaboration between a national multidisciplinary working group and a quality assurance programme facilitated ongoing development of standardized quality control criteria and analysis methods for high-quality SARS-CoV-2 genomic approaches across Australia. With this article, we shed light on the robustness of amplicon sequencing and analysis methods to produce highly concordant genomes, while also presenting additional assessment criteria to guide laboratories in identifying areas for improvement. Insights from this nationwide collaboration underscore the need for real-time knowledge-sharing and iterative refinements to quality standards, particularly as situations and methods evolve during a pandemic. While the spotlight is on SARS-CoV-2, the analyses and findings have universal implications for genomic surveillance during infectious disease outbreaks. As WGS becomes increasingly central in outbreak surveillance, continuous evaluation and collaboration, like that described here, are vital to ensure data accuracy and inform future public health responses.The global scientific community responded to the coronavirus disease COVID-19) pandemic with the rapid development of laboratory and bioinformatic data analysis methods for whole-genome sequencing (WGS) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These methods have been widely adopted, with more than 45 countries conducting routine genomic surveillance 9 pandemi.Amplicon sequencing is the main method of SARS-CoV-2 WGS, with bioinformatic methods dependent on the platform . PreviouAustralia and New Zealand have been at the forefront of using fine-scale genomic data to manage their COVID-19 responses. Genomic data are shared via AusTrakka to provide context for local and interstate transmission. AusTrakka is a national real-time pathogen genomics surveillance platform for public health laboratories that facilitates analytical harmonization and national reporting as well as provides equitable access to computational resources and expertise . AustralIn July 2020, the Medical Research Future Fund (MRFF) COVID-19 Quality Control Working Group (WG), supported by the Communicable Diseases Genomics Network (CDGN), initiated a concertorming guidelines in real timed effort to harness genomic sequencing for an enhanced response to the COVID-19 pandemic. Comprised of 18 public health laboratorians and bioinformaticians from Australia, the WG’s primary objective was to establish a framework that ensures laboratory and bioinformatic standards and quality control, permitting procedural adaptability yet ensuring consistent SARS-CoV-2 genomic data. Continuous communication among laboratory technicians and bioinformaticians was maintained via monthly meetings and regular online discussions via Slack, facilitating protocol optimization and addressing potential sequencing and analysis challenges in real time.The WG aimed to enhance interlaboratory data concordance but faced challenges in coordinating a national validation study during pandemic surges. Consequently, the WG procured SARS-CoV-2 WGS proficiency testing programme (PTP) data from the Royal College of Pathologists of Australasia Quality Assurance Programmes (RCPAQAP) for retrospective, in-depth bioinformatic analyses. In the study presented here, PTP data were used to characterize discordant SNVs and investigate bioinformatic quality control standards for remediation. Submitted consensus genomes were used to evaluate the effect of discordant SNVs on key surveillance metrics, lineage assignment and phylogenetic clustering, while submitted read data were used to investigate discordant sites. Finally, we reflect on the importance of multidisciplinary national working groups in informing guidelines in real time for bioinformatic quality acceptance criteria under the competing demands of a pandemic.Data were obtained from the 2021 RCPAQAP SARS-CoV-2 WGS PTP, sample characteristics and methods have previously been described . BrieflyN=8) were sent to 11 participating laboratories for WGS using each laboratory’s standard procedure. The raw reads of sequence data without preprocessing or trimming and the derived consensus sequence data, as submitted by the participants, were assessed based on three quality metrics , as decided with input from CDGN Genomics Implementation and Bioinformatics Working Groups  and previously described by Lau et al.  we did observe that false SNVs occurred near primer sites, which could signal the need for bioinformatic troubleshooting by the participant.For PHLs actively involved in WGS quality control, they typically possess greater familiarity with methods tailored for prokaryotic pathogens, where shotgun sequencing of isolates is routinely conducted . The cha to iVar . Althouget al. [et al. [Similar to Foster et al.  6], we , we et a [et al. . A good et al. [Since the PTP analysed here concluded in 2021, several laboratory and bioinformatic developments have occurred, reflecting the evolving nature of the emergent pandemic response. The ARTIC primer scheme was redesigned in terms of laboratory methods and commercial schemes were offered to account for increasing variation . From a et al.  and recoet al. . These dA key advantage of the WG was the real-time collaboration and knowledge-sharing to form living guidelines by continually reviewing and updating the quality standards for SARS-CoV-2 WGS. One member noted that by comparing results across laboratories and methodologies, they could identify and rectify a spurious SNV impacting tree topology, which stemmed from a specific primer set. Another highlighted the utility of the Slack channel, finding it valuable for accessing bioinformatic tools shared by colleagues, thereby enriching their analytical processes. Amid the pressing challenges of pandemic surges in PHLs, this collaborative approach promoted bioinformatic equity via shared expertise and distributed tasks. Additionally, it offered a dynamic platform for discussing the continuously evolving understanding and demands associated with the virus.Given this was a retrospective analysis, we must consider that the PTP was not designed for the study at hand. While it offered a dataset reflecting SARS-CoV-2 WGS methodologies across Australia, its design posed challenges for our comparative analysis. Issues included data entry mistakes and inconsistencies in the PTP questionnaire responses. The questionnaire aimed to gauge the ability of participants to accurately report and convey results, but our analysis highlights potential challenges PHLs faced during pandemic surges. This might also underscore varying PHL capabilities in recognizing critical bioinformatic traits. For future reference, multidisciplinary working groups might consider creating an intuitive bioinformatic analysis platform for participants to upload data and obtain technical feedback, like the metrics described here. These insights would increase bioinformatic analysis equity and provide PHLs with data-driven strategies to inform living guidelines, facilitating sequence data concordance as knowledge and methods evolve throughout a pandemic.Despite the variety of laboratory and bioinformatic methods used for SARS-CoV-2 WGS, the results were largely accurate. However, challenges such as low read depths and inconsistent amplicon sequencing coverage were observed, and variants at positions with read depths below ten require careful consideration. We recommend PHLs bioinformatically generate two consensus genomes for distinct purposes: (1) quality control with ambiguity codes and a strict frequency threshold; and (2) downstream analysis without ambiguity codes. We also suggest implementing the following assessment criteria: (1) per-amplicon read depth as an indicator of primer efficiency; (2) SNVs to consider intrahost variation; and (3) a minimum genome coverage of 90 %. In a genomics-forward era of public health pathogen surveillance, our study emphasizes the role of multidisciplinary working groups in providing technical analysis and feedback for sequence data concordance across PHLs. We also present additional assessment criteria to guide laboratories in identifying areas for improvement.Click here for additional data file.Click here for additional data file.


Photoreceptor degeneration underpinned by oxidative stress-mediated mitochondrial dysfunction and cell death leads to progressive and irreversible vision impairment. Drug treatments that protect against photoreceptor degeneration are currently available in the clinical settings. It has been shown that hyperoside, a flavonol glycoside, protects against neuronal loss in part by suppressing oxidative stress and maintaining the functional integrity of mitochondria. However, whether hyperoside protects against photoreceptor degeneration remains unknown.To address the pharmacological potentials of hyperoside against oxidative stress-mediated photoreceptor degeneration on molecular, cellular, structural and functional levels, multiple in vitro and in vivo methodologies were employed in the current study, including live-cell imaging, optical coherence tomography, electroretinography, histological/immunohistochemical examinations, transmission electron microscopy, RNA-sequencing and real-time qPCR.The in vitro results demonstrate that hyperoside suppresses oxidative stress-mediated photoreceptor cell death in part by mitigating mitochondrial dysfunction. The in vivo results reveal that hyperoside protects against photooxidative stress-induced photoreceptor morphological, functional and ultrastructural degeneration. Meanwhile, hyperoside treatment offsets the deleterious impact of photooxidative stress on multiple molecular pathways implicated in the pathogenesis of photoreceptor degeneration. Lastly, hyperoside attenuates photoreceptor degeneration-associated microglial inflammatory activation and reactive Müller cell gliosis.All things considered, the present study demonstrates for the first time that hyperoside attenuates oxidative stress-induced photoreceptor mitochondrial dysfunction and cell death. The photoreceptor-intrinsic protective effects of hyperoside are corroborated by hyperoside-conferred protection against photooxidative stress-mediated photoreceptor degeneration and perturbation in retinal homeostasis, warranting further evaluation of hyperoside as a photoreceptor protective agent for the treatment of related photoreceptor degenerative diseases. The retina consists of multiple orders of neurons that collaboratively conduct light-sensing and vision-forming functions. Photoreceptors are the first-order retinal neurons carrying out specialized light-sensing and phototransduction functions, thereby contributing in an indispensable manner to the initiation of the visual processes . RegardlThe general consensus of the mechanisms underpinning photoreceptor cell death irrespective of the etiologies centers on the heightened level of oxidative stress . OxidatiCuscuta chinensis Lam., an herbal medicinal that is conventionally used for the treatment of vision impairment in traditional Chinese medicine, is effective at protecting against oxidative stress-mediated photoreceptor degeneration .TRIzol reagent  was used for isolating RNA from the mouse retinas. PrimeScript RT Master Mix  was then used for reverse transcription. The expression of P < 0.05.Data were expressed as mean ± standard error of mean (SEM) or mean ± standard deviation (SD). Statistical analyses were performed by one-way or two-way ANOVA with the Tukey’s multiple comparisons test . Statistically significance was defined if To directly assess the hypothesis that hyperoside protects against oxidative stress-induced mitochondrial impairment and cell death, 661W cells were subjected to SNP treatment, which has been shown to induce photoreceptor cell death by triggering reactive oxygen species (ROS) production in mitochondria . Real-tiNext, to directly verify the protective effects of hyperoside against oxidative stress-mediated photoreceptor degeneration in vivo, photooxidative stress-mediated photoreceptor degeneration was modeled in Balb/c mice. Seven days after the experimental light exposure, full-retinal morphological views were obtained from OCT imaging to gain an objective assessment of the pharmacological effects of hyperoside on the photoreceptor morphology Fig. A. The thHistological and immunohistochemical examination was subsequently performed to further characterize the protective effects of hyperoside on photoreceptors. Given that a nearly complete protection of the photoreceptor structure and retinal function was observed when hyperoside was administered at 50 mg/kg Figs.  and 4, tIn addition, the in situ expression of rod photoreceptor-specific rhodopsin as well as cone photoreceptor-specific M-opsin and S-opsin was assessed to visualize the protective effects of hyperoside on rod and cone photoreceptors, respectively. For this purpose, cryosections were made 6 h, 1d, 3d and 7d after illumination and subjected to IHC examination. As shown in Fig. Next, to validate the protective effects of hyperoside on photoreceptors in greater detail, the retinal ultrastructure was examined by TEM. First, in distinct contrast to the normal ultrastructural features observed in photoreceptors from the NLE mice, overtly disorganized OS membrane discs and disrupted connecting cilium were readily observed in the LE retinas. Secondly, phagocytosed membrane discs were evident in the neighboring retinal pigment epithelium (RPE). The apical microvilli of RPE cells also became irregularly shaped and disorganized Fig. A. ThirdlEverything considered, the results from the histological, immunohistochemical and ultrastructural examinations demonstrate that hyperoside confers significant protection to the photoreceptor morphological integrity under photooxidative stress conditions.To further understand the molecular mechanisms associated with the photoreceptor protective effects of hyperoside, the retinas were collected 1d post illumination, a time point prior to significant loss of photoreceptors were noted Fig. A, and suCrx, Nr2e3 and Nrl  exhibited altered expression in the LE retinas. Meanwhile, altered expression of Gfap and Glul was also noted in the LE retinas, indicating reactive gliosis of Müller cells. However, hyperoside treatment counteracted the deleterious impact of the experimental light exposure on the retinal expression of these genes (Fig. In addition to degenerative pathologies manifested by photoreceptors per se, glial cells responsible for the maintenance of retina homeostasis also undergo reactive changes during the course of photoreceptor degeneration. It is known that photoreceptor degeneration is accompanied by neuroinflammation, a hallmark event signifying disturbed retinal homeostasis . Photorenes Fig. A. Real-tnes Fig. B–E. IHC nes Fig. G. CollecIn the present study, we demonstrate that hyperoside is pharmacologically active at protecting against oxidative stress-induced mitochondrial impairment and photoreceptor cell death in vitro. Most importantly, these cell-intrinsic photoreceptor protective activities of hyperoside are translatable in vivo as hyperoside attenuates photooxidative stress-induced photoreceptor degeneration on molecular, cellular, structural and functional levels. Moreover, hyperoside treatment counteracts neuroinflammatory responses and reactive alterations in microglia and Müller cells in the retina, providing additional evidence supporting the pharmacological significance of hyperoside in maintaining retina homeostasis under photooxidative stress conditions.Our major findings here relate to the pharmacological implications of hyperoside in suppressing oxidative stress-mediated photoreceptor degeneration. Oxidative stress plays a pivotal role in triggering cell death, which is especially relevant in the case of photoreceptor cell death, the key cellular mechanism underlying photoreceptor degeneration . This isAside from photoreceptors, it is worth noting that hyperoside treatment attenuates photoreceptor degeneration-associated neuroinflammatory responses and microglial activation in the retina. Retina is a complex neuronal tissue consisting of various types of neurons to execute the essential function of vision formation as well as non-neuronal cells that provide a supportive microenvironment underpinning the normal structural and functional homeostasis of the retina. Among the non-neuronal cellular constituents of the retina, glial cells, namely microglia, astrocytes and Müller cells, are equipped with important functions for maintaining a homeostatic microenvironment in the retina . The patGlul. Glutamine synthetase is primarily responsible for catalyzing the conversion of glutamate, a neurotransmitter that mediates normal excitatory synaptic transmission, to glutamine, the precursor of glutamate, thereby playing an essential role in regulating the glutamate-glutamine cycle, the shuttle of glutamate and glutamine between neurons and Müller cells. Inhibition of the glutamine synthetase leads to disturbed glutamate–glutamine cycle, causing marked reduction in the function of the retinal neurons including photoreceptors [Glul expression can therefore directly cause insufficient metabolism of glutamate released by damaged photoreceptors, further exacerbating photoreceptor cell death. On the other hand, increasing the expression of glutamine synthetase confers protection against retinal degeneration [Gfap and simultaneous downregulation of Glul. Meanwhile, aberrant expression pattern of Gfap is notable throughout the course of photoreceptor degeneration. These observations indicate that reactive gliosis of Müller cells is not only a phenotype of disturbed retinal homeostasis, it is also actively involved in the progression of photoreceptor degeneration under photooxidative stress conditions. Hyperoside treatment results in decreased expression of Gfap and increased expression of Glul in the light-exposed retinas. Meanwhile, the expression pattern of Gfap in the HYP retinas remains comparable to the NLE retinas. These results further highlight the beneficial impact of hyperoside on the retinal homeostasis under photooxidative stress conditions. However, whether hyperoside exerts direct impact on the pathophysiological changes in Müller cells remains to be investigated.In addition to the impact on microglia, the suppressive effects of hyperoside on the reactive gliotic pathologies of Müller cells are also worth noting. Müller cells are not only the predominant glia of the retina, they are also the only glia specifically found in the retina. Müller cells closely interact with the retinal neurons including photoreceptors to maintain a homeostatic environment by regulating the metabolism as well as the extracellular milieu essential for the survival and normal function of the retinal neurons. Nearly all known retinal disorders are associated with a reactive gliotic changes in Müller cells, which is characterized by aberrantly upregulated expression of Gfap . Althougeceptors . Injuredneration . Thus, gneration . Our finThe current work sheds new light on the pharmacological mechanisms of hyperoside in photoreceptor protection. Multiple levels of evidence presented here support the notion that hyperoside is pharmacologically effective at protecting against oxidative stress-mediated photoreceptor degeneration in part by suppressing oxidative stress-induced mitochondrial impairment and photoreceptor cell death. In addition, our findings here unveil that hyperoside treatment mitigates reactive gliosis in microglia and Müller cells in the retina, supporting the beneficial effects of hyperoside on maintaining retinal homeostasis under photooxidative stress conditions.


To determine the impact of a longitudinal, near-peer, dedicated ECG didactic curriculum on internal medicine resident ability to accurately interpret ECGs.This study employs a prospective cohort design. Internal medicine residents at University at Buffalo participated in monthly ECG didactic sessions over a 7-month period. Residents were invited to complete pre- and post-curriculum questionnaires. Responses were anonymous and participation voluntary. Data collected included basic demographics, career interest, exposure to clinical cardiology, and number of sessions attended. Residents were asked to interpret sixteen unique ECGs, divided evenly among eight common rhythms into both questionnaires. Pre- and post-curriculum cohorts were compared using t-tests and chi-square analyses. Associations between attendance, comfort level in interpretation, and number of correct interpretations were analyzed using Pearson correlations. Multivariate linear regression determined the strongest predictor of the number of correct ECG interpretations.p < .001). Didactic attendance was significantly associated with comfort level in interpreting ECGs  and trended towards an increased number of correct interpretations . Residents who attended three or more sessions demonstrated increased ECG interpretation skills compared to those who attended two or fewer sessions . Number of clinical cardiology rotations attended was significantly associated with correct interpretations  and was the strongest predictor of accurately interpreting ECGs .The post-curriculum cohort correctly interpreted a significantly greater percentage of ECGs compared to pre-curriculum cohort (74.5% vs. 60.9%, Participation in a longitudinal, near-peer ECG didactic curriculum improved resident ability to interpret ECGs. A curriculum which contains both didactic sessions and clinical exposure may offer the greatest benefit in improving ECG interpretation skills. The electrocardiogram (ECG) is one of the most commonly employed diagnostic tests in medicine. ECGs offer a simple, non-invasive, and cost-effective method for the early detection and diagnosis of cardiovascular disease , 2. HoweResidents are often responsible for initial interpretation of ECGs and for implementing appropriate treatment decisions based on their findings. Although many medical school curricula include an introduction to ECGs, residents enter their training with varying competency in ECG interpretation , 7. The Despite the recommendations from these professional societies, there exists no consensus on the best methods for teaching ECG interpretation to residents . CommonlWe recently implemented a cardiology fellow-led ECG didactic curriculum for the Internal Medicine Residency Training Program at The University at Buffalo (State University of New York). This study builds upon our prior research demonstrating improvement in resident comfort-level in interpreting ECGs following this curriculum . Herein,The University at Buffalo’s Internal Medicine Residency Training Program’s near-peer, didactic ECG curriculum aims to educate internal medicine residents on proper ECG interpretation, basic electrophysiologic pathology, and initial medical treatments for common arrhythmias. This curriculum was designed in conjunction with the Cardiovascular Disease Fellowship Program at The University at Buffalo and was led by cardiology fellows with cardiology attending oversight. Overall, eight cardiology fellows voluntarily participated in delivering ECG didactic sessions. Fellows who elected to participate in didactic sessions were assigned specific ECG-related content to address by the chief cardiology fellow. Didactic sessions were held in monthly intervals. Residents attended a total of seven didactic sessions over the course of seven months. Each didactic session ran for thirty minutes. Residents spent a total of three and a half hours on ECG training of the course of the seven months. Traditional lecture-style format was used to deliver background material on cardiac electrical abnormalities and to educate in the basics of interpreting various arrhythmias. Didactic sessions were held using a hybrid model of in-person and virtual teaching. Residents attended sessions at three training sites in-person, with videoconferencing used to connect residents across the different sites. The fellow leading each session would present virtually to all sites simultaneously. Approximately five to seven unique ECGs were discussed during each didactic lesson. Question-and-answer style format was employed at the end of each session to assess learner comprehension of the aforementioned material. Monthly didactic sessions were divided into the following broad topics: (1) Normal Cardiac Electrophysiology; (2) Basics of ECG Interpretation; (3) Acute Coronary Syndromes; (4) Heart Blocks and Conduction Disease; (5) Bundle Branch Blocks; (6) Wide-complex Arrhythmias; (7) Narrow-Complex Arrhythmias, (8) Miscellaneous ECG Abnormalities ; (9) Basics of Pacemakers and Paced Rhythm Identification.Data was collected using paper questionnaires. All residents who attended ECG didactic sessions were invited to complete two questionnaires administered before and after completion of the ECG curriculum. Participation in both questionnaires was voluntary and data collected anonymously. Data collected included demographics, attendance, exposure to clinical cardiology, interest in cardiology, prior participation in ECG training (if any), and number of didactic sessions attended. Residents were asked to eight common ECG arrhythmias and/or abnormalities on each questionnaire for a total of sixteen ECGs. Two unique ECGs were selected for each rhythm and divided evenly among the two questionnaires. Answers were given in free-text response and were scored for correct or incorrect identification of the rhythm or abnormality. Comfort-level in interpreting ECGs was assessed using a Likert scale. A separate survey was sent to the cardiovascular disease fellows to determine how participation in organizing and leading ECG didactic session affected their training and skills as educators.Descriptive analyses  were used to summarize characteristics of the sample and survey data. Correct ECG interpretations were compared between the pre- and post-curriculum cohorts using chi-square analyses for individual ECG rhythm strips and a t-test for the total number of correct interpretations. Associations between sample characteristics, survey responses and number of correct interpretations were analyzed using Pearson correlations for linear variables and chi-square analyses for categorical variables. Finally, a multivariate linear regression was used to determine the significant predictors of the number of correct ECG interpretations.Characteristics of the residents who completed the surveys are shown in Table p = .05, d = 0.37]. As PGY level increased, there was a statistically significant trend towards increased self-reported comfort in ECG interpretation abilities  vs. 2.84 (0.81), p < .001, d = 0.76]. Regarding the individual ECG rhythms, the post-curriculum cohort had significantly higher percentages of correct identification of abnormalities than the pre-curriculum cohort for ST-elevation myocardial infarction , 2nd -degree AV block Mobitz type I (p = .005) and 2nd -degree AV block Mobitz type II (p = .006), 3rd degree AV block (p < .001), and atrial flutter .Overall, the average number of correct ECG interpretations was significantly higher for the post-curriculum cohort than for the pre-curriculum cohort . Results of a multivariate regression showed that number of clinical cardiology rotations attended was a better predictor of accurate ECG interpretations than didactic sessions attended for the post-curriculum cohort  of the fellows who were surveyed indicated that they enjoyed the experience and agreed or strongly agreed with the statement that participation in the ECG didactic curriculum improved their skills as an educator .Results from our study affirmed that residents who attended the longitudinal, near-peer ECG didactic curriculum demonstrated improved accuracy in ECG interpretation. The impact of the didactic sessions themselves was evidenced by regression analysis, as individuals who attended more sessions were more likely to correctly interpret ECGs than their peers who attended fewer sessions. Residents also reported feeling more comfortable interpreting ECG tracings after attending didactics. Additionally, residents further along in their training reported feeling significantly more comfortable interpreting ECGs compared to their junior peers, although this did not translate into a significant difference in objective interpretations among residents of different training levels.A unique finding of this study was the positive effect that participation in clinical cardiology had on ECG interpretation skills. While prior research has demonstrated that patient exposure improves overall clinical performance among healthcare workers, the present study, to our knowledge, is the first to specifically identify the impact of exposure specifically to clinical cardiology on ability to interpret ECGs . InteresECGs demonstrating 2nd - and 3rd -degree AV blocks proved the most difficult for residents to accurately interpret prior to the implementation of the didactic curriculum. Previous research has corroborated the difficulty residents often have in correctly detecting these arrhythmias on ECG tracings , 20. AnoFinally, results from our survey of the cardiology fellows who organized and facilitated the ECG didactic sessions indicated that their participation in the curriculum improved their own abilities to interpret the various arrhythmias presented and improved their abilities as educators. These results are in line with those reported by prior research, which has likewise found that near-peer teaching provides mutual benefit to both learners and educators and allows educators to consolidate their own knowledge , In futuThere are limitations in the present study. Our relatively small size and its single-center nature reduce generalizability. Given that data was collected via voluntary questionnaires, our study is subject to potential nonresponse bias, although demographic characteristics of residents who participated in both pre- and post-curricular surveys were similar. Although number of didactic sessions attended predicted increased resident aptitude at correctly identifying ECG abnormalities, the observational nature of our study limits our ability to establish a direct causal relationship.Results of this study confirm the effectiveness of near-peer ECG didactic curriculum in improving resident ability to accurately interpret ECGs. While prior research has shown a similar effect in a single didactic session, to our knowledge, this is the first study to evaluate the impact of near-peer teaching on resident ECG interpretation skills in the context of a formal, longitudinal curriculum led by cardiovascular disease fellows , 23. FurThe implementation of a novel, near-peer, ECG didactic curriculum improved internal medicine resident ability to accurately interpret ECGs. The most significant improvement was seen in correct identification of STEMI, 2nd - and 3rd -degree AV block, and atrial flutter. Exposure to clinical cardiology in the form of dedicated clinical rotations was the strongest predictor of successful ECG interpretation. An ECG curriculum which contains both near-peer didactic sessions as well as clinical exposure to cardiovascular diseases may offer the greatest benefit in improving ECG interpretation skills.


Tobacco smoking is highly prevalent among persons with serious mental illness (SMI) and is the largest contributor to premature mortality in this population. Evidence-based smoking cessation therapy with medications and behavioral counseling is effective for persons with SMI, but few receive this treatment. Mental health providers have extensive experience working with clients with SMI and frequent treatment contacts, making them well positioned to deliver smoking cessation treatment. However, few mental health providers feel adequately trained to deliver this treatment, and many providers believe that smokers with SMI are not interested in quitting or have concerns about the safety of smoking cessation pharmacotherapy, despite substantial evidence to the contrary.We present the protocol for the pilot “IMPACT” (Implementing Action for Tobacco Smoking Cessation Treatment) study, which aims to pilot test a multicomponent implementation intervention to increase the delivery of evidence-based tobacco smoking cessation treatment in community mental health clinics.We are using a prepost observational design to examine the effects of an implementation intervention designed to improve mental health providers’ delivery of the following four evidence-based practices related to smoking cessation treatment: (1) assessment of smoking status, (2) assessment of willingness to quit, (3) behavioral counseling, and (4) pharmacotherapy prescribing. To overcome key barriers related to providers’ knowledge and self-efficacy of smoking cessation treatment, the study will leverage implementation strategies including (1) real-time and web-based training for mental health providers about evidence-based smoking cessation treatment and motivational interviewing, including an avatar practice module; (2) a tobacco smoking treatment protocol; (3) expert consultation; (4) coaching; and (5) organizational strategy meetings. We will use surveys and in-depth interviews to assess the implementation intervention’s effects on providers’ knowledge and self-efficacy, the mechanisms of change targeted by the intervention, as well as providers’ perceptions of the acceptability, appropriateness, and feasibility of both the evidence-based practices and implementation strategies. We will use data on care delivery to assess providers’ implementation of evidence-based smoking cessation practices.The IMPACT study is being conducted at 5 clinic sites. More than 50 providers have been enrolled, exceeding our recruitment target. The study is ongoing.In order for persons with SMI to realize the benefits of smoking cessation treatment, it is important for clinicians to implement evidence-based practices successfully. This pilot study will result in a set of training modules, implementation tools, and resources for clinicians working in community mental health clinics to address tobacco smoking with their clients.Trial Registration: ClinicalTrials.gov NCT04796961; https://clinicaltrials.gov/ct2/show/NCT04796961ClinicalTrials.gov NCT04796961; https://clinicaltrials.gov/ct2/show/NCT04796961DERR1-10.2196/44787 Tobacco smoking is the largest contributor to premature mortality among persons with serious mental illness (SMI) -4. An esThe provision of effective, evidence-based smoking cessation treatment could substantially reduce the premature mortality experienced by people with SMI; however, few in this group receive evidence-based treatment -20. In aAs many people with SMI receive the majority of their health care from the specialty mental health sector -24 and tThis protocol describes a pilot study of an implementation intervention of evidence-based smoking cessation treatment in community mental health clinics. We developed and are testing an implementation intervention designed to improve mental health providers’ knowledge, self-efficacy, and delivery of evidence-based smoking cessation treatment. The shorthand name for the study is “IMPACT” (Implementing Action for Tobacco Smoking Cessation Treatment).Our study is grounded in Gurses et al’s  model ofThis is a prepost study examining the effects of a 12-month implementation intervention on providers’ knowledge and self-efficacy and the mechanisms through which the implementation intervention is designed to improve the delivery of evidence-based smoking cessation treatment. We will also evaluate the effects of the implementation intervention on the delivery of evidence-based practices for smoking cessation. In addition, we will analyze measures of providers’ perceptions of the acceptability, feasibility, and appropriateness of the implementation strategies and the IMPACT evidence-based practices.The study is conducted in 5 community mental health clinics, all of which serve persons with SMI. Provider participants are employees of the community mental health organizations, including leaders and mental health clinicians . Data will also be analyzed from the clients served by the clinics around their receipt of the evidence-based practices. The research was approved by the Johns Hopkins University School of Medicine Institutional Review Board (IRB) (#IRB00231836).The intervention includes the following four evidence-based practices for smoking cessation that are based on consensus guidelines, recommendations for persons with SMI, and recent clinical trials ,13,31-33Assessment of smoking status involves asking adult clinic clients if they currently smoke tobacco and, if they respond yes, further assessing the severity of tobacco dependence .Assessment of willingness to quit uses stage-of-change questions . In thisThe focus of the behavioral counseling will vary depending on clients’ willingness to quit. For clients who are not interested in quitting within 12 weeks, behavioral counseling entails an immediate, brief session (<10 minutes) using motivational interviewing techniques to explore the pros and cons of smoking, elicit client concerns about their smoking, and identify potential benefits of quitting . The proThe fourth evidence-based practice is pharmacotherapy prescribing, in which a prescribing physician or nurse practitioner meets with clients undergoing smoking cessation behavioral counseling to encourage use of 1 of the following 3 Food and Drug Administration (FDA)–approved treatments: varenicline with or without nicotine replacement therapy (NRT), bupropion SR with or without NRT, or NRT alone . When NRTo improve mental health providers’ knowledge, self-efficacy, and delivery of evidence-based practices, the study will employ the following five implementation strategies: (1) training on evidence-based smoking cessation treatment, including an innovative web-based avatar module for motivational interviewing practice; (2) a tobacco smoking treatment protocol; (3) expert consultation for prescribers and therapists; (4) coaching; and (5) organizational strategy meetings (OSMs). A more detailed description of each component is outlined below.Trainings are conducted by study staff. All provider participants in the IMPACT project complete 1 hour of prerecorded web-based training modules. Then, therapists and prescribers use a video conferencing platform to participate in real-time training on delivering smoking cessation behavioral counseling, prescribing smoking cessation pharmacotherapy, and using motivational interviewing counseling skills when having conversations with clients about their smoking. Trainings are housed in a web-based management system that enables tracking of provider participation as well as continuing education credit. The training outline is shown in The real-time motivational interviewing training is supplemented with a web-based avatar practice module developed in partnership with Kognito ,42. The Prescribers (psychiatrists and nurse practitioners):Online training modules (1 hour)Module 1: Why IMPACT (Implementing Action for Tobacco Smoking Cessation Treatment)?Module 2: Evidence-based treatment for smoking cessation for persons with serious mental illness (SMI)Module 3: Assessing smoking status willingness to quitModule 4: Pharmacotherapy for smoking cessationReal-time trainings (in person or videoconferencing platform) (2 hours)Training 1 (1 hour): Facilitating smoking cessation conversationsTraining 2 (1 hour): Motivational interviewing approach to smoking cessation pharmacotherapyOnline motivational interviewing avatar (recommended monthly 15-minute practice sessions)Therapists :Online training modules (1 hour)Module 1: Why IMPACT?Module 2: Evidence-based treatment for smoking cessation for persons with SMIModule 3: Assessing smoking status willingness to quitModule 4: Pharmacotherapy for smoking cessationReal-time trainings (in person or zoom) (4 hours)Training 1 (2 hours): Facilitating smoking cessation conversations and an overview of behavioral counselingTraining 2 (2 hours): Motivational interviewing approach to smoking cessation behavioral counselingOnline motivational interviewing avatar (recommended monthly 15-minute practice sessions)The research team developed a tobacco smoking treatment protocol to assist clinicians in delivering evidence-based smoking cessation treatment. This protocol includes a resource guide that provides an overview of the IMPACT program and will help clinicians navigate their work on the project. Clients who report being current smokers  are assessed for their willingness to quit. Based on client responses to the tobacco smoking status and willingness-to-quit assessment, instructions help clinicians facilitate brief smoking cessation conversations; all clients interested in quitting will be offered treatment. Clinicians are provided manuals for delivering smoking cessation behavioral counseling sessions and prescribing pharmacotherapy.The smoking cessation behavioral counseling manual includes the outline for 13 session topics that can be delivered flexibly based on the client’s current smoking status and the provider’s judgment about what would be most helpful see . A smokiExpert consultation is available for prescribers and therapists to discuss issues and ask questions related to smoking cessation pharmacotherapy and behavioral counseling. Study team members who are experts in smoking cessation pharmacotherapy and behavioral counseling are available during the 12-month intervention to conduct as-needed phone or email consultation with clinicians.Coaching is available for therapists and prescribers to discuss specific client cases, develop smoking cessation behavioral counseling skills, and answer questions about prescribing smoking cessation pharmacotherapy. The coaching sessions, which will be offered monthly through a videoconferencing platform, will focus on skill development, overcoming barriers to providing evidence-based smoking cessation treatment, and additional training as requested. To increase participation, we aim to incorporate coaching sessions into regularly scheduled clinic meetings but will schedule individual coaching sessions as needed. The expectation is that providers attend at least one session per quarter.OSMs are designed to improve engagement in practice change. These meetings will occur monthly and consist of a 2-to-3–member clinic leadership team, including providers and staff leaders. OSMs will be a chance for the study team to work with the clinic to identify successful organizational-level processes, share implementation data, provide feedback, and problem-solve to overcome identified barriers to program delivery.Data will be obtained from several sources, including provider surveys, provider interviews, web-based data collection regarding provider participation in training, and client data from the electronic medical record. Providers will be surveyed either by email with instructions and a link to the study assessments in the REDCap software or by paper-and-pencil, depending on-site preference; these assessments will be administered at baseline and at 12 months. Data on providers’ competency using motivational interviewing skills will be obtained from scheduled avatar-simulated conversations and from standardized actor phone interviews, which will occur at baseline and 12 months at a minimum. Standardized client scenarios will be provided to actors that reflect the kind of situations community mental health clinicians would likely encounter with clients who smoke; this method has demonstrated predictive validity in terms of providers’ performance with actual clients . The resprimary outcomes are changes in providers’ knowledge about and self-efficacy to deliver evidence-based smoking cessation treatment from baseline to 12 months.The Secondary outcomes include change in the delivery of the recommended four evidence-based practices: (1) assessment of smoking status for all adult clinic clients (with quarterly follow-up assessments for smokers not yet willing to quit), (2) assessment of willingness to quit for smokers, (3) receipt of behavioral counseling for those willing to quit within 12 weeks, and (4) receipt of pharmacotherapy for those willing to quit within 12 weeks and referral for pharmacotherapy for those not willing to quit in this time frame. These outcomes will be measured by clinic documentation during client visits (in the EMR or site-specific documentation) and assessed at baseline and throughout the implementation period. When available, baseline documentation will include data from 3-6 months prior to project implementation. Additional secondary measures are changes in the acceptability, appropriateness, and feasibility of the intervention implementation strategies and of the evidence-based practices as assessed through the survey instrument.To assess motivational interviewing skills, we will use the Motivational Interviewing Treatment Integrity coding system . We willPerceived barriers and facilitators on the part of clinic providers and leaders will be assessed based on qualitative interviews with individual providers before the start of the implementation intervention and at 12 months, and also with information obtained in monthly OSMs. We will also collect data about providers’ and clients as shown in We will conduct 2 main analyses. First, we will use survey data to assess the effects of the implementation intervention (baseline and 12 months) on providers’ knowledge and self-efficacy, the mechanisms through which the implementation intervention is designed to improve the delivery of evidence-based smoking cessation treatment, using a generalized linear mixed effects modeling approach. The model will include a binary variable representing the prepost time points, fixed effects for the 5 study sites, and provider demographic characteristics. Second, we will evaluate the effects of the intervention (baseline and 12 months) on the implementation of evidence-based practices using a multilevel modeling approach. We will also assess the potential moderating effects of the implementation climate by adding appropriate interaction terms to the main models. We will use descriptive statistics to characterize staff perceptions of the acceptability, feasibility, and appropriateness of the implementation intervention strategies and the IMPACT evidence-based practices. Interview transcripts will be analyzed in MAXQDA (VERBI GmbH), using inductive coding to identify key themes. Survey analysis will be done using Stata 14 (StataCorp LLC) or SAS software (SAS Institute).The study was approved by the Johns Hopkins University School of Medicine IRB on January 14, 2021 (IRB number 00231836). Community mental health leaders and clinical staff will be appropriately recruited and informed of the study by the study team, with a waiver of documentation of informed consent. Patient data will be obtained per an approved waiver of consent. These waivers were approved by the IRB.Each participant will be assigned a unique study ID number for data collection. Interview data will be audio recorded and transcribed by an approved vendor. Names will be removed from transcripts. Standardized actor interview will be stored on a secure network and participants identified by study number only. Study data will not be presented in such a way that identity can be inferred. Mental health leader and staff study participants will be paid US $50 for completing each interview and US $25 for each standardized actor interview as applicable. They will be paid up to a maximum total of US $60 for completing surveys at 4 time points.The study is underway at 5 clinic sites. More than 50 providers have been enrolled, exceeding our recruitment target. The study is ongoing. We anticipate that results will be reported in 2023 or 2024.Tobacco smoking is the leading cause of preventable mortality among persons with SMI and contributes to the reduced lifespan up to 25 years for persons in this population . EvidencIn order to realize the intended benefits of smoking cessation treatment for persons with SMI, it is important that mental health programs implement evidence-based practices. Current barriers faced by clinicians include not having the knowledge or confidence to deliver smoking cessation treatments, as well as misconceptions about the safety of smoking cessation medications and client interest in quitting -28. TherWhile evidence-based smoking cessation treatments are not provided routinely in mental health clinics, where people with SMI receive the majority of their health care, these settings provide opportunities for the delivery of these recommended practices. We have specifically designed the training materials for providers in the community mental health center setting and have tailored the counseling manual for delivery to persons with SMI. We also worked with the sites’ leadership to embed smoking cessation processes of care into the EMR and current workflow to increase clinician uptake. Using data from the EMR can provide an objective measure of smoking cessation evidence-based practices that are being implemented, enabling us to highlight areas of success and problem-solve barriers. At the completion of this study, we will have training modules, implementation tools, and resources for the delivery of smoking cessation treatment in community mental health centers. In order to address barriers to the implementation of these evidence-based practices, we are using a range of strategies, including asynchronous trainings and novel avatar simulations, to improve motivational interviewing counseling skills. We will collect data about the acceptability, appropriateness, and feasibility of both the evidence-based practices and implementation strategies that will inform future implementation efforts and planning for a randomized controlled trial.In terms of limitations, our implementation intervention is effortful and multifaceted and may require additional supports to be carried out at other community mental health centers. The COVID-19 pandemic has created further challenges. As a result of pandemic-related restrictions, the study team had to adapt the implementation strategies to be delivered remotely rather than in-person, which, while being efficient to deliver, can make it more challenging to engage clinicians. Clinicians also had to adapt the counseling sessions to be delivered remotely if needed, which can be an added barrier for those less comfortable with technology. We also recognize that it may be difficult for providers to prioritize smoking cessation given other time-sensitive client concerns, such as those related to acute psychiatric symptoms and mental health crises . CliniciThe IMPACT study will provide evidence about the use of implementation strategies to increase providers’ knowledge, self-efficacy, and delivery of the evidence-based practices for smoking cessation treatment for persons with SMI in community mental health center settings.


The genetic basis of phenotypic emergence provides valuable information for assessing individual risk. While association studies have been pivotal in identifying genetic risk factors within a population, complementing it with insights derived from predictions studies that assess individual-level risk offers a more comprehensive approach to understanding phenotypic expression. In this study, we established personalized risk assessment models using single-nucleotide polymorphism (SNP) data from 200 Korean patients, of which 100 experienced hepatitis B surface antigen (HBsAg) seroclearance and 100 patients demonstrated high levels of HBsAg. The risk assessment models determined the predictive power of the following: (1) genome-wide association study (GWAS)-identified candidate biomarkers considered significant in a reference study and (2) machine learning (ML)-identified candidate biomarkers with the highest feature importance scores obtained by using random forest (RF). While utilizing all features yielded 64% model accuracy, using relevant biomarkers achieved higher model accuracies: 82% for 52 GWAS-identified candidate biomarkers, 71% for three GWAS-identified biomarkers, and 80% for 150 ML-identified candidate biomarkers. Findings highlight that the joint contributions of relevant biomarkers significantly influence phenotypic emergence. On the other hand, combining ML-identified candidate biomarkers into the pool of GWAS-identified candidate biomarkers resulted in the improved predictive accuracy of 90%, demonstrating the capability of ML as an auxiliary analysis to GWAS. Furthermore, some of the ML-identified candidate biomarkers were found to be linked with hepatocellular carcinoma (HCC), reinforcing previous claims that HCC can still occur despite the absence of HBsAg. While genomic instability reveals only a portion of the biological underpinnings of complex diseases9, identifying genetic biomarkers can facilitate targeted and personalized treatments for individuals with increased genetic susceptibility to specific diseases.Since the genetic architecture of complex diseases follows a polygenic rather than a Mendelian model10, associated with complex traits. The study design of GWAS involves testing individual SNPs for their association with the phenotype15. To come up with a statistically relevant association amidst multiple SNP testing, highly conservative thresholding is necessary, often leading to underpowered SNP detection with small effect sizes19. Most identified associations point to larger regions of correlated variants due to linkage disequilibrium22, highlighting the potential influence of neighboring variants with modest effects on predicting phenotypic expression. Similarly, while biomarkers having robust associations are often perceived as prime candidates for modeling, they might be poor predictors of phenotypic outcomes23. Assessing the predictive utility of GWAS-identified candidate biomarkers, therefore, still warrants further investigation.Genome-wide association studies (GWAS) serve as the gold standard approach in identifying disease susceptibility variants, such as single nucleotide polymorphisms (SNPs)27. In addition, the “curse of dimensionality,” resulting from the millions of features present in genomic data28, prevents attaining an optimized model performance due to the presence of irrelevant features. In the context of personalized medicine, understanding the differences in goals of association and prediction studies23 and accounting for the complex interactions among SNPs is a crucial consideration. Machine learning (ML) is a widely accepted methodical framework in analyzing high-dimensional and complex data32, owing to its unparalleled ability to handle high-volume data and uncover implicit and nonlinear patterns that are pertinent for predictive modeling. By selecting a minimum subset of individually relevant and neighboring features while minimizing information loss33, ML captures complex interactions, leading to the identification of highly-predictive features.Traditionally, predictive models such as polygenic risk score models were used to quantify the predictive value of SNPs; however, such models are limited to learning only the linear interactions among variables23, this paper aims to identify biomarkers linked to the phenotype by incorporating insights from both analyses. More precisely, this study intends to develop a robust risk assessment model that identifies the best combination of GWAS-identified and ML-identified candidate biomarkers. We organized the study as follows: Section II outlines the data description and preprocessing, as well as the model framework, including feature selection, model classification, and model evaluation through hyperparameter tuning and cross-validation; Section III presents the results of implementing the model framework to various biomarker types such as GWAS-identified candidate biomarkers and ML-identified candidate biomarkers; Section IV discusses the results and key findings; and Section V summarizes main points and their implications in the biomedical field, demonstrates limitations of the study, and provides recommendations for future research.Understanding the differences in the information gained from population and individual levels14, a study on hepatitis B virus (HBV) surface antigen (HBsAg) seroclearance in patients with chronic hepatitis B (CHB) of homogeneous viral genotype. The data is composed of 200 subjects genotyped for 2,372,784 SNPs. The SNP dataset was subjected to quality control procedures as discussed by Kim et al.14: (1) SNPs that were not located on autosomal chromosomes, (2) SNPs with missing call rates of less than 0.95 in both cases and controls, (3) SNPs with a minor allele frequency of less than 0.01, or (4) SNPs with significant deviation from the Hardy-Weinberg equilibrium of The secondary SNP dataset used in this study was obtained from Kim et al.34. For further details regarding the data, refer to this paper14. Furthermore, the SNPs were encoded in the additive encoding scheme35, which counts the number of minor alleles in the phenotype for a suitable representation for ML analysis.The phenotypes include 100 patients who underwent HBsAg seroclearance before the age of 60 and 100 patients who demonstrated a high level (> 1000 IU/mL) of HBsAg after the age of 60 as case and control, respectively. HBsAg seroclearance is the absence of circulating HBsAg with or without the presence of antibodies in patients with CHB, hence considering it a functional cure for the infection14 and ML-identified candidate biomarkers through feature selection via random forest (RF). In investigating the most effective approach, the support vector machine (SVM) will be trained using various biomarkers sets, i.e., GWAS-identified candidate biomarkers only, ML-identified candidate biomarkers only, and a combination of both, and assess their classification performances. To maintain consistency in the model configurations, we used identical sets of hyperparameters to optimize SVM. We also implemented a cross-validation scheme during model evaluation to ensure generalizable model performances. Figure We developed a model framework that determines the best combination of GWAS-identified candidate biomarkers reported in the recent paper36, RF was used as a feature selection technique to determine the optimal combination of SNPs. RF uses bootstrapping to train decision trees on randomly sampled subsets of training data, then consolidates the predictions of the individual trees to generate a final prediction. Furthermore, RF enhances the diversity of its ensemble by incorporating randomization at the node level when growing each individual tree by selecting a random feature subset to determine the best split for each node. The feature importance of t. The feature importance of an t, and Feature selection is an essential step in ML that reduces the dimensionality of data by selecting the most relevant and informative features to build highly predictive models. Owing to its remarkable ability to build a predictive model without any prior assumptions about the genotype-phenotype relationshipmentclass2pt{minim37. RF’s inherent ability to capture SNP-SNP interactions and subsequently leading to satisfactory phenotype prediction performance40, make it suitable for genomic data analysis and bioinformatics research.RF is widely used in “large p, small n” problems due to its one-step-at-a-time node strategy, while still being able to consider correlations and interactions among predictors due to the “grouping property” of decision treesHyperparameter tuning is necessary for achieving optimal performance in model training. Bayesian Optimization (BayesOpt), a global optimization method for black-box functions such as ML models, was utilized to tune the hyperparameters of RF and SVM. Unlike grid and manual search algorithms wherein experiments are conducted in isolation, BayesOpt balances exploration to uncertain search spaces and exploitation of results from previous experiments to arrive at global rather than local optimum. BayesOpt is a principled approach for approximating a probabilistic model of the objective function via a surrogate function to select future parameter values based on prior knowledge. In this study, BayesOpt is built on (1) a Tree-structured Parzen Estimator (TPE), a Bayesian surrogate model to fit results from objective function, and (2) an acquisition function to decide the next iteration of hyperparameter values.For 50 independent trials, BayesOpt performed a parameter search on the respective baseline models, i.e., RF and SVM, using stratified 10-fold cross-validation on the training set while ensuring a minimized loss of the objective function.After retrieving the set of hyperparameters that achieved a minimized loss, evaluate the performance of the optimized model by using the testing set.Store the selected hyperparameters and their corresponding performances in a CSV file.Repeat steps (1) to (3) for ten independent trials.From the CSV file containing ten sets of hyperparameter values and their corresponding performance metrics, select the best set that achieved the highest performance accuracy. The optimal set of hyperparameters is demonstrated in Supplementary Table In performing hyperparameter tuning, the dataset was initially split into 80% and 20% training and testing sets. The BayesOpt algorithm was given a search space of allowable values for all hyperparameters  to ensure a stringent model evaluation. LOOCV is well-known for its stringent validation approach, where it iteratively leaves out one data point at a time as the validation set while using the remaining points for training. The division process is repeated until each observation has been used once as the testing data. In addition, model accuracy, sensitivity, precision, and area under the curve (AUC)-receiver operating characteristic (ROC), were determined for each model configuration for a more comprehensive model evaluation.Within the LOOCV framework, feature selection was implemented to ensure generalizable feature importance scores. The feature selection process through RF involved a collective analysis of all 1,318,897 SNPs associated with the phenotype, rather than studying each SNP independently in isolation, to capture pertinent SNP-SNP interactions. Such a process involves iteratively retrieving SNP subsets ranging from 10 to 1000 SNPs , where each subset is subjected to RF training using LOOCV. The specified range of SNP subsets allows a balance between model complexity and generalization performance. Given N folds in LOOCV (where N = 200), the computation of the final feature importance per SNP subset is calculated as the average of all importance scores across N folds. Obtaining each feature subset involves selecting SNPs based on their computed highest feature importance scores. Specifically, a feature subset containing 10 SNPs was chosen based on the top 10 highest feature importance scores, and so on for higher-ranked subsets.14 received approval from the ethics committee at the Korea University Anam Hospital and was conducted in accordance with the ethical guidelines in the Declaration of Helsinki.All participants provided written consents to take part in the study, permitting the use of their medical data and the collection of serum samples for research purposes. The project of Kim et al.This study focuses on three main tasks: (1) assessing the predictive power of GWAS-identified candidate biomarkers, (2) assessing the predictive power of ML-identified candidate biomarkers, and (3) augmenting ML-identified candidate biomarkers to the core GWAS-based biomarkers model. It is worth noting that while the sample size used in this study may not be large enough, the balanced data distribution still enables a reliable evaluation of the models’ generalization abilities, as each class is fairly represented during each validation step in LOOCV. The use of LOOCV is deemed appropriate for small sample sizes as it maximizes the use of available data for training and validation, mitigating overfitting risk and minimizing the impact of chance associations within the data.14 and (ii) the potential GWAS-based biomarkers model that includes 52 GWAS-identified candidate biomarkers with a cut-off p-value of 14. Conversely, a baseline model, which uses all SNPs from the data, was also developed to establish a benchmark. All risk assessment models were trained using the optimal set of hyperparameters of SVM from Supplementary Table To evaluate the predictive capacity of GWAS-identified candidate biomarkers, we constructed two risk assessment SVM models based on GWAS results: (i) the core GWAS-based biomarkers model that comprises the three most statistically associated GWAS-identified candidate biomarkers as indicated in Supplementary Table S4Results from Table The ML-based biomarkers model, which uses ML-identified candidate biomarkers retrieved using the exhaustive feature selection via RF, was compared against the baseline SVM model (see Table The results showed that training the model using SNPs with high predictive power considerably improved model performance. As depicted in Fig. p-value 45. Finally, PCED1B was reported to be upregulated with HCC with predicted poor survival46. Notably, the ML-based approach could investigate the biological link between HCC and HBsAg seroclearance. The result of the biomarker identification reinforces previous studies53 that clinical complications such as HCC are still possible even in the absence of HBsAg. As a result, this necessitates clinical monitoring and regular surveillance54.From the feature selection process using RF, the calculated feature importance scores for the GWAS-identified candidate biomarkers from Supplementary Table Finally, combining information from population and individual levels, we augmented the core GWAS-based biomarkers model by iteratively adding ML-identified candidate biomarkers retrieved through RF, referred to as the GWAS+ML-based biomarkers model. The mentioned model was developed to quantify the effect of the non-GWAS SNPs on the model’s predictive performance. As seen in Fig. 23. To harness the complementary insights from population- and individual-levels, we assessed the predictive power of GWAS-identified candidate biomarkers, evaluated the predictive power of ML-identified candidate biomarkers, and developed a model based on the combination of SNPs identified using the two types.Unlike association studies, which are explanatory and focus on identifying patterns and relationships between variables based on the population-level, the prediction route in prediction studies such as ML is focused on developing models using the best combination of features with a final aim of personalized risk assessmentt55. While utilizing various biomarkers causes a significant impact on the phenotype, the relevance of features must still be accounted for. For instance, signals originating from the three biomarkers from Supplementary Table 56, stating that utilizing multiple correlated SNPs rather than solely using the most statistically significant risk variants improves risk assessment model performance. More so, using the entire feature space without considering the relevance of the individual features hinders achieving an optimal model performance. Given that genomic datasets suffer from the curse of dimensionality32, it is crucial to eliminate irrelevant features and retain only the most informative variants related to the phenotype under investigation. Removing noise from the data improves models’ accuracy and reliability, thereby gaining a deeper understanding of the genetic mechanisms underlying risk susceptibility.Complex disorders are influenced by the joint contributions of multiple dysfunctional genetic variants, each of which contributes to the phenotypic expression with an individual effect of varying magnitude23. Although association statistics provide valuable insights regarding the relationship between two variables, it does not guarantee a predictive relationship. For instance, the collective effects of the three GWAS-identified candidate biomarkers with robust associations from Supplementary Table While identifying relevant genetic risk factors is a crucial step in assessing risk, a statistically significant association alone is inadequate to signify a claim of prediction57, thus aiding GWAS in identifying novel biomarkers. From these, incorporating the ML-identified candidate biomarkers into the three GWAS-identified candidate biomarkers from Supplementary Table 57. Ultimately, the high performance attained by the GWAS+ML-based biomarkers model highlights the synergy of GWAS and ML in translating scientific discoveries into clinical and practical use.Understanding that association and prediction studies are not mutually exclusive, we used these approaches in conjunction with one another by combining information from the population and the individual levels. The superior model performance from the GWAS+ML-based biomarkers model illustrates that ML-based approaches could be employed as another approach in detecting collective effects of variants on complex traitsAcknowledging that association and prediction studies may offer complementary insights into disease mechanisms, we leveraged information at the individual and population levels to improve model performance. Iteratively adding ML-identified candidate biomarkers into the pool of the three most statistically significant GWAS-identified candidate biomarkers resulted in a considerable improvement in the model performance, attaining a maximum accuracy, sensitivity, precision, and AUC of 90%, 90%, 89%, and 0.90, respectively.Extensive validation of all findings in the study is imperative in developing a robust and reliable personalized disease risk assessment through ML. To ensure the reliability of the proposed method, we recommend conducting validation studies that assess the utility of combining information from population and individual levels across various disease types and populations. Findings from this study are specific to the Korean cohort, and therefore, their generalizability necessitates further investigation. Verifying the biological mechanisms underlying GWAS-identified candidate biomarkers and ML-identified candidate biomarkers is also recommended to ensure that the identified biomarkers accurately indicate the phenotype. Without a clear understanding of the fundamental biology, biomarkers indicative of a phenotype may be inaccurate and unreliable, and their subsequent use in prognosis and diagnosis could be misguided.Supplementary Tables.


The complex structure of the liver and its elaborate hemodynamics can cause hepatic pseudolesions on contrast-enhanced imaging, making the interpretation of diagnostic liver imaging challenging. Aberrant gastric veins are rare; most of their epidemiology data comes from small single-center studies. While current literature suggests that pseudolesions originating from aberrant gastric veins mainly present as hyperdense defects, some cases can also show up as hypodense, as shown in these cases. Differences in flow rates between the portal and aberrant veins and the timing of the scans could explain this contradiction. Identifying aberrant gastric veins on cross-sectional imaging is crucial because they could be misdiagnosed as liver lesions, granting further unnecessary workups or invasive procedures. Aberrant gastric veins can also act as pathways for the spread of gastric cancer. This manuscript presents one aberrant right gastric vein and two aberrant left gastric veins causing hepatic pseudolesions. The complex structure of the liver, its intricate blood supply with dual inflow, 25% from the hepatic arteries, and 75% from the portal vein, respectively, and the various pathological conditions that can impact liver function can make interpreting diagnostic liver imaging challenging . MoreoveDuring the early stages of embryonic development, anastomotic omental veins connect the venous plexus of the primitive foregut to the ductus venosus of Arantius . Normal Usually, gastric veins, which drain blood from the lesser curvature of the stomach, merge with the portal vein, making part of the physiological hepatopetal flow (blood flow toward the liver). Aberrant hepatopetal venous flow, also known as third inflow, may contribute to HPS; third inflow can be caused by an aberrant right gastric vein (ARGV) and, more rarely, by an aberrant left gastric vein (ALGV) .We present three cases of patients with HPS secondary to aberrant gastric veins. Since not all the imaging features of aberrant gastric veins in cross-sectional imaging studies have been widely reported, we present these cases and encourage other authors to report similar cases.First caseAn asymptomatic, 62-year-old woman with a history of a partial gastrectomy with gastrojejunal anastomosis and cholecystectomy underwent an abdominal contrast-enhanced computed tomography (CT) to assess a renal angiomyolipoma identified incidentally on a routine abdominal ultrasound. The CT showed an aberrant drainage pattern of the right gastric vein into the liver, causing a hypodense HPS localized at the hepatic segment IVb Figures . Since the patient remained asymptomatic, no further intervention was necessary.Second caseA 46-year-old woman with a medical history of irritable bowel syndrome (IBS) arrived at the emergency department with dull abdominal pain lasting for two months. During the workup, the patient underwent a contrast-enhanced abdominal CT, which incidentally revealed an ALGV, causing a HPS localized at the hepatic segments II and III Figures .Since the ALGV was an incidental finding, the patient was conservatively treated.Third caseA 50-year-old man with a history of abdominal pain lasting one week underwent a contrast-enhanced abdominal CT, which incidentally revealed an ALGV, causing a small HPS localized at hepatic segment III Figure .The patient's abdominal pain was attributed to IBS after ruling out alternative diagnoses; therefore, he was medically managed and discharged after resolution.Aberrant gastric veins are considered an exceedingly rare finding. Most information regarding their epidemiology comes from small single-center studies. The incidence of ALGV ranges from 0.8%-4%, whereas ARGV is 1.5%-49%, as reported by Kobayashi . In our According to Muñoz and Fraum, the ALGV typically drains into the posterior margins of hepatic segments II and III . At the Elsayes et al. described that the HPS associated with either aberrant gastric vein results in an area of relative hyperenhancement at contrast-enhanced CT and MRI ; nonetheWe consider that the hypodense or hyperdense appearance of the HPS in imaging studies depends on the timing of the scan rather than on the intrinsic characteristics of the lesion. Considering these factors carefully when interpreting imaging studies is critical to avoid misdiagnosing and ensure appropriate clinical management.Some authors have described additional clinical significance for aberrant gastric veins; for example, these could act as an alternative route for venous drainage in hypertensive gastropathy in cirrhotic patients or as a direct metastatic pathway for gastric cancer to the left side of the liver ,5. MoreoAberrant gastric veins are a rare but relevant finding in cross-sectional imaging, potentially leading to additional imaging studies or biopsies. The density of the HPS caused by aberrant gastric drainage can be variable, ranging from hyperdense to hypodense, depending on the timing of the scan rather than the lesion's intrinsic characteristics.Encouraging authors to publish more cases like ours is crucial to increasing the available evidence on aberrant gastric vein imaging features in cross-sectional imaging studies.