Innovating in Medical Device (MD) industry is challenging. This study aims to develop and validate an evidence-based framework that helps innovators of small and large enterprises (SEs and LEs) assess their readiness for successful MD development and deployment. We conducted a key-informant process (stage 1) where 25 international experts identified a list of emergent Health Technology Assessment (HTA) themes they believed were essential to company success. A sample of 22 European and US selected companies (13 SEs and 9 LEs) then reached a consensus on a list of key themes through a robust Delphi process (stage 2). Finally, we constructed (stage 3) and validated (stage 4) the checklist for SEs and LEs. The checklist for SEs and LEs included 21 and 15 items  with nine overlapping criteria for both SEs and LEs. In both groups, MD success was driven by three major item categories: (i) R&D assessment strategy; (ii) device-outcome measures; (iii) company profiling. Alongside the retrospective validation study, we collected 40 case studies on MDs (23 successes and 17 failures) across the selected enterprises. The retrospective validation provided the proportion of successful and failed case studies that met the ’MeDKET’ criteria. We discovered that early HTA plays a pivotal role in MD industry success with different implications based on enterprise size. This study is the first of its kind to provide a holistic picture of the perceived role of early-stage HTA in MD industry success. The Research and Development (R&D) process in Medical Device (MD) industry is complex, expensive, and has plenty of pitfalls. This process is more multifaceted than the innovation continuum in other industries or sectors . The uniFewer than 6% of MDs reach the market each year after many years of development efforts and high costs sustained by companies, governments, and R&D investors, which could fund cost-ineffective technologies that never achieve implementation . The devThe specificities of the MD industry generate a particular case in the market access of new MDs due to the highly regulated aspect of the industry and the interdependencies of each new product with existing frameworks, products, and systems in clinical use , 8. IndeTechnology producers should understand that the MD industry’s traditional definition of product success is evolving. New criteria and requirements for achieving success push relevant stakeholders involved in the R&D process  to assess innovative products as earlier as possible. The previous factors, combined with increasing healthcare budget constraints and reimbursement schemes, threaten the MD industry’s future, which is globally in accelerated and compulsory growth , 13.Early-stage HTA is an emerging ’species’ of HTA in which technologies in development are evaluated to support healthcare decision-making from the initial idea up to phase III-like trials, anticipating market access and reimbursement , 15. TheThis exploratory study aims to develop and field-test an evidence-based framework to understand whether and to what extent early-stage HTA might influence the product success of small and large enterprises (SEs and LEs) from a company perspective. Incorporating early-stage HTA into R&D and company decision-making might be beneficial. However, evidence remains sparse on whether (and how) the MD industry conducts early-stage HTA. The implications of conducting early-stage HTA on future (post-market) product success must be made clear and straightforward. Our implicit aim is, therefore, to identify the drivers of MD industry success.We applied a multi-method approach, which was successfully used in producing the ’POCKET’ toolkit  for deveAs outlined in A three-step key-informant process was addressed to international experts and methodologists to identify a list of emergent themes that explained the MD company’s success.Karolinska Institutet involved senior academics in healthcare innovation management and informed the development of essential themes covered in the next step.Initial discussions at We conducted 25 semi-structured interviews by phone or in person with key informants . The expert academics  were identified by academic publishing output; some also worked as freelance consultants for the MD industry. The industry experts  were well-known professionals working in spin-off companies based on our academic institutions. We performed a general thematic analysis of the interviews to extract emergent themes.Health Economics Research Centre  and re-piloted the revised version a month later. The aim was to make the easily understandable questions in case of no scientific background in biomedical technology innovation/early-stage HTA.We translated the list of emergent themes, identified by the key informants, into a series of statements to form a survey questionnaire . We piloted the questionnaire with the academic staff of the A robust Delphi process with skilled professionals working in the MD industry aimed to reach a consensus on theme relevance.We selected the Delphi participants at both company and professional levels. Inclusion criteria for SEs and LEs were as follows: (i) intense R&D process; (ii) high specialisation; (iii) international partners. We made every effort to include relevant experience or expertise existing outside Italy. We set a minimum of eight participants for each group  as a pragmatic sample size, given time and resources .Inclusion criteria for practitioners were as follows: (i) (at least) four years of experience within the company; (ii) a comprehensive view of R&D and market access ; (iii) accurate representation of the company needs and aims. We reached the leaders or CEOs of each firm by invitation included in their trade association newsletter  or through direct contacts. After the approval of the CEO of each firm, we interviewed the CEO or the persons indicated by the CEO. We excluded six SEs after preliminary informal talks with the management team because the companies were not interested in this research and three LEs after their CEOs and other senior professionals were unavailable.Results drove the final number of Delphi participants, as more interviews were carried out until no new themes emerged. Tables The semi-structured interview study aimed to identify: (i) the degree of relevance of each HTA dimension in each R&D phase; (ii) starting time, approaches and perspectives used in early economic evaluation; (iii) barriers to market access and adoption of MDs; (iv) the costs and benefits of conducting early-stage HTA during R&D; (v) the perceived role of early-stage HTA in MD industry success.We conducted 13 semi-structured interviews in the SE and 13 in the LE groups. Indeed, out of 9, 3 selected companies indicated more than one proper person. Out of 26, 15 interviews  were conducted face-to-face by one interviewer (SM), whereas the remaining were via phone or "Skype". The interview structure resulted from the key-informant process (stage 1). It was further refined in conjunction with an expert in mixed research (MN) to allow the collection of both quantitative and qualitative data while consenting to flexibility and original suggestions. Interviews lasted for approximately 60 min, were digitally recorded, and then transcribed for analysis. The 12 interviews conducted in Italy were in Italian and translated into English. Two authors (SM and MN) co-analysed the data independently to minimise biases. Initially, interview data were coded based on predetermined themes; additional themes emerged and were coded during the interview analyses. In four cases, participants were contacted to clarify the interpretation of data. Data were analysed with NVivo V.10.1.1 software .The Delphi questionnaire has been extensively described elsewhere . The quewww.surveymonkey.com). In a few cases, the questionnaire was administered by phone; the score was assigned using the qualitative answers of the experts. Survey data were analysed using Stata 15 software for Windows , and descriptive analyses were carried out .The survey was administered online using a web method  R&D processes; (ii) device outcome-measure; (iii) structure, which included structural peculiarities of the company and reference market segment. We organised the prioritised themes into two groups of relevance  using comments and ratings from stages 1 and 2 combined with our interpretation. At last, we revised and edited the prioritised themes to ease the use of the checklist. We indifferently use the term’ item’ or ’driver’ to refer to the framework items.The involvement of the Ethics Committee of Sant’Anna School of Advanced Studies was unnecessary, as the study recruited expert academics in HTA and MD developers involved in a qualitative study. There was no patient contact or involvement, and no access to patient data and medical records was necessary. The study was conducted by the EU General Data Protection Regulation EU-2016/679 (GDPR). Academic and industry experts were invited to participate through an information letter describing the study’s aims and methodology, and participants signed a written consensus. Data were stored on a protected server and collected anonymously.We found out that SEs and LEs perceived success differently. Indeed, SEs perceived success as business continuity, whereas LEs identified success as large-scale utilisation and value experimented by patients and target users. The different perceptions of MD success led us to elaborate on two separate definitions based on enterprises’ size .We are very driven by patient value and whatever enables us to provide more value to the patients. That is a success. Patient outcomes are a success. No economic value, no simple technology development. If a surgeon finds value in using the device. That is a success." CEO, large company]The definitions of success as business continuity for SEs and market share for LEs involve measurable indicators that are relatively easy to obtain. The second definition of success for LEs, i.e., success perceived as achieving incremental value for patients and end-users, can be more challenging to quantify. "’MEDKET’ for SEs and LEs included 21 (13 primary and eight secondary) and 15 (12 primary and three secondary) items, with nine overlapping themes for both SEs and LEs. In both groups, success was driven by three major item categories: (i) R&D processes ; (ii) device outcome measures ; (iii) structural peculiarities of the company  and the specific market . Most ’MEDKET’ drivers belonged to the first item category .The field-testing of the MEDKET checklist through 40 retrospective case studies collected from a selected sample of European and US small and large enterprises showed that primary and secondary framework items might drive MD success. Successful case studies had, on average, a more significant proportion of positive responses  on the ’MEDKET’ checklist compared with failed case studies. Similarities and differences between the successful and the failed case studies also emerged regarding the target MD  and its innovation degree. Further information on the MDs assessed in the 40 case studies and successes/failures collected across case studies are detailed in In this exploratory study, we investigated the level of early-stage HTA incorporation into R&D and company decision-making using a four-stage mixed-method approach. The research culminated in a multiple case study that led us to obtain the external validation of the ’MEDKET’ framework. Moreover, we explored to what extent conducting early-stage HTA alongside biomedical R&D might drive future (post-market) product success by gathering retrospective case studies of successful and failed MDs from a selected sample of European and US small and large enterprises. The perceived role of early-stage HTA could have different implications on achieving success according to the enterprise size. Our study suggests original insights and reflections on the perceived role of early-stage HTA in achieving success for SEs and LEs.Our study confirms evidence from the literature concerning the role of early-stage HTA in SEs. Small companies do not perform pre-market or early-stage analyses consistent with an early-stage HTA approach. This is not only due to the need for more resources and opportunities to conduct pre-market HTA but also to a specific knowledge-gap problem . Many developers need to be made aware of health economics concepts, human-factor aspects, and market challenges, as they appear driven mainly by technological value and pioneer spirit. After several years of development efforts, SE developers realise they have to deal with the challenge of financial sustainability. However, last-minute adjustments are not possible at later stages when the device has already reached a high level of technology maturity. A "last-minute" approach to HTA may increase the risk of product failure and, for mono-product companies and start-ups, the risk of company failure. One company has failed during the conduction of the present study.failing fast, failing cheap); (iii) approach the R&D process more systematically while increasing the probability of future (post-market) product success. This evidence is well documented in the literature [Our study sheds light on the perceived role of early-stage HTA in large companies to achieve post-market success. Our study provides evidence of the fact that LEs perform R&D analyses consistently with an early-stage HTA strategy, as conducting pre-market or early-stage HTA analyses can: (i) increase the overall R&D efficiency and efficacy; (ii) anticipate the interruption of devices in development that are likely to be unsuccessful in later R&D phases .Anticipating financial sustainability, health economics, and human factors alongside a biomedical technology’s lifecycle is essential for surviving the market. SEs should urgently adopt early-stage HTA to develop MDs more likely to meet the market’s expectations incorporating human-factor and financial requirements from the early stages of concept, design, and development. Furthermore, systematically integrating these requirements into the R&D process of innovative MDs might build more confidence in potential investors, ease searching for funding, and guarantee company survival and market continuum.LEs should address the ’optimum’ threshold of ’how’ conducting early-stage HTA by adopting a ’prioritisation’ approach that maps the TRL reached by the product with the assessment dimension(s) that is(are) priority . Both SEs and LEs should increase and promote collaborations with academia, which can have a strategic role in conducting and disseminating early-stage HTA analyses. Finally, governments should provide comprehensive governance and leadership to define globally agreed rules on what and how constitutes reliable evidence for market approval and regulatory process of new or novel MDs to increase data sharing and public health transparency.This research does present strengths and limitations. We highlight that the study was conducted using a company perspective. Thus, a mutual understanding of the implications associated with the perceived role of early-stage HTA as a driver of MD industry success needs to be further understood across other relevant stakeholders  with purposes of alignment. Another limitation concerns the adoption of a small sample size of participants that prevents us from drawing any conclusion regarding geographical variations. Whether (and how) the role of early-stage HTA in MD industry success varies considerably across countries is a critical consideration that needs further investigation. Finally, many study design limitations are typical to qualitative research, especially the Delphi process, which may lead to a compromise position rather than true consensus and a small sample size with unpredictable representation. Given the time and resources of this exploratory exercise, a certain degree of convenience sampling was required, as a random sampling approach was not feasible. Among the study strengths, we highlight (i) the use of a multi-method approach; (ii) a fruitful collaboration between academia and industry; (iii) the collection of multidimensional data on MD successes and failures by facing sparse and fragmented evidence characterising this emerging sector. In this sense, our study is the first to provide a holistic picture of the perceived role of early-stage HTAs in MD industry success.In this exploratory study, we investigated the level of early-stage HTA incorporation into MD R&D and company decision-making. Despite some limitations common to qualitative research, this study is the first to provide a holistic picture of the perceived role of early-stage HTAs in MD industry success. Our findings led us to draw relevant recommendations addressed to industry, governments, and academia to increase the efficacy and efficiency of the overall biomedical technology lifecycle.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.S2 Appendix(DOCX)Click here for additional data file.S3 Appendix(DOCX)Click here for additional data file.S4 Appendix(DOCX)Click here for additional data file.


Current guidelines recommend endoscopic resection for superficial colorectal neoplasia in patients with ulcerative colitis (UC), especially for clearly visible colitis-associated neoplasiaWe previously described the benefits of using adaptive traction devices (A-TRACT 2 and A-TRACT 4) to anchor two or four points of the lesionA 61-year-old man with UC had a large neoplastic area involving three-quarters of the circumference of the rectum. After circumferential incision and trimming, the first two loops were fixed by clips to the oral and anal edges of the target area. Six other loops were fixed on lateral edges of the lesion and another clip was attached to affix the rubber band to the opposite rectal wall . The diVideo 1 Challenging endoscopic submucosal dissection of a giant rectal lesion facilitated by A-TRACT 8. Image shows rectal dysplasia on ulcerative colitis.We hypothesize that such a dedicated device could facilitate resection of giant lesions, especially in selected cases, such as patients with inflammatory bowel disease, where the technical difficulties due to fibrosis can represent a great challenge and result in a time-consuming procedure.Endoscopy_UCTN_Code_TTT_1AQ_2AD


Retroelements (REs) had been considered ’Junk’ until the encyclopedia of DNA elements (ENCODE) project demonstrated that most genome is functional. Although the function of retroelements has been reported in diverse cancers including human breast cancer (HBC) and subtypes, only a few studies have suggested the putative functions of REs via their random genome integration. A canine mammary tumor (CMT) has been highlighted due to the similarities in molecular and pathophysiology with HBC. This study investigated the putative roles of REs common in both HBC and CMT. The human LINE and HERV-K sequences harbor many miRNAs responsive elements (MREs) for tumor-suppressive miRNA such as let-7. We also observed that various MREs are exist in the ERV and LINE highly expressed in the transcriptome data of CMT as well as HBC sets. MREs against miR-126 were highly expressed in both HBC and CMT while the levels of miR-126 were down-regulated. Oppositely, the expression of miR-126 target genes was significantly up-regulated in the cancers. Moreover, cancer patients with an increased level of miR-126 showed better overall survival. The expression of ENPP5, a putative miR-126 target gene, was downregulated by miR-126 mimic. Importantly, overexpression of LINE fragment significantly suppressed miR-126 function on the target gene expression. We propose the functional role of REs expression in tumorigenesis as competing endogenous RNAs (ceRNA) against tumor-suppressive miRNAs. This study provided pieces of evidence that LINE expression, even partial and fragmented, have a regulatory function in ENPP5 gene expression via the competition with miR-126. It is not surprising any more that almost half of our genome is composed of retroelements  which has been known as ‘Junk DNA’ . Around For the last few decades, the function of REs expressed in some disease conditions including cancers has been suggested with various mechanisms depending on transposable activity and protein coding potentials , 4. SeveOf note, most of REs are found to be transcribed as non-coding RNAs (ncRNAs) with unexpected implications of novel genetic mechanisms in tumorigenesis , 15. TheDogs and canine mammary tumor (CMT) have been paid attention as a model for human breast cancers. Dogs develop spontaneous CMT with clinical and molecular similarities to human breast cancer (HBC) . Some clhttp://www.heatmapper.ca) ..47]. We Through the bioinformatic analysis, we demonstrated a common increase in RE-derived MREs for miR-126 in HBC and CMT samples. We thus confirmed whether the overexpression of REs could affect the regulatory functions of miR-126. The expression of miR-126 decreases in cancer in the BRCA transcriptome database . On the Our current study is based on the findings of the ENCODE project demonstrating more than 80% of genome are transcribed to RNAs. Since REs comprised approximately 50% of human genome, it is expected that much of these transcripts come from REs. However, until now most transcriptome analysis has been conducted to focus on the genes which are composed of 1.2% of entire human genome. The RE transcriptome was rarely analyzed because of not only uselessness ‘called as junk’ but also the limitation of RE analysis using high-throughput sequencing with the short reads. More attentions onto REs and their functions in both normal and diseases condition are necessary for better understanding in genome molecular biology.The association of RE expressions with cancerization has been reported, and their functions are suggested at various levels . Most REUnfortunately, this study has a limitation that we only investigated the MREs on the significantly increased REs in cancer. The MRE investigation in the overall REs expression will provide better information to understand the role of RE as a ceRNA. The total amount of individual MREs is more meaningful than the source of particular RE types. For instance, differentially expressed (increased or decreased) REs could share MREs that compensate for MRE changes. However, this study is still worthwhile because most of the REs we identified are significantly increased in cancers.CMT is used as an animal model due to its high similarity to HBC. We thought that the roles of REs might be specific to each species depending on the type and sequence of REs, but the evolutionarily conserved REs and their functions would be significant. It suggests that the expression of REs can be involved in the regulation of miRNAs in humans and other mammals at least in disease conditions including cancers. As an example of the tumor promoting function of MREs, we found that MRE-miR-126 is commonly elevated in HBC and CMT. The miR-126 is a tumor suppressor and its expression is reduced in HBC. It is known that the treatment of miR-126 inhibited cancer cell proliferation and induced G1 arrest . This stENPP5 expression levels in the cell line, MDA-MB-231 about five times higher than in MCF-10A. This study provides critical clues that the increased expression of miRNA responsive elements in retroelements across the genome can play a crucial role in tumorigenesis by regulating tumor suppressive miRNAs and thus relieving the blockade of oncogene expression.S1 Fig(A) molecular functions and (B) cellular compartments using the putative target genes of miRNAs identified by the MREs on the reference RE sequences (C) The Pearson correlation between the expression of putative target genes with APOBEC3C gene expression in public database. ND: not determined.Two other categories of GO analysis (TIF)Click here for additional data file.S2 FigThe procedure, parameters and intermediated results were summarized.(TIF)Click here for additional data file.S3 Fig(A) miR-126 (mimic) successfully reduced ENPP5 mRNA level in other breast cancer cell lines MCF-7 and SKBR-3. (B) LINE overexpression increased ENPP5 mRNA level in MCF-7 cells but not in SKBR-3. *, ** and *** indicate significance p<0.05, 0.01, and 0.001, respectively. ns means not significant.Validation of the association of LINE with miR-126 on the ENPP5 expression (TIF)Click here for additional data file.


Type 1 Diabetes (T1D) is an autoimmune destruction of pancreatic beta cells. The development of the Edmonton Protocol for islet transplantation in 2000 revolutionized T1D treatment and offered a glimpse at a cure for the disease. In 2022, the 20-year follow-up findings of islet cell transplantation demonstrated the long-term safety of islet cell transplantation despite chronic immunosuppression. The Edmonton Protocol, however, remains limited by two obstacles: scarce organ donor availability and risks associated with chronic immunosuppression. To overcome these challenges, the search has begun for an alternative cell source. In 2006, pluripotency genomic factors, coined “Yamanaka Factors,” were discovered, which reprogram mature somatic cells back to their embryonic, pluripotent form (iPSC). iPSCs can then be differentiated into specialized cell types, including islet cells. This discovery has opened a gateway to a personalized medicine approach to treating diabetes, circumventing the issues of donor supply and immunosuppression. In this review, we present a brief history of allogenic islet cell transplantation from the early days of pancreatic remnant transplantation to present work on encapsulating stem cell-derived cells. We review data on long-term outcomes and the ongoing challenges of allogenic islet cell and stem cell-derived islet cell transplant. Type 1 Diabetes (T1D) is an autoimmune destruction of pancreatic beta cells. In 2022, there were approximately 8.7 million cases of T1D worldwide, with the prevalence continuing to increase substantially . While tThe development of an islet transplantation protocol in 2000 by Shapiro et al. revolutionized T1D treatment and offered a glimpse at a cure for the disease. Since then, advances have been made in optimizing islet cell transplantation as well as exploring alternative sources of islets, notably stem cell-derived islet cells and different transplant sites. In this review, we present a brief history of allogenic islet cell transplantation from the early days of transplanting pancreatic remnants to present-day work on encapsulating stem cell-derived cells . We alsoThe origin of transplantation as a treatment for diabetes dates back to the 1800s , before The next breakthrough came in the early 1900s with experiments involving pancreatic duct ligation and intraperitoneal injection of “extracts of degenerated pancreas” by Eugene Gley . He publAlthough the early 1900s improved the understanding of islet cells and their role in insulin secretion, islets were challenging to isolate. In 1960, Horaguchi and Merrell introduced the technique of perfusing the pancreas with collagenase to detach islets from the collagen matrix ; this spIn 2000, Shapiro et al. developed the Edmonton Protocol for islet cell transplantation  and intrIn 2006, Shapiro et al. published their follow-up findings of 36 patients treated with pancreatic islet cell transplantation at nine international sites . Per theIn 2022, Marfil-Garza et al. published the 20-year findings of pancreatic islet cell transplantation from the University of Alberta in Edmonton, Canada ; this waThese findings are consistent with the data published by the Collaborative Islet Transplant Registry (CITR) in their 5-year outcome data of islet transplantation in 398 patients with T1D complicated by severe hypoglycemia events . The CITThe largest retrospective, multicenter cohort study from the CITR was recently published by The Lancet, presenting the five-year outcome data for 1210 patients who received islet transplantation or islet-after-kidney transplantation in the last 20 years . The priIn this study, islet graft function was measured 28 days following the last islet infusion and calculated as the BETA-2 score using fasting C-peptide and glucose levels and exogenous insulin needs; this revealed a linear relationship between primary graft function and long-term transplant success, which was independent of patient factors and immunosuppressive strategies. The mean primary graft function of patients was quantified using the BETA-2 score and was inversely related to the cumulative 5-year incidence of unsuccessful islet transplant of 70.7% . What reOverall, these recent studies and clinical data results support the safety and efficacy of islet cell transplantation for the treatment of T1D and provide promising new directions for future research in optimizing the long-term success of transplanted islets.While the advances made in improving the Edmonton Protocol are promising, they remain limited by two main obstacles: scarce organ donor availability and risks associated with chronic immunosuppression. To overcome these challenges, the search has begun for an alternative cell source. The most promising avenue is the exploration of stem cell-derived islet-like cells. Islets can be derived from embryonic stem cells (ESC) or induced from pluripotent stem cells (iPSC).The derivation of islets from ESCs has been successfully carried out since the early 2000s. In 2006, D’Amour et al. generated pancreatic endoderm cells from ESCs, which expressed insulin at a similar level to human islets but were not yet responsive to glucose stimulation . In 2008In 2022, Vertex announced in public media the results of their first trial patient with T1D who received an intraportal infusion of ESC-derived islet cells. They showed an increase in both fasting and post-prandial C-peptide levels, and the first patient attained complete insulin independence . These tViaCyte, on the other hand, encapsulated ESC-derived pancreatic endoderm cells in a biologic membrane device, which was then implanted subcutaneously. VC-01, ViaCyte’s first cell-based therapy, encapsulated pancreatic progenitor cells (PEC-01) derived from ESCs in a device called PEC-Encap. These cells further matured into ß-like cells once implanted subcutaneously. ViaCyte then improved this therapy in VC-02, where they used the same implant model but with more mature and functional cells (PEC-02). The preliminary results from 17 patients with T1D who received this transplant were shared in 2021. Six of the 17 patients had detectable C-peptide secretion six months post-transplant . Both clWhile ESC-derived islet cells address the problem of islet and donor supply, recipients still require chronic immunosuppression. In response, a new direction of study has emerged with the use of pluripotent stem cells. In 2006, Takahashi and Yamanaka described the use of pluripotency genomic factors, coined “Yamanaka factors,” which can reprogram mature somatic cells back to their embryonic, pluripotent form—known as inducible pluripotent stem cells (iPSCs) . iPSCs ciPSCs differentiate and mature into islet-like cells through a seven-stage process, as illustrated in Another recent advancement in optimizing iPSC maturation is the improved three-dimensional cell expansion protocol. Cuesta-Gomez et al. (2023) demonstrated that 3D expanded cells showed higher expression of pluripotency markers  compared with cells cultured in 2D planar models (69.4% vs. 57.4%) . TraditiOptimizing stem cell-derived islet cells is rapidly progressing. These cells remain a promising alternative to islet cells and have the potential to have the same efficacy as human islet cells. Further work is needed to limit off-target growth and cyst formation and to determine the best site for implantation of these cells therapeutically.Several challenges remain with allogenic islet cell transplantation, as summarized in Anti-inflammatories have been shown to improve islet cell survival post-transplant and minimize inflammatory responses after infusion. Two agents that are used are etanercept (TNFα blocker) and anakinra (IL-1 receptor antagonist). Etanercept neutralizes lymphotoxins while anakinra prevents ß-cell destruction and minimizes the instant blood-mediated inflammatory reaction that occurs after islet cell transplantation . In theiOnce islet cells are transplanted, and the initial inflammatory response is overcome, the next barrier to graft survival is graft acceptance and tolerance by the host. One novel approach is the co-infusion of islet cells with regulatory T cells (Tregs). Tregs are immunomodulatory cells that play a role in preventing autoimmune rejection. A 2016 study by Visperas and Vignali investigated the role of Tregs in causing T1D . They arFinally, another approach to mitigating the challenge of immunosuppression is the co-transplantation of islets with mesenchymal stromal cells (MSCs) as accessory cells. Wang et al. (2022) engineered MSCs to overexpress PD-L1 and CTLA4-Ig . In vitrMSC co-transplantation has also been shown to improve the vascularization of the transplanted islet graft in a mouse model by promoting endothelial and smooth muscle cell proliferation and migration, further improving graft survival . In anotThese experiments demonstrate local immunomodulation without the need for any physical barriers between the islets and host or any manner of cell encapsulation. While promising, further investigations are needed to explore the long-term efficacy of this approach, whether it can be translated to other transplant sites such as the portal vein or subcutaneous space, and whether the same degree of immunosuppression and islet survival can be achieved with allogeneic MSCs.The immediate blood-mediated inflammatory reaction discussed above is incredibly detrimental to islet cells. Mitigating this has been challenging as islet cells are more prone to hypoxia than other cells and require high levels of oxygen to engraft and survive . By encaEncapsulation can be broadly divided into two categories: micro and macro-encapsulation. Micro-encapsulation techniques involve coating islet cells in a thin natural polymer, traditionally consisting of alginate. Alginate hydrogels are modifiable in firmness and permeability. When mixed with islet cells and then injected into the recipient, the hydrogel polymerizes into a fibrin gel, creating a protective porous nest for the islets . DiffereSome of the challenges encountered with microencapsulation are the inflammatory foreign body response to the polymer as well as the injectable nature of the mixture; this does not allow for retrieval of the graft if problems later arise. These questions prompted the development of macro-encapsulation techniques, which involve implanting devices over 1 mm in size ; this alIn 2022, Zhan et al. introduced the potential for “islet banking” by developing a novel vitrification process for islet cells . TraditiTheir group instead proposed suspending the islets in cryoprotectant within a nylon mesh, which wicks excess cryoprotectant from the cells, increasing islet density prior to submersion in liquid nitrogen; this increased the rate of cooling and warming. They subsequently described the optimal composition of cryoprotectant for islets using a mixture of ethylene glycol and dimethyl sulfoxide to maintain islet viability. Their methods achieved over 90% of islet cell recovery and viability, with cells showing similar morphology, function and insulin secretion when compared to non-vitrified islets .The results of Zhan et al. lay a foundation for further experimental directions, including testing this protocol in different batches of stem cell-derived islet cells to assess for variability in cell function post vitrification as well as evaluation of this technique to assess for transportation of cells between centers.Traditionally, islet cells have been transplanted into the hepatic portal vein as the only successful routine clinical site . This miThe subcutaneous space is relatively avascular; however, it is easily accessible and lends itself well to the introduction of biomaterial or macro-encapsulated islet cells. These bioscaffolds mimic an extracellular matrix and are based on natural polymers such as collagen, fibrin, and alginate . Their dMore recently, Yu et al. demonstrated successful device-less islet transplantation subcutaneously without the need for priming by incorporating islets in an “islet viability matrix” composed of collagen, glutamine, fetal bovine serum and medium . They deAnother potential site for islet cell transplant is the omentum. Its large surface area, high vascularity and portal venous drainage system make it an opportune transplant site . A cliniWhile the laparoscopic approach is promising for omental transplants, one limitation of this approach is the difficulty of subsequent islet cell transplants due to adhesions, risks of wound infections and impaired healing with repeat invasive surgeries, particularly if converted to a laparotomy . NeverthAllogenic islet cell transplantation has evolved considerably since the early experiments of Oscar Minkowski, Emmanuel Hedon, and Eugene Gley. The Edmonton Protocol of human islet cell transplantation was built on the foundation of knowledge developed by these pioneers. Recent advances have optimized the long-term success of transplanted islet cells, and in parallel, stem cell technology has introduced the possibility of an alternate source of islets.As researchers around the world race to develop the final cure for diabetes, new developments and discoveries are rapidly emerging. This review is a testament to the vast amount of knowledge and information that has been discovered in the last few years alone and the exciting new avenues for further exploration.


In this report, we present a series involving critically ill patients with known coronavirus disease (COVID-19) infection where a portable X-ray machine equipped with artificial intelligence (AI) software aided in the urgent radiographic diagnosis of pneumothorax. These cases demonstrate how real-world clinical employment of AI tools capable of analyzing and prioritizing studies in the radiologist’s worklist can potentially lead to earlier detection of emergent findings like pneumothorax. The use of AI tools in this manner has the potential to both improve radiology workflow and add significant clinical value in managing critically ill patient populations, such as those with severe COVID-19 infection. The world remains in the midst of the ongoing coronavirus disease 2019 (COVID-19) pandemic caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). First declared a global pandemic by the World Health Organization on March 11, 2020, more than 765 million cases of COVID-19 and 6.9 million deaths have been reported worldwide as of April 30, 2023 [Several cases of spontaneous pneumothorax in patients with COVID-19 have been reported in the literature -4. AdditSeveral hospitalized patients with known COVID-19 infection underwent routine chest X-rays acquired with an AI-enabled portable X-ray scanner. This machine was able to automatically detect the presence of pneumothorax in these patients and generate an alert in the patient archiving and communication system (PACS), enabling prioritization of these studies for rapid review by the radiologist and ultimately expediting urgent intervention. This article highlights the utility of this AI tool in promoting prompt detection of a critical finding by radiologists, which not only improves radiology workflow but also has the potential to add significant clinical value in the management of critically ill COVID-19 patients.Three patients with laboratory-confirmed COVID-19 infection with imaging findings that raised concerns for pneumothorax detected on an AI-enabled portable radiography machine were retrospectively identified through a search of saved cases in PACS. All three patients were in the ICU setting when AI-enabled chest radiography was performed and their ages ranged from 23 to 76 years.Images were acquired on a portable radiography machine equipped with Critical Care Suite , an FDA-approved AI tool that can be used for pneumothorax detection . This teCase 1A 23-year-old pregnant female with a past medical history of asthma presented to the emergency department (ED) with worsening shortness of breath, chest pain, fevers (maximum temperature of 101.3 °F), and poor appetite. Laboratory tests confirmed the diagnosis of COVID-19 and she was admitted to the Internal Medicine floor for further management. During hospitalization, she developed preeclampsia and her clinical picture continued to deteriorate. She required intubation and subsequently underwent emergent cesarian delivery, after which she was transferred to the ICU. Postoperatively, her course was complicated by multifocal pneumonia that quickly progressed to ARDS, requiring cannulation for veno-venous extracorporeal membrane oxygenation Figure . A folloCase 2A 61-year-old male with a past medical history of asthma, emphysema, hepatitis C, and a recent diagnosis of COVID-19 two weeks prior presented to the ED with acute-onset shortness of breath. This patient had visited an external hospital earlier in the day where a chest radiograph demonstrated patchy infiltrates bilaterally, correlating to his known pneumonia secondary to a recent COVID infection Figure . He was Case 3A 76-year-old female with no significant past medical history initially presented to an external hospital ED with altered mental status. She was found to have acute hypoxic respiratory failure due to COVID-19 pneumonia and required hospitalization. Her condition progressed to ARDS, requiring intubation and transfer to the ICU on hospital day 10 Figure . Over thEstablished lung imaging findings reported with COVID-19 primarily pertain to CT and include multifocal ground-glass opacities in a predominately peripheral distribution with slight lower lung predilection and a striking absence of pleural effusions . Chest rHowever, as imaging volumes continue to rise worldwide, increasing clinical demands on radiology departments have challenged current workflow models. In some settings, it may not always be feasible for radiologists to read and interpret all acquired radiographs in a timely fashion, particularly those ordered as a routine priority without clinical suspicion of an acute abnormality or those performed outside of peak radiology staff times . This caLeveraging an AI tool that expedites pneumothorax detection is highly desirable given that timely detection of moderate or large pneumothoraces can enable prompt and appropriate clinical management that mitigates the risk of serious complications. The AI tool explored in this case series, which specializes in pneumothorax detection, was first developed by researchers at the University of California, San Francisco (UCSF) and licensed to GE Healthcare for introduction into the clinical world . During In its evaluation by the FDA, the Critical Care Suite software was tested on a dataset of 804 frontal chest X‐rays . The reaThe three cases presented in this case series serve as a real-world examples of an AI-enabled platform in action and highlight several key benefits of this technology in clinical practice. The scenario described in the first case demonstrates the potential role of the AI-enabled tool in detecting an unsuspected pneumothorax on a routine chest radiograph, which led to the prioritization of the study’s review by the interpreting radiologist. The second case highlights the utility of the AI-enabled tool in recognizing potential complications associated with chest tube management, such as air leaks. Lastly, the third case highlights the ability of the AI-enabled tool to detect subtle pneumothoraces. Altogether, these cases illustrate how the integration of an AI-enabled portable X-ray machine may accelerate the detection and diagnosis of pneumothorax in the setting of COVID-19, thereby enabling the primary team to provide timely and appropriate treatment to minimize complications from pneumothorax in already critically ill patients.While our case series documents real-world examples of one particular AI tool's utility in assisting and expediting the detection of pneumothoraces in ICU patients, the potential for continually advancing AI to be leveraged more broadly within intensive care medicine represents an exciting prospect for the future. A few possible uses that have been explored include predicting a patient’s length of stay in the ICU, evaluating a patient’s likelihood of developing complications, and assisting in fine-tuning mechanical ventilator parameters for a given patient ,13. HowePneumothorax is an uncommon but possible complication in critically ill patients with COVID-19 infection. The interpreting radiologist is often the first person to identify this abnormality on routine chest radiographs and hence has the potential to add significant clinical value in managing this patient population through timely and accurate interpretation. The timeliness of interpretation of these critical findings relies in large part on the acuity of the order requisition and worklist demands of the radiologist. This report described a few cases that illustrated how the employment of AI-enabled software capable of analyzing and prioritizing studies in the radiologist’s worklist can potentially lead to earlier detection of emergent findings like pneumothorax, thereby greatly improving radiology workflow and ultimately patient outcomes.


The use of non-invasive brain stimulation (NIBS) techniques to study the brain has increased significantly in recent decades. It has become one of the most accepted therapeutic approaches and powerful tools in treating neurological and psychiatric disorders. NIBS, such as Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), have been proven effective in several clinical conditions, such as major depressive disorders, stroke, and to improve addition/craving and cognition, in both young and geriatric populations . The results add to the current literature on the treatment of geriatric depression. They may result in short-term clinical gains in this population, especially for those who cannot tolerate antidepressants or are resistant to standard treatments. Furthermore, the study of the effects on specific biomarkers will improve the understanding of the neurobiological mechanisms of depression and their relationship to the treatment.Although the use of rTMS for the treatment of depression in adults is relatively well established, there is still the need to develop and test new ways of rTMS in geriatric depression. Theta-burst stimulation (TBS) is a form of rTMS that mimics the rhythms of brain activity and uses short bursts of high-frequency stimulation, with bursts of stimulation about five times per second  with baseline performance (sham stimulation) . In theChen et al. examined both clinical improvement and alpha (α) rhythm changes in resting-state electroencephalogram (rs-EEG) induced by three tDCS protocols in patients with chronic ischemic stroke. In this single-blind randomized crossover design, a total of nineteen patients received four experimental sessions with four tDCS protocols: anodal tDCS (atDCS), cathodal tDCS (ctDCS), bilateral tDCS (bi-tDCS), and sham tDCS. Both clinical and rs-EEG were assessed before and after the tDCS session. The results showed that the three tDCS protocols differentially modulated α-EEG. AtDCS, especially the low-α rhythms (8–10 Hz), increased the α power at focal regions in the central and distal regions of the frontal and parietal lobes, especially the low α (8–10 Hz). Bi-tDCS modulated mainly high-α rhythms (10-13Hz). No modulatory effects on EEG rhythms were found after either ctDCS or sham. In addition, clinical factors of post-stroke time and the degree of motor impairment were found to be associated with a high-α change from atDCS and bi-tDCS. The modulatory effects persisted for up to 20 min without decay. This study suggested that different tDCS protocols have distinct modulatory effects on the brain, as assessed by α-rhythm EEG. The authors also suggested the dependency of a high-α on clinical features, such as post-stroke time and motor impairment.The heterogeneity of NIBS results may not be only determined by the clinical profile and baseline performance but also due to protocol heterogeneity. Thereby, a study by Ayanampudi et al., two 15-min pre-sleep personalized transcranial alternating current stimulation (tACS) was applied in 25 volunteers to modulate sleep-dependent neuronal activity in the theta/alpha frequency band. Specifically, they had fixed tACS patterns at 5 and 10 Hz and personalized tACS approach with the stimulation frequencies determined by the individual's peak EEG frequencies in the 4–6 Hz and 9–11 Hz bands. Results showed that personalized tACS extended sleep duration by 22 min, in contrast to the 19 minutes in the fixed tACS protocol. Fixed stimulation, compared to control, did not significantly prolong the sleep duration. Concerning falling asleep, personalized tACS reduced time to onset by 28% compared with fixed tACS. Personalized tACS also improved sleep duration by 33 min for the group with poor sleep quality, compared to both control and fixed tACS. The results of this pilot study have important implications for the design of future clinical trials by showing the therapeutic effects of personalized tACS on sleep, including in individuals with insomnia.In a within-subjects, randomized crossover design (with null-stimulation controlled) by Another way to test new brain stimulation protocols is to combine two NIBS that have been tested separately for their effects on a specific clinical condition. Thus, in the study by Quin and colleagues, they tested the effects of TMS combined with peripheral repetitive magnetic stimulation (rPMS) on limb spasticity in subjects with post-stroke spasticity (PSS) on clinical recovery assessed by clinical scales and by pre- and post-stimulus resting-state brain activity using resting-state functional magnetic resonance imaging. A total of forty-nine PSS subjects were randomly assigned to one of three study groups: (1) Combined (LF-rTMS and rPMS); (2) Low-frequency rTMS (LF-rTMS), and (3) Control (routine rehabilitation). Results showed that all participants had a decrease in the MAS scores and an increase in both FMA-UE and MBI scores. However, the combined group had significant improvement in motor function and relieved spasticity in PSS. In addition, the combined groups also showed the increased amplitude of low-frequency fluctuation (ALFF) values over the right supplementary motor area, right middle frontal gyrus, and right cerebellum, and reduced ALFF values over the right post-central gyrus. When comparing ALFF between the three groups, the results showed that the combined method, compared with LF rTMS and control, resulted in increased ALFF values in the right cerebellum and decreased values in the frontoparietal cortex. The results provide evidence of the clinical efficacy of combining LF rTMs with rPMS to improve spasticity state and motor function in subjects with PSS, possibly due to the activity regulation in the cerebellum and frontoparietal areas.In sum, we summarized five original research articles addressing various protocols NIBS that investigated fundamental questions in brain stimulation research, such as the effects of personalized stimulation or the combination of different NIBS. More research is needed to facilitate the current NIBS protocols to achieve better results in both basic science and applications of brain stimulation.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Undiagnosed and untreated lung pathologies are among the leading causes of neonatal deaths in developing countries. Lung Ultrasound (LUS) has been widely accepted as a diagnostic tool for neonatal lung pathologies due to its affordability, portability, and safety. However, healthcare institutions in developing countries lack well-trained clinicians to interpret LUS images, which limits the use of LUS, especially in remote areas. An automated point-of-care tool that could screen and capture LUS morphologies associated with neonatal lung pathologies could aid in rapid and accurate diagnosis.We propose a framework for classifying the six most common neonatal lung pathologies using spatially localized line and texture patterns extracted via 2D dual-tree complex wavelet transform (DTCWT). We acquired 1550 LUS images from 42 neonates with varying numbers of lung pathologies. Furthermore, we balanced our data set to avoid bias towards a pathology class.Using DTCWT and clinical features as inputs to a linear discriminant analysis (LDA), our approach achieved a per-image cross-validated classification accuracy of 74.39% for the imbalanced data set. Our classification accuracy improved to 92.78% after balancing our data set. Moreover, our proposed framework achieved a maximum per-subject cross-validated classification accuracy of 64.97% with an imbalanced data set while using a balanced data set improves its classification accuracy up to 81.53%.Our work could aid in automating the diagnosis of lung pathologies among neonates using LUS. Rapid and accurate diagnosis of lung pathologies could help to decrease neonatal deaths in healthcare institutions that lack well-trained clinicians, especially in developing countries. Respiratory diseases in newborns are the leading cause of admission to Neonatal Intensive Care Units (NICU) . In receIn a neonatal intensive care unit (NICU), the most common lung pathologies are transient tachypnea (TTN), pneumothorax (PTX), respiratory distress syndrome (RDS), consolidations (CON), and chronic lung disease (CLD). Clinicians characterize LUS morphologies to classify neonatal lung pathologies. Typical LUS morphologies are Pleural lines, A-lines, Separate or Coalescent B-lines, and Consolidations . PleuralPrevious works have attempted to automate the detection of lung pathologies using LUS morphologies. Summers et al. developed a diagnostic assistant to detect LUS morphologies related to PTX among adults . A prenaWhile the aforementioned works automated the classification of lung pathologies from primarily fetal LUS images, POC-US studies for diagnosing lung pathologies in neonates using LUS morphologies are lacking in the current literature. Moreover, previous studies examined only a subset of the most common neonatal lung pathologies. Thus, our current work aims to automate the detection and classification of lung pathologies in neonates using textural and morphological features of LUS images. Our current work also aims to expand the classification for all neonatal lung pathologies commonly encountered by clinicians in a NICU. Our work could aid in improving the diagnosis of neonatal lung pathologies and alleviate neonatal mortality in developing countries needing well-trained physicians.Our previous works attempt to contribute to automating the detection and classification of common neonatal lung pathologies. In Bassiouny et al. , seven iDTCWT is effective in extracting localized spatiotemporal features from signals and images. Chen et al. previously used 1D DTCWT to extract electroencephalography (EEG) signal features for seizure detection . AydoganExtracted line and texture features from the DTCWT decomposition of neonatal LUS images.Utilized the DTCWT and clinical features to classify typical LUS pathologies among neonates using a Linear Discriminant Analysis model.Models were tested using 2 data sets, a balanced and an imbalanced data set, as well as 2 cross-validation methods: leave-one-out cross-validation (LOO CV) and leave-one-subject-out cross-validation (LOSO CV).The proposed research can help assist the clinical community, especially in remote hospitals, in screening for neonatal lung conditions and ensuring early identification of potential issues.The key research contributions of the paper are listed below:Our work is organized as follows. We present our results in Section 2. We discuss how our results relate to the literature on LUS morphology classification in Section 3. In Section 4, we present our conclusions and the implications of our findings to the rapid and accurate diagnosis of neonatal lung pathologies. We describe in Section 5 our data set, image preprocessing and decomposition, feature extraction, and classification methods. Finally, in Section 6 we provide our declarations including a list of all abbreviations.(i) Linear Discriminant Analysis (LDA) with Leave-one-out Cross Validation (LOO CV) on a balanced data set, (ii) LDA with LOO CV on the imbalanced data set, (iii) LDA with Leave-One-Subject-Out Cross Validation (LOSO CV) on a balanced data set and (iv) LDA and LOSO CV on the imbalanced data set. In performing the above experiments, we also restricted the feature dimension to the top 15 DTCWT features selected by the feature selection method and three clinical features. Considering the approximate training group sample sizes, 18 features will form  10–15% of the training group sizes, which is expected to produce conservative performance without over-fitting. We also tested the distribution of top-selected features by the feature selection method. We found that, in general, Grey-Level Co-occurrence Matrix (GLCM) and Grey-Level Run Length Matrix (GLRLM) features were selected in larger proportions than statistical and Linear Binary Pattern (LBP) features.We performed the following four 6-group classification experiments: 92.78%, most groups are classified well except PTX, which slightly overlaps between Normal and TTN. Table 74.39%, the performance drops considerably compared to the balanced data set. As evident from Table The obtained results are presented in the four confusion matrices in Tables Moving on to the LOSO results in Tables Additionally, to examine whether additional DTCWT features could further improve our classification accuracy, we reiteratively implemented our pattern classification method with LOSO while gradually increasing the number of DTCWT features. We show in Fig. All six typical neonatal lung pathologies observed in the NICU could be classified using line and textural features of POC–LUS images and clinical features.Features extracted from LUS images using 2D DTCWT and clinical features demonstrate the potential to accurately separate the six most common neonatal lung pathologies.Previous works have demonstrated wavelet transform and its variants to detect line and texture patterns from LUS images to classify and assess lung pathologies. Jiao et al. . Also, ten columns/rows of pixels were removed from each side of the image, resizing to [500 400]. The image resizing steps were performed to create a uniform image size for the images in the data set and to remove any non-ultrasound pixels from the edges of some of the images. These steps were taken to remove the high-intensity artifacts that can easily be picked up by some of the sub-images and normalize the images for DTCWT decomposition. Finally, LUS images were cropped to remove unimportant parts and artifacts that appeared at the edges of the video. An example of the preprocessing steps is provided in Fig. The LUS morphologies combine spatially localized information, texture patterns, and small oscillations. These patterns can be characterized as belonging to different spatial frequencies and relative locations, so 2D time-frequency/time-scale transformations may be able to capture these patterns, making extracting features that can quantify them easier.j. k is the translation parameter.The 2-D discrete wavelet transform (DWT) can be used to analyze an image and isolate these different frequencies using different scales. The 2-D discrete wavelet transform uses basis functions to decompose various scaled versions of the input image , 30. TheN and M are the row and column numbers. Using the 2D-DWT an image s follows:2\documeDTCWT-type approaches can be used as it is nearly shift-invariant. Also, DTCWT has good directional selectivity and perfect reconstruction . A 2D tiThe decomposition of an image  follows :4\documeunctions .We extracted features from the top and bottom half of the DTCWT sub-images. The rationale is the top half of the images will have features related to the pleural line and the bottom half will have features related to B-lines and A-lines. We used statistical features directly on the image to extract features that can describe the intensity distribution of the pixels, grey-level co-occurrence features, and rotation-invariant uniform LBP features. We used grey-level run length matrix features to extract features that measure the morphology in the image. A combination of textural and morphological features was selected to obtain a complementary feature set that should produce a more robust classification model . Statistn is the number of rows in the image, m is the number of columns in the image, i is the row number, j is the column number and I is the image.The statistical features below were chosen as they are commonly used as global features in medical image analysis.i, j) of the gray level co-occurrence matrix represents the number of occasions a pixel with intensity i is adjacent to a pixel with intensity j in the LUS image. The GLCM stores the co-occurring values representing the distance and angular spatial relationship of pixels in a structured matrix. We then extracted 5 features from the GLCM [i is the row number of the GLCM, j is the column number of the GLCM and G is the GLCM. Where u is the mean pixel intensity in the quantized image and The grey-level co-occurrence matrix is calculated by determining how often pairs of pixels with specific values and in a specified spatial relationship occur in an image. Then, statistical measures are extracted from the GLCM . To calcthe GLCM .10\documThe grey-level run length matrix stores run lengths based on the grey-level value and length of the run. A grey-level run is a set of pixels with the same grey-level value, which are consecutive and collinearly distributed in some given direction . We calcThe LBP histogram is used to store LBP pixel labels for the image. The pixel labels are calculated by thresholding the 3x3-neighborhood of each pixel with the center value and considering the result as a binary number . We usedAs used in previous works and our initial work , 9, 14, In this work, we used a simple Linear Discriminant Analysis (LDA) based classifier to classify the 6 LUS conditions using the features extracted from the LUS images. A simple linear classifier, such as an LDA, was chosen over the complex non-linear classifiers to emphasize extracting meaningful LUS features relevant to clinical markers and keep the outcomes conservative and realistic. More importantly, LDA is less prone to overfitting when compared to more complex models , which iIn terms of cross-validation, we tested the performance using two forms of cross-validation. First, we used leave-one-out cross-validation (LOO CV), a form of cross-validation where only one image is used as the testing set, and the model is trained on the rest of the images. This is repeated so that each image is used as a testing set. The average accuracy of all these runs then results in per-image classification performance. We also used leave-one-subject-out cross-validation (LOSO CV). In this form of cross-validation, all images belonging to a subject are used as the testing set and the rest of the images as the training set. This is repeated until each subject has served in the testing set. The average accuracy of all these runs then results in per-subject classification performance. The motivation behind the LOSO cross-validation is to avoid biasing the model due to the similarity between images from the same patient. LOO CV was used to estimate the system’s performance when used to make predictions on data not used to train the model. LOSO CV was used to estimate the system’s performance when used to make predictions on a subject that was not used to train the model. We only selected five images from each video to avoid the significant similarity between frames in the same video for our LOO results. The images were selected at equal intervals throughout the video. If the lung was not imaged in the frame, another frame was selected, as at the beginning or end of a few videos. In the results section, we provide overall classification accuracies, confusion tables and weighted F1-score. The weighted F1-score computes the F1 score for individual classes and then averages using each class’s true label count .


In drug design, the prediction of new active compounds from protein sequence data has only been attempted in a few studies thus far. This prediction task is principally challenging because global protein sequence similarity has strong evolutional and structural implications, but is often only vaguely related to ligand binding. Deep language models adapted from natural language processing offer new opportunities to attempt such predictions via machine translation by directly relating amino acid sequences and chemical structures to each based on textual molecular representations. Herein, we introduce a biochemical language model with transformer architecture for the prediction of new active compounds from sequence motifs of ligand binding sites. In a proof-of-concept application on inhibitors of more than 200 human kinases, the Motif2Mol model revealed promising learning characteristics and an unprecedented ability to consistently reproduce known inhibitors of different kinases.  In drug design, it is generally attempted to establish relationships between biological targets and chemical matter. This can be accomplished in different ways, directly or indirectly, for example, by using a three-dimensional 3D) structure of a protein as a template for the design of new ligands or by using a set of small molecules with activity against a given target to infer new active compounds by employing principles of molecular similarity. Early attempts to directly associate target and ligand information for predictive modeling date back about 15 years, when combined protein and small molecule representations (descriptors) were designed to generate machine learning models for distinguishing between true and false protein–ligand associations (complexes) ,3. For sD structuWith the advent of deep learning in drug discovery, various deep neural network (DNN) architectures were adapted for exploring new design concepts establishing immediate links between target and ligand information. For example, on the basis of protein 3D structures, graph or voxel representations of ligand binding pockets were generated using DNNs and combined with other networks to produce ligand shapes and new compounds consistent with such shapes ,5,6. FurDeep generative modeling ,8 is incIn a few studies, RNNs or transformers have also been applied to associate protein and ligand representations. Specifically, three studies have attempted to generate new small molecule ligands from target protein sequences via language models ,23,24. HIn this work, we report the development and application of a simpler transformer model for the design of new active compounds from sequence data. Since the transformer relates amino acid sequences to molecular structure, it is termed a “biochemical language model”. Different from the earlier studies ,23,24 thThe Motif2Mol approach was designed to generate chemical structures from different amino acid sequence segments (motifs). The underlying idea was to derive a language model that associates sequence signatures of target proteins with specifically active compounds and use the model to predict new compounds for targets (sequence motifs) of interest. For this purpose, a transformer model was implemented.The choice of the transformer architecture instead of RNNs for this machine translation task involving different types of molecular representations was motivated by the availability of the transformer-specific attention mechanism that makes it possible to operate on hidden states of different parts of input sequences in parallel . TransfoThe encoder (left) consists of three modules with eight multi-head attention sub-layers each and a feed-forward sub-layer (512 dimensions), which generates a 512-dimensional vector embedding of input sequence motifs through positional encoding . The embedding represents the hidden states. The decoder (right) also comprises three modules with multiple attention sub-layers and a feed-forward sub-layer. Here, however, each module contains two types of attention sub-layers (with eight sub-layers of each type). The multi-head attention sub-layers corresponding to those in the encoder operate on encoder-generated hidden states as well as the output of the first decoder module. Thereby, the multi-head attention sub-layers can learn relationships between sequence encodings on the encoder side and structure encodings on the decoder side and pay attention  to particular sequence segments based on structural features (and vice versa). This architecture facilitates an effective use of the self-attention mechanism. By contrast, the masked attention sub-layers representing the second type only operate on the output of the preceding attention sub-layer of the decoder modules. The masked attention sub-layers identify (and mask) transmitted information that should not be utilized to ensure that translated encodings are created in the correct sequential order. Hence, these layers are designed to prevent translation errors. SMILES tokens are sampled according to the probability distribution learned by the model. Output probabilities are derived in the softmax layer and the decoder generates a 512-dimensional embedding of the output sequence via positional encoding (corresponding ot the encoder).As a proof-of-concept application for the Motif2Mol approach, we selected the design of candidate compounds for ATP site-directed PKIs based on kinase sequence motifs: a topical drug discovery task. 50 potency values of 6 or larger. Pairs of 225 sequence motifs and corresponding PKIs were used as input and output for Motif2Mol model derivation and validation, respectively. In addition, three qualifying kinases  and their inhibitors were exclusively used as test kinases for model evaluation. So-defined sequence motifs of human kinases and inhibitors of these kinases were extracted from ChEMBL   structures among all generated SMILES strings. It is defined as the ratio Nng RDKit , and NalTc is the Tanimoto coefficient [A| represents the number of structures in set A. The Tc was calculated using 2048-bit Morgan fingerprints of radius 3 [a and b.Maximum 1-nearest neighbor (1-NN) similarity (Equation (1)) and average 1-NN similarity (Equation (2)) were calculated to compare the newly generated structures (set of structures A) and existing inhibitors (set of structures B) of a target kinase.fficient  and |A| radius 3  of strucpairwise2 function implemented in BioPython [BLOSUM62 [Sequence identity between two kinases was calculated via pairwise sequence alignment using the ioPython  using BLBLOSUM62  as the sTo establish proof-of-concept of the approach, a large-scale investigation on sequence motifs and PKI data of 228 human kinases was carried out. The Motif2Mol transformer was trained on 49,969 sequence motif/PKI pairs (80%). The trained model was then evaluated using 12,493 sequence motif/PKI pairs . In In addition to studying learning curves and structure generation frequency, analyzing the validity of generated molecular representations see  represenWe then systematically determined the similarity of newly generated Motif2Mol compounds to PKIs. The results reported in Furthermore, maximal nearest neighbor similarity calculations revealed that new structures with 100% fingerprint similarity to known inhibitors were generated for all kinases, regardless of the amounts of available training data  to identical structures a. BTK diTaken together, the findings discussed above show that the Motif2Mol model consistently reproduced known PKIs for all 225 training/validation kinases and three test kinases not encountered during the training and validation phase. Thus, the results provide substantial support for the ability of the Motif2Mol model to generate new specifically active compounds. In this work, we have addressed the design of new active compounds from protein sequence data by considering this design effort as a machine translation task. Accordingly, machine learning was used to transform amino acid sequences into different sequences of tokens representing chemical structures. Therefore, a transformer network was derived to associate sequence motifs of binding site regions in target proteins with textual ligand representations and predict new candidate compounds from sequence motifs. For establishing proof-of-concept, the pilot version of the Motif2Mol transformer was implemented exclusively using public domain programs and available code ,34,36, a


The COVID-19 pandemic is an example of a global infectious disease outbreak that poses a threat to the well-being of children and youth . The consequences of challenges faced during COVID-19 may be longstanding and newly developed interventions are being deployed. We present a narrative synthesis of available evidence from the first 2 years of the COVID-19 pandemic on the feasibility, accessibility, and effects of interventions to improve well-being among children and youth to inform the development and refinement of interventions relevant to post-pandemic recovery.Six databases were searched from inception to August 2022. A total of 5484 records were screened, 39 were reviewed in full text, and 19 studies were included. The definition of well-being and the five domains of well-being as defined by the Partnership for Maternal, Newborn & Child Health and the World Health Organization in collaboration with the United Nations H6 + Technical Working Group on Adolescent Health and Well-Being were used.n = 18, 95%) targeted health and nutrition, followed by connectedness , while fewer studies targeted agency and resilience , learning and competence , or safety and support . Five interventions (26%) were self-guided while 13 interventions (68%) were guided synchronous by a trained professional, all of which targeted physical and mental health subdomains within health and nutrition; one intervention (5%) was unclear.Nineteen studies  from 10 countries were identified, involving a total of 7492 children and youth  and 954 parents that occurred during the COVID-19 pandemic (March 2020 to March 2021). Nearly all interventions (Studies deploying synchronous interventions most often reported improved well-being among children and youth largely in the domain of health and nutrition, specifically physical and mental health. Targeted approaches will be crucial to reach sub-groups of children and youth who are most at risk of negative well-being outcomes. Further research is needed to determine how interventions that best supported children and youth early in the pandemic are different from interventions that are required now as we enter into the post-pandemic phase.The online version contains supplementary material available at 10.1186/s12916-023-02828-4. Since the onset of the COVID-19 pandemic, rigorous efforts have been made by governments and public health officials worldwide to protect the public from disease transmission, including widespread closure of public institutions, implementation of mandatory masking and physical distancing policies, travel restrictions, and “stay at home” orders , 3. SociThe Partnership for Maternal, Newborn & Child Health, and the World Health Organization (WHO) led an initiative of the United Nations H6 + Technical Working Group on Adolescent Health and Well-Being to develop a consensus framework for defining, programming, and measuring adolescent well-being, ultimately defined as that “children and youth have the support, confidence, and resources to thrive in contexts of secure and healthy relationships, realizing their full potential and rights,” including five domains  . Child aExisting literature reviews on children and youth in the context of the COVID-19 pandemic have focused primarily on mental health outcomes , 19, oftWe undertook a systematic review and narrative synthesis to answer: What are the effects of interventions deployed within the COVID-19 pandemic to improve well-being among children and youth? We followed the relevant requirements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines  of child and youth well-being . The. The9]. We initially sought to identify data on interventions to improve well-being that were deployed before the COVID-19 pandemic  as well as during the COVID-19 pandemic. Given that interventions during the COVID-19 pandemic very frequently occurred within the context of broader social lockdowns, our initial search strategy was broad to capture a range of outcomes in the contexts of interventions with and without co-occurring lockdowns. The available literature from before COVID-19 in times of similar health crises was sparse and was therefore not included in this review. Additional identified data from non-interventional studies on the association of strategies or approaches to improve child and youth well-being will be published elsewhere.After a subset of the team  achieved 100% agreement on a pilot test of 50 random citations, all titles and abstracts were reviewed independently in duplicate by two reviewers . Any study selected by any reviewer at this stage progressed to the next stage. The full text of all articles was reviewed independently in duplicate by two reviewers ; articles selected by both reviewers at this stage were included in the final review. Disagreements were resolved by discussion and or the involvement of a third reviewer when necessary. References were managed in Endnote X9 .p-values, measures of variance), and authors’ conclusions were collected. Included studies with notable subgroups determined from the study eligibility criteria  were recorded. Studies that assessed parental well-being outcomes as a secondary outcome were noted. Evidence was assessed for risk of bias by using the Adapted Cochrane Risk of Bias Assessment Tool for assessing the risk of bias for all study designs [After another calibration exercise to achieve 100% agreement, two authors  independently and in duplicate extracted outcome data that were verified independently by 1 author (MS). Information on document characteristics , study characteristics , youth and family characteristics , intervention characteristics , well-being outcomes , statis designs .p < 0.05 as statistically significant. We did not conduct a formal quantitative or qualitative assessment of reporting bias or publication bias.Owing to the heterogeneity of interventions and study designs, including small samples, meta-analysis was not possible. We performed a narrative synthesis of the results, grouping studies according to the type of well-being domain . The WorFigure Fifteen studies (79%) were person-level RCTs , 49, 51,n = 17, 89%) assessed the intervention outcomes using validated assessment tools, five (26%) of which also included single-response questions; two studies (11%) assessed anthropometrics at follow-up. Seventeen studies (89%) identified positive outcomes to improve well-being after completion of the intervention, and two studies (11%) identified neither positive nor negative outcomes, such as adverse events, harm, or distress associated with the intervention. A summary of findings from interventions by the last point of outcome assessment is provided in Table Nine studies (47%) had a low risk for bias, and eight studies 42%) had a high risk for bias, while two studies 11%) were unclear  at 1-month follow-up  while thChoi and colleagues compared the performance of defocus incorporated multiple segments lens with that of single vision lens treatment in reducing myopia progression that was found to be worsening during the COVID-19 pandemic . In thisDing and colleagues conducted a self-guided 8-week model 328-based peer education peer-education RCT with 150 youth  recruited through convenience on youth anxiety, depression, and sleep quality . They foAn 8-week logotherapy-based mindfulness RCT was conducted by Liu and colleagues with the aim to improve internet addiction among 121 youth  in China. The authors did not specify how the intervention was guided. Their intervention not only improved Internet addiction  and its five dimensions, but also improved both (self-rated) anxiety and depression.Shao and colleagues investigated the intervention effect of professionally guided dance therapy based on the Satir model on the mental health of 62 adolescents  with depression located within 4 communities in China . CompareZhang and colleagues explored the intervention effect of an 8-week research-based professionally guided psychological counseling program in combination with physical exercise on 152 adolescents’ mental health  . They reZuo and colleagues conducted an RCT in one school in China on the effect of self-guided Divergent Thinking Training on teenager’s self-efficacy and emotions measured using the General Self-Efficacy Scale . ParticiThe results from the Peer-to-Peer support intervention  provided by Zheng and colleagues of grade 7 students across 12 schools in China in a cluster RCT indicated that their digital behavior change intervention reduced children’s anxiety  and eye strain (on the Computer Vision Syndrome Questionnaire), but not sleep quality , during COVID-19-associated online schooling .Lee and colleagues conducted an RCT in Korea to investigate the effects of 10 weeks of 2 times per week online physical education classes, using Tabata training, on 54 middle school students’ physical fitness  . Their rThe effectiveness of a professionally guided CrossFit program to mitigate the deficits in fitness caused by COVID-19 prevention measures and to evaluate the effects on self-efficacy in a group of 30 children and youth  was studied by Cataldi and colleagues . Their iCruwys and colleagues performed a professional 8-week cognitive behavior therapy (CBT) and Groups 4 Health RCT performed on 174 healthy adolescents in Australia  . The autThree complex cluster RCTs and three complex person-level RCTs focused on improving the connectedness of children and youth during the COVID-19 pandemic. These six included studies reported increased well-being ; increasThe intervention deployed by Sarti and colleagues (described above) resulted in children with specific learning disorders and cerebral palsy scoring higher than typically developing children in Support and in Respect scales of the Comprehensive Inventory of Thriving Children .Chen and colleagues explored the intervention effect of an 8-week meditation mindfulness training and aerobic exercise intervention on negative emotions as measured by the Positive and Negative Affect Scale of 2120 adolescents  with moderate or severe anxiety in five middle schools during the COVID-19 pandemic . After tSchleider and colleagues conducted an RCT with 2452 adolescents  with elevated depression symptoms testing two online (self-guided) 20–30-min single session interventions  with peer narratives and writing activities, compared with a supportive control . CompareMesurado and colleagues measured the efficacy of a professionally guided 7-week Virtual Hero Program in a cluster-RCT to increase positive emotions and prosocial behavior of 211 Colombian adolescents  . They alMalboeuf-Hurtubise and colleagues conducted two cluster pilot and feasibility RCTs to test art therapy experientials—different activities that may be used in art therapy broadly—including an emotion-based drawing intervention and a mandala drawing intervention, in two elementary school classrooms   and PhilTwo complex RCTs included a component to address learning and competence among children and youth. These studies reported improved learning, increased positive emotions, and increased well-being  or decreSarti and colleagues conducted a professionally guided 4-month telerehabilitation program including 56 children  with special needs  compared to children who did not undertake telerehabilitation despite the special needs diagnosis during the pandemic, and with typically developing children . Using tYadav and colleagues evaluated the use of a self-guided Heartfulness Meditation and Audio Brainwave Entrainment to help teenagers cope with mental health issues . The intFive included studies assessed improvements in agency and resilience among children and youth after completing their respective well-being interventions with a follow-up that ranged from 1 week to 12 months. Included interventions reported increased negative coping and increased positive coping , increasThe following interventions have been described above, and only their findings on agency and resilience will be presented here. The Logotherapy-based Mindfulness Intervention by Liu and colleagues improved positive and negative coping and 121 youth as measured on the Trait Coping Style Questionnaire . Shao anThe effect of resilience trainings on self-efficacy of 80 elementary 9–10-year-old school girls across two schools recruited through convenience sampling in Iran was investigated by Gadari and colleagues . The ChiA single study investigated the effect of a well-being intervention to improve safety and support among children and youth. This study reported increased income and decreased violence at seven months .Gulesci and colleagues conducted a complex RCT including 600 vulnerable adolescents aged 15–18 recruited through convenience on a professionally guided 3-month Youth Empowerment Program that offered training in soft skills and technical skills, sexual education, mentoring, and job-finding . The autWe present a detailed systematic review of the effects of interventions deployed during the COVID-19 pandemic designed to improve well-being among children and youth. Although 14 of the 19 included studies (74%) provided high-quality data from RCTs, data for many interventions included small numbers or lack of real-life diversity in the sample , which limited how accurately the data represent the experiences or outcomes of all individuals or cultural groups. A minority of studies that described the development of their interventions integrated children and youth with lived experience in intervention development despite the recognition that intervention developer-user collaboration can enhance the acceptability and usefulness of innovations . Owing tMost included studies deployed mental health interventions to improve psychological well-being. Three types of interventions had the greatest supporting evidence for positive effects on child and youth well-being, specifically (1) recovery psychology , (2) poFew studies included process evaluations to assess implementation  and outcome measures  that is especially important among participants of self-guided interventions to ensure that the intervention for both control and experimental groups is received as specified in the protocol . While mWe evaluated a broad scope of outcomes that were primarily measured using validated assessment tools for symptoms of mental health disorders, the most common of which being the Generalized Anxiety Disorder-7, Children’s Depression Inventory-2, Self-rating Anxiety Scale, and the Self-rating Depression Scale. In addition to assessing the improvement of negative consequences of the COVID-19 pandemic, we included four studies that explored positive adaptations , 64. HopEmerging research describes mixed evidence regarding the impact of the COVID-19 pandemic on children and youth . It is rBased on the results of this review, significant gaps in the existing literature on interventions to improve well-being among youth and adolescents can be discerned. Among the highest priority gaps are the need for well-designed trials that study online interventions and include appropriate and blinded control groups  within an adequate sample size; ethical considerations of withholding interventions in community contexts as well as the inability to blind behavioral interventions may have contributed to this knowledge gap. These interventions have been shown to be potentially effective, but confidence is limited due to lower quality and lack of replication. Independent corroborating evidence for any particular intervention is required. In addition, more structured and comprehensive analysis methodologies need to be applied. At a minimum, gender, age, and relevant social-economic variables of interest should be included as covariates. More research is needed to determine when and for whom an intervention to improve well-being would be developmentally and contextually appropriate. Capturing child and youth voices through introspective and dialogical approaches that transcend cultures is needed to inform the refinement of existing interventions to support child and youth well-being in the post-pandemic phase and for the development of preventive and responsive interventions during future health crises.We used a large number of educational as well as health electronic databases independently and in duplicate assessed study eligibility, conducted data extraction, and evaluated study quality; however, we included only published literature (excluding preprints that may have increased publication bias), and it is possible that studies may have been missed. Several studies reported only descriptive analyses that did not take account of potential confounders. The studies included work performed within the first year of the COVID-19 pandemic and across 10 countries globally that represent varied and diverse pandemic experiences. More work is needed to examine the effect of well-being interventions that were tested in later waves as well as after the COVID-19 pandemic. There are likely to be long-lasting impacts of the pandemic on children and youth well-being. In addition, while several studies included participants with medical conditions , no studies were included on a number of important outcomes or vulnerable groups, including studies of children with autism or studies of eating disorders or substance use; effectiveness of interventions should be generalized with great caution to children and youth other than those in which they have been studied. Owing to the heterogeneity of included studies, it was not possible to conduct a meta-analysis; rather, the results were summarized with a narrative synthesis. We used an established conceptual framework including five broad and non-mutually exclusive domains for adolescent well-being [In this systematic review of interventions from the first 2 years of the COVID-19 pandemic to improve child and youth well-being, studies of short-term and long-term follow-up reported improved well-being among children and youth. Data for many of these interventions came from places where small numbers or lack of real-life diversity in the sample limited how accurately the data represent the experiences or outcomes of certain individuals or specific groups. The available data indicate that future well-being interventions should be evidence-informed, data-driven, and reflective of need; developing acceptable and useful interventions to improve all aspects of youth well-being will require increased availability and access to quality data across sectors. While actions aimed at single issues are necessary and may seem simpler to implement, systemic change that upholds fundamental child rights will lead to sustainable improvement in the overall well-being of all children and youth.Additional file 1:  Table S1 - S4. Additional file 2: Data abstracted from included studies.


The stomach is one of the most deformable organs. Its shape can be easily affected by breathing movements, and daily diet, and it also varies when the body position is different. The susceptibility of stomach has made it challenging to treat gastric cancer using the conventional image-guided radiotherapy, i.e., the techniques based on kilovoltage X-ray imaging. The magnetic resonance imaging guided radiotherapy (MRgRT) is usually implemented using a hybrid system MR-LINAC. It is feasible to implement adaptive radiotherapy using MR-LINAC for deformable organs such as stomach. In this case report, we present our clinical experience to treat a gastric cancer patient using MR-LINAC.The patient is a 58-year-old male who started having black stools with no apparent cause a year ago. Gastroscopy result showed pancreatic cancer, pathology: adenocarcinoma on gastric cancer biopsy, adenocarcinoma on gastric body minor curvature biopsy. The patient was diagnosed with gastric cancer . The patient was treated in 25 fractions with radiotherapy using MR-LINAC with online adaptive treatment plans daily. The target area in daily MR images varied considerably when compared with the target area on the CT simulation images. During the course of treatment, there have even been instances where the planned target area where the patient received radiotherapy did not cover the lesion of the day.Online adaptive MRgRT can be a meaningful innovation for treating malignancies in the upper abdomen. The results in the current study are promising and are indicative for further optimizing online adaptive MRgRT in patients with inoperable tumors of the upper abdomen. Radiation therapy is one of the most effective treatments for stomach cancer . HoweverX-ray imaging methods such as kV radiography and cone beam CT (CBCT) are commonly used in image-guided radiation therapy (IGRT) for patient setup prior to treatment. This reduces the effects of potential setup errors caused by anatomical changes in target and OAR location . HoweverThe patient is a 58-year-old male who presents with a feeling of fullness in the upper abdomen after meal. The patient began to have black stools with no apparent cause in June 2021, several times a day. Gastroenteroscopy showed cardia cancer and diagnostic CT images showed localized thickening and enhancement of the gastric wall on the lesser curvature after treatment for gastric cancer. Pathology results were: adenocarcinoma on cardia biopsy, adenocarcinoma on biopsy of the lesser curvature of the gastric body, immunohistochemistry: Her-2 (3+), pMMR, PD-L1 expression CPS=0, EBER (–). Patient was diagnosed with gastric cancer .The patient received concurrent chemoradiotherapy with oral tegafur-gimeracil-oteracil potassium (S-1) and 25 sessions of online adaptive MR-guided radiotherapy for gastric tumors. The patient was treated with the Unity MR-LINAC. The patient underwent a 4D CT scan with an empty stomach. Before CT simulation, anisodamine (dose 10 mg) was given to reduce gastric motility. The cardia and gastric body lesions  was outlined on the 4DCT scan and the images were combined into an internal CTV (ICTV). The combined ICTV included enlarged metastatic lymph nodes and a planned target area volume (PTV) extending 5 mm outwards from the ICTV. The patient was treated with involved site radiation therapy (ISRT)at 50 Gy in 25 fractions. Patient continued to be treated with Tislelizumab and Herceptin during this period. The patient fasted and received anisodamine (10 mg dose) prior to each radiation therapy session (®) and the resulting images were then reviewed and modified by the attending radiation oncologist. The MR images of stomach tumors were clearer in patients taking scopolamine compared to those not taking it  after outlining the gastric tumor lesions on real-time MR imaging and simulated CT imaging. With CBCT guidance, even after enlarging the PTV by 5 mm as usual, the tumor area was not completely covered at any fraction Figure 2Patient with a DSC of 0 at the second treatment, indicating the complete separation from the target area Figure 3It is generally accepted that local tumor growth in malignant upper abdominal tumors is associated with severe symptoms and significantly reduced quality of life. As advances in systemic therapy have improved patient survival, effective treatments aimed at local tumor control and symptom relief are becoming increasingly important to ensure patient survival and a good quality of life. For this reason, radiation therapy as a minimally invasive local ablation therapy has sparked interest in the treatment of various tumors in the upper abdomen . The stoIntroduction of intensity-modulated radiation therapy, advanced motion management solutions , and image-guided radiation therapy (IGRT) techniques  help reduce gastrointestinal side effects and increase dose to target volume to achieve higher bioequivalent doses . IGRT haAlthough CBCT is very effective, it provides poor image quality for soft tissues, which makes accurate identification of soft tissue targets and surrounding OARs very difficult.The higher morphological quality of MR images allows better visualization and design of treatment volumes compared to standard localization imaging . EmerginAs online MR guided adaptive radiotherapy is a relatively new technology, its unique features have shown that it can effectively deal with the daily geometric deformation of the target and surrounding OARs . It has Our case showed that giving patients scopolamine before treatment session helped to reduce gastric peristalsis, resulting in clearer imaging. MRI-based treatment systems enable real-time tracking of these structures during radiation treatment, thus avoiding under-dosing of the tumor as well as over-dosing of key structures. We have shown that it is feasible to use on-line adaptive MR-guided radiotherapy for patients with gastric malignancies. However, the survival of patients with gastric cancer treated with MR-LINAC compared to conventional radiotherapy needs to be observed over time. Large-scale controlled studies are also needed to confirm the benefits of receiving MR-LINAC.The original contributions presented in the study are included in the article/The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.YS wrote the first draft of the manuscript. YZ, HW, MZ, and FG wrote sections of the manuscript. YS, ZL, and JY managed the radiotherapy treatment plan processing and data analysis. ZL and JY contributed to image review and contouring. YS performed dose accumulation and generated figures. All authors contributed to manuscript revision, read, and approved the submitted version.