There has been a continuous underrepresentation of minorities in healthcare research and vaccine trials, along with long-standing systemic racism and discrimination that have been fueling the distrust of the healthcare system among these communities for decades. The history and legacy of racial injustices and negative experiences within a culturally insensitive healthcare system have greatly contributed to vaccine hesitancy among ethnic minorities. COVID-19 vaccine hesitancy will impact vaccine uptake in the US, subsequently hindering the establishment of herd immunity (75–85% of the population vaccinated) to mitigate SARS-CoV-2 infection and transmission. Information targeting underserved racial/ethnic minorities in the US in a culturally competent manner has been lacking. This information is crucial for educating these communities about COVID-19 vaccines and their distribution as well as dispelling misinformation regarding vaccine trials, safety, and efficacy. This lack of education has greatly contributed to COVID-19 vaccine hesitancy and will increase disparities in vaccine uptake. Moreover, timely vaccinations are also essential to curtailing virus transmission and the emergence of SARS-CoV-2 variants that may evade the immune response produced by the three existing COVID-19 vaccines. SARS-CoV-2 that causes COVID-19 disproportionately affects racial and ethnic minorities compared to non-Hispanic whites (NHW) ,4,5,6,7.Operation Warp Speed (OWS) was a partnership initiated by the US government with the private sector to facilitate and accelerate the development, manufacturing, and distribution of COVID-19 vaccines, therapeutics, and diagnostics . EntitieThe Pfizer vaccine is a lipid nanoparticle-formulated, nucleoside-modified mRNA vaccine that encodes the prefusion spike glycoprotein of SARS-CoV-2  . In a PhThe Moderna vaccine is also a lipid nanoparticle-formulated, nucleoside-modified mRNA vaccine that encodes the prefusion spike glycoprotein of SARS-CoV-2  ,25. In a10 virus particles or a placebo. The vaccine showed an efficacy of 72% against symptomatic COVID-19 with 85% efficacy overall against severe disease. Common adverse events included injection site pain, fever, fatigue, headache, and myalgia [The single-dose Johnson & Johnson’s Janssen (J&J/Janssen) COVID-19 vaccine consists of a recombinant, replication-incompetent human adenovirus serotype 26 (Ad26) vector that encodes a full-length and stabilized SARS-CoV-2 spike protein . In a Ph myalgia .FDA EUA guidance for both the Pfizer and Moderna vaccines is to not administer the vaccines to individuals with a known history of a severe allergic reaction  to any component of the COVID-19 vaccines. In addition, persons with a history of anaphylaxis should be observed for 30 min rather than 15 min after COVID-19 vaccinations for both Pfizer and Moderna vaccines . Even moVaccine hesitancy refers to a delay in uptake or refusal of a vaccine even when the vaccine is proven safe and widely accessible ,34. VaccNational surveys have shown NHW to be more likely to agree to COVID-19 vaccination than H/L and AA . HoweverIn a survey conducted by the Kaiser Family Foundation COVID-19 Vaccine Monitor project, approximately three in 10 rural residents would accept the vaccine compared to four in 10 in both urban and suburban areas . The samIn a recent poll by the Associated Press-NORC Center for Public Affairs Research, 67% of Americans indicated that they either plan to get vaccinated or have already been vaccinated. However, a significant number of individuals who identify as Republicans and individuals without college degrees are still hesitant about getting the COVID-19 vaccine . This leAA are the most heavily impacted by COVID-19 with the highest percentage of COVID-19 cases, the most severe clinical presentation, and the highest rates of hospitalization and COVID19 morbidity and mortality in both adults and children ,46,47. AH/L in the US have been disproportionately impacted by COVID-19 because they are more likely to be hospitalized and die from COVID-19 than NHW . HistoriThere is also vaccine hesitancy in underserved populations in the developing world that could impact herd immunity on a global scale. A recent survey conducted by CompariSure reported that 52% of South Africans will not take the COVID-19 vaccines with religion, fear of needles, and unconsented government tracking being reported as the main reasons for not accepting the vaccine . South AApproximately 330 million doses of the J&J vaccine or 660 million doses of either the Pfizer/BioNTech or Moderna vaccine are needed to vaccinate the entire US population. At the time of writing this review, vaccine supply has fallen short of demand. Vaccine manufacturers have pledged to increase their production capacity or have proposed manufacturing partnerships to increase vaccine supply.Some forms of vaccine hesitancy are directly linked to vaccine supply shortage. For some in the US who are contemplating COVID-19 vaccination, supply shortage may prompt them to delay or avoid vaccination altogether. For those anxiously awaiting vaccination when vaccine supply is scarce, their frustration with the wait could cause them to give up vaccination. It is unclear how low-income countries around the world will get equitable access to COVID-19 vaccines. Strategies to combat vaccine hesitancy on a global scale in a culturally appropriate manner are essential. The global population is connected through international travel and trade. Therefore, to curb COVID-19 spread, we must vaccinate the global community, including individuals from low-income countries and marginalized populations. To achieve this, standards of practice for fair vaccine accessibility and affordability are essential.In the US, vaccine supply shortage is especially apparent at vaccination sites that serve minority populations. Additionally, there are fewer vaccination sites and staff members serving minority communities. These factors contribute to inequities in vaccination among underserved communities most heavily impacted by COVID-19. Consequently, individuals in these communities are less equipped to navigate the complexities of vaccine access and more likely hesitant to get vaccinated.Globally, high-income countries possess 60% of the world’s COVID-19 vaccine supply even though they make up only 17% of the global population. For example, Canada has acquired 300 million doses for its 100 million citizens. Conversely, Nigeria currently does not have access to the vaccines for its 220 million citizens. This inequity in vaccine distribution will perpetuate the pandemic, allow viral variants to emerge, and continue to cripple the global economy. A virtual world summit that meets regularly may be a viable step to identify barriers against global vaccine equity as well as to ensure that low-income countries and marginalized populations have access to COVID-19 vaccines. Raging SARS-CoV-2 infections in developing countries and continual outbreaks in developed countries indicate that COVID-19 is endemic on a global scale. Strategies to facilitate continual vaccinations and vaccine development as well as to curtail the evolution of viral variants are critical.Healthcare providers are among the most trusted advisors and influencers of vaccination decisions. Recommendations from physicians correlate strongly with vaccine acceptance among their patients . UnfortuShekar et al. conducted a cross-sectional study in the US to examine COVID-19 vaccine acceptance among healthcare workers . Among tHigh levels of vaccine hesitancy have been observed in the southern US. A study by Doherty et al. surveyed multiracial participants from nine counties in North Carolina who represent underserved communities in the state. The authors examined the prevalence of COVID-19 vaccine hesitancy and attitudes regarding vaccinations and assessed their correlation with race . There wThe antivax movement continues to expand globally and is becoming more organized with significant financial support ,58,59,60By not accepting safe and effective vaccines, antivaxxers can impose undue harm on society . A reporSocial media platforms and internet providers can play a role in curbing misinformation regarding COVID-19 vaccine safety and efficacy so that science-based information can reach communities that are vulnerable to misinformation. The benefits of COVID-19 vaccines have been overshadowed by political polarization in unprecedented ways. The antivax movement may lower support for science-based policy interventions and lead to reservoirs of unvaccinated individuals that could continue to transmit viral variants of increased virulence that could become completely resistant to the developing vaccines. Therefore, constructive discussions with antivaxxers are essential to promoting acceptance and uptake of COVID-19 vaccines.The success of COVID-19 vaccines will depend on high vaccine acceptance and strategies that combat the lack of education about vaccines and vaccine misinformation in a culturally competent manner. It is essential to provide minority communities in the US with access to COVID-19 clinical trials and COVID-19 vaccines. Unvaccinated minority communities, including the incarcerated, homeless, and migrant communities, are potential infection reservoirs for COVID-19 that may prolong the pandemic in the US. As a result, SARS-CoV-2 variants that are more virulent or can evade the effects of currently available vaccines may emerge, potentially leading to high rates of mortality and disease with little hope of a return to normalcy. Therefore, it is essential that communities throughout the US have a high rate of vaccine acceptance in order to mitigate COVID-19 transmission in a timely manner.COVID-19 vaccination among children (up to 17 years of age) in the US is essential to curbing the pandemic. Unfortunately, this strategy is problematic due to vaccine hesitancy among parents. Parents who are hesitant about COVID-19 vaccines are also less likely to allow their children to be vaccinated. According to the 2010 Census, there were 74.2 million people under the age of 18 in the US  . This woVirtual platforms and events that focus on vaccine hesitancy as well as radio commentaries, flyers, and pamphlets in multiple languages, can provide comprehensive outreach to minority communities. Surveys, such as those conducted before and after specific events, and interviews can also help identify barriers against vaccine acceptance. Virtual town hall meetings sponsored by community leaders and local health care providers can engage minority communities in dialogs that address questions these communities have about COVID-19 vaccines.Minority and marginalized communities in the US, including the medically disabled, homeless, indigenous peoples, and undocumented immigrants, need better access to new and existing COVID-19 preventive infrastructure. We need to deliver the vaccines and other forms of available assistance to individuals who have no access to vaccination sites. Possible strategies to accomplish this include the use of mobile vaccine delivery units and the deployment of vaccine administrators who deliver vaccines to the homeless and other transient and immobile populations.A trained workforce is essential to timely COVID-19 vaccination in the population. The expansion of vaccination sites to unconventional venues, such as the Department of Motor Vehicles, restaurants, churches, salons, coffee shops, post offices, grocery stores, bus/train stations, theme parks, and shelters, can increase COVID-19 vaccine accessibility. Announcements on social media platforms can help individuals find and make vaccination appointments.There is also a need for culturally sensitive approaches so that we can identify subpopulations at risk of vaccine hesitancy. Standards of care in underserved minority communities that combat COVID-19 vaccine hesitancy and promote equitable vaccine distribution are warranted. Research in vaccine development and technologies is also crucial to improving COVID-19 vaccine access, particularly in low-income countries with limited infrastructure. For instance, the Pfizer/BioNTech and Moderna vaccines require extreme storage conditions that many low-income countries cannot afford. Therefore, innovations that can improve vaccine accessibility are crucial to ensuring equity in COVID-19 vaccine distribution.The level of public trust in vaccines warrants examination in the context of specific populations and their experiences with vaccines. A high level of vaccine acceptance across all populations in the US is essential to mitigating the further transmission of SARS-CoV-2 and its variants as well as to achieving herd immunity . It is aThis report was not an attempt to quantify COVID-19 vaccine hesitancy in US. This report is an analysis or snapshot of vaccine hesitancy as it exists at the time of this writing among minority communities in the US. We also acknowledge differences among study participants vs. differences in the methods of data collection cited here. Vaccine hesitancy changes with the dynamics of the pandemic, such as access to vaccines, ongoing education and awareness campaigns, and behavioral changes among individuals that are hesitant to accept the vaccine.


Schizophrenia (SZ) is a prevalent functional psychosis characterized by clinical behavioural symptoms and underlying abnormalities in brain function. Genome-wide association studies (GWAS) of schizophrenia have revealed many loci that do not directly identify processes disturbed in the disease. For this reason, the development of cellular models containing SZ-associated variations has become a focus in the post-GWAS research era. The application of revolutionary clustered regularly interspaced palindromic repeats CRISPR/Cas9 gene-editing tools, along with recently developed technologies for cultivating brain organoids in vitro, have opened new perspectives for the construction of these models. In general, cellular models are intended to unravel particular biological phenomena. They can provide the missing link between schizophrenia-related phenotypic features  and data from pathomorphological, electrophysiological and behavioural studies. The objectives of this review are the systematization and classification of cellular models of schizophrenia, based on their complexity and validity for understanding schizophrenia-related phenotypes. Schizophrenia (SZ) is a severe mental disease affecting 1% of the population globally. Three partially overlapping symptom clusters characterize SZ: positive symptoms , negative symptoms  and cognitive dysfunction. The aetiology and pathogenesis of this disease are largely unknown. There are several hypotheses to explain the origin of SZ. It may result from neurotransmitter misbalances, as suggested in the dopamine, glutamate and gamma-aminobutyric acid (GABA) hypotheses, or from changes in inflammation-related biochemical pathways (the kynurenic acid hypothesis). Both environmental and genetic factors are involved in the pathogenesis of SZ, the latter playing a pivotal role in disease risk; the heritability of SZ is estimated at 70 to 85% . The genAppropriate in vitro and in vivo models are needed to elucidate the pathophysiological mechanisms of SZ and develop new drugs to treat it . CellulaHere, we describe the most important cellular models used in basic research and drug discovery to investigate the molecular mechanisms associated with SZ at the cellular, biochemical and genetic levels. We categorize the models by their validity and focus on the neuronal cultures and cell types relevant to the pathophysiological mechanisms of SZ. Particular attention is given to CRISPR/Cas9 systems as effective instruments to manipulate the cellular models.In living SZ patients, brain structure is unique and complex; environmental factors, medication interference and genetic risk are interlinked. Since the human brain is mainly inaccessible except through post-mortem studies when it is altered both intrinsically and by the medications that were taken, researchers need living biological models. Additionally, biological models allow us to establish the causality of SZ through molecular and genetic manipulation.A good model of SZ should satisfy the following validity triad: face validity, constructive validity and predictive validity . Face vaAlthough the aetiology of SZ remains unknown, pharmacological and post-mortem studies and in vivo neuroimaging point to neurons and glial cells as key players. Initially, altered neuronal signalling was considered to be the cause of SZ. This hypothesis was supported by the mechanism of antipsychotics, modulating the activity of neurotransmitter receptors, mainly D2 dopamine receptors. However, compounds such as N-methyl-D-aspartate NMDA receptor antagonists can reproduce psychotic symptoms, and glial cells can impact SZ progression. Post-mortem electron microscopy of the dorsolateral prefrontal cortex (DPFC) reveals pathological changes in myelinated fibres and damage and degradation of oligodendrocytes . Reduction in the number of dendritic spines in some brain areas and increased protein density in the synapses could be mediated by the action of astroglia, which are involved in the maturation of neurites, particularly of the dendritic spines . MutatioCellular models exhibit constructive and predictive validity. The most popular in vitro model, the SH-SY5Y neuroblastoma cell, is used in neuropsychiatric research. It has the advantage of low cost, ease of culture, reproducibility and available literature . The SH-SH-SY5Y cells display similarities to immature neurons. This cell lineage has dopaminergic and adrenergic properties as well as the proliferative marker (proliferating cell nuclear antigen (PCNA)) and the immature neuronal marker (nestin). Retinoic acid and neurobasal medium induce differentiation of SH-SY5Y cells, including the upregulation of the axonal guidance signalling pathway, growth of neurites and conversion into a neuron-like phenotype. Additionally, the localisation pattern of synapsin-I, a protein associated with the surface of synaptic vesicles, changes during differentiation. This protein shifts from being diffused to aligned with the axonal structure .Both undifferentiated and differentiated SH-SY5Y express the dopamine biosynthesis pathway enzymes and secrete dopamine. The surface of SH-SY5Y contains dopamine, GABA, acetylcholine and glutamate receptors. Taken together, these characteristics confirm the constructive validity of this model .SH-SY5Y cells can be used to reproduce some features of the dopaminergic (DAergic) neurons of the basal ganglia. The main phenotypes with disease-relevant predictive validity for this model are cell survival (resistance to cell damage), membrane potential, the proliferation and migration rates, and the ultrastructure of neurites and synapses.2+ influx. Descending glutamatergic neurons send efferent axons to DAergic neurons in the ventral tegmental area (VTA) and substantia nigra (SN). In this model, SH-SY5Y cells represented DAergic neurons of SN or VTA, and MK-801 was proposed to mimic the consequences of prefrontal cortex dysfunction [SH-SY5Y cells treated with the NMDA-antagonist MK-801 were used as a model of impairments in the neurons of patients with SZ. Paliperidone specifically suppressed the action of MK-801. The effect of MK-801 was mediated through the downregulation of the SIRT1/miR-134 signalling pathway and Cafunction . These dThe convenience of genetic manipulation with SH-SY5Y makes this cell line a valuable object for SZ research. For example, it was used to investigate the molecular mechanisms of the reduction in neurite spines, a well-known vulnerability factor for SZ  that hasSilencing of the SZ susceptibility gene DISC1 (Disrupted-In-Schizophrenia) by lentiviral infection of shRNA in SH-SY5Y induces mitochondrial fragmentation and defects in respiration. Previously, Western blotting and co-immunoprecipitation data (CoIP) were used to demonstrate that reciprocal chromosomal translocation results in truncated forms of DISC1, such as ∆597-854, which fail to incorporate into the mitochondrial contact site and cristae organizing system (MICOS) protein complex. Fluorescent microscopy showed that the DISC1-depleted cells failed to maintain the mitochondrial oxidative phosphorylation (OXPHOS) complex function . All neuSimilar research was conducted for important SZ candidate genes encoding arsenite methyltransferase (AS3MT). AS3MT is the most statistically significant locus outside the major histocompatibility complex (MHC) region associated with SZ . A humanThe forkhead box protein P2 FOXP2 gene encodes a forkhead transcription factor. Mutations in FOXP2 are known to cause developmental verbal dyspraxia, a speech and language disorder. Some polymorphisms of this gene are also associated with SZ. Complex rearrangement involving one copy of chromosomes 7 and 11 might affect some regulatory regions of FOXP2. Notably, the breakpoint in the 7q31.1 chromosome is located 205.5 kb downstream from the 3′ end of FOXP2. Using a luciferase assay, two enhancer regions were identified: the first is located downstream of FOXP2, and the second was found in the intergenic region between the FOXP2 and MDFIC genes. A related neuroblastoma cell line, SK-N-MS, was used to investigate the regulatory role of the two enhancers by targeted deletion using the CRISPR/Cas9 system. The deletion of either enhancer significantly altered the expression of FOXP2 and changed the transcription of six well-known FOXP2 target genes. Thus, identified enhancers regulate the activity of a FOXP2-specific regulatory network in human cell lines. SHANK2 encodes a protein that functions as a postsynaptic scaffolding protein at glutamatergic synapses in the brain. This protein is essential for synapse formation, development and plasticity , and itsSignificantly, the tumour origin of SH-SY5Y does not hamper the investigation of neuronal phenotypes in the context of neurodevelopmental and neurodegenerative diseases. However, specific genomic alterations limiting the use of the model should be taken into account. The SH-SY5Y genome shows trisomy of chromosome 7, gain of the short arm of chromosome 2 (2p25.23-2p16.3) and multiple translocations .The findings made using this cellular model and their reproducibility in other disease-relevant models have proved its constructive and predictive validity.Since animal models cannot reproduce complex genetic disorders such as SZ and autism-spectrum disorders (ASDs), there is a need for patient-specific modelling tools. iPSCs derived from patients recapitulate each donor’s genotype. Initially, iPSCs were used to model diseases with highly penetrant genetic variants of significant phenotypic effect. However, their application has expanded to modelling psychiatric disorders and generating patient-specific organoids. The ability of iPSC-derived neurons to recapitulate fundamental neuronal functions, including firing action potentials and releasing neurotransmitters, led to the development of functional analysis of SZ-associated genetic variants.iPSCs are an indispensable source of a plethora of neural lineage cells. The first iPSC cells were generated by the retroviral delivery of Yamanaka transcription factors  into somatic cells . Then, tiPSCs themselves rarely serve as models of processes associated with SZ. If genetic variations significantly affect the iPSC population, they are probably highly penetrant and responsible for a relatively low proportion of SZ cases. For example, the 22q11.2 deletion was shown to decrease the proliferation rate of iPSCs in neurosphere cultures .The question of the constructive validity of iPSCs and iPSC-derived cells due to intra-subject variability has been discussed extensively . MinimizThe drawback of iPSCs is that mutations and CNVs accumulate in somatic cells undergoing reprogramming. Hence, biological repeats are needed in iPSC experiments. iPSCs and iPSC-derived models can recapitulate events taking place in neurodevelopment and are unaffected by secondary events. iPSCs have advantages over post-mortem cells. A 3D neuronal and glial co-culture derived from CRISPR-edited iPSCs at rs4702 (FURIN) exhibited significant transcriptomic and cellular effects, whereas post-mortem data were inconsistent . Late SZAlthough the reproducibility of iPSC models has been questioned, the appropriate choice of iPSC cells for reprogramming, use of a sufficient number of biological repeats and careful selection of subjects and controls can help overcome their weaknesses.NPCs are first formed during the iPSC-to-neuron transition. NPCs may also be derived from neural stem cells (NSCs) isolated from the olfactory epithelium (OE) or through direct reprogramming (trans-differentiation) of non-neural cells . NPCs foAfter induction with N2 and B27 supplements, with or without the addition of dual-SMAD inhibitors, NPCs organize in neural rosettes. Rosettes are plane structures reminiscent of cross-sections of the neural tube. If clones of NPCs from rosettes are maintained, they differentiate into various types of neurons. Noggin Shh, FGF8 or small-molecule inhibitors can induce migration of the NPCs to specific brain areas, depending on the regulatory pathways active during neurodevelopment .Research performed using NSCs and NPCs has helped to extend the understanding of SZ, so that it is no longer seen as a “synaptic disease”  but rathDISC1 interruption by a balanced Chr translocation was associated with SZ in a Scottish family . The mutThus, the NPC model may link mutations to abnormal brain development in schizophrenia.The glutamate hypothesis explains SZ as a lack of glutamate signalling, mainly via NMDA glutamate receptors. The administration of NMDA receptor non-competitive inhibitors reproduces both positive and negative symptoms of SZ . GlutamaA pathogenic SNP—a 4bp-deletion frameshift in DISC1—is known to be associated with SZ and other mental disorders . The mutMicroRNA profiling of glutamatergic neurons with 22q11.2 microdeletions, particularly the deletion of DiGeorge syndrome critical region 8 DGCR8, resulted in the dysregulation of a set of miRNAs that control the expression of genes involved in neurotransmitter function, synaptogenesis and neuronal differentiation .A study of the heterozygous 22q11.2 deletion showed abnormal expression of genes involved in apoptosis, mitogen-activated protein kinase MAPK signalling and cell cycle. At the network level, 22q11.2 genes and their co-expressed targets likely play two distinct roles during brain development, with a CDC45-mediated cell cycle pathway involved in embryonic brain development and a PRODH-modulated subnetwork contributing to adolescent brain functions. A possible spatial interaction between the 22q11.2 regions and the human leukocyte antigen 6p21 locus was predicted .Cell type-specific differences in the number of splice variants were identified in the patient’s iPSC-derived glutamatergic neurons and oligodendrocytes with the heterozygous deletion of CNTNAP2. Cells from the proband were compared to those from the unaffected parent with the same mutation. This work demonstrates the level of complexity involved when a genetic variation shows incomplete penetrance, probably due to interactions with an individual’s protective and risk-bearing alleles .Neurons also appear to be indispensable for studying variations in response to pharmacological treatment. This could lead to an understanding of treatment-resistant SZ. A gene expression study of iPSC-derived cortical excitatory glutamatergic neurons of monozygotic twins with clozapine-responsive and -resistant SZ revealed that the cell adhesion genes were expressed differently upon treatment. Proteins of these genes, including protocadherins  and cadherins (CDH8 (an ASD-risk gene) and DSC3), participate in synapse formation. Further research may shed light on the reasons for treatment-resistant SZ . SpecifiThe hypothesis of dopaminergic system dysfunction is central to SZ and has been one of the most enduring ways of conceptualizing the illness . This hyiPSC-derived DAergic neurons help to elucidate potential molecular mechanisms linking genetic variants of SZ patients with DAergic neuronal dysfunction. In patients with schizophrenia, Kushima et al. found a rare CNV in the gene of reelin (RELN) that controls neuronal migration in the developing brain . RELN muGWAS studies found that copy number variation at 16p11.2 is strongly associated with SZ . To elucThese data support the contention that DAergic neurons derived from CRISPR/Cas9-engineered iPSC have both constructive and predictive validity. They could serve as a valuable model of SZ to investigate the pathogenesis of DAergic system-linked GWAS-identified genetic variants.Ketamine administration results in acute psychosis, which is accepted as a behavioural model of psychosis in SZ. Since ketamine is an NMDA antagonist, insufficient NMDA receptor input on GABAergic neurons is involved . GeneticMedium spiny neurons, located in basal ganglia, form another subpopulation of GABAergic interneurons. Medium spiny neurons contain D1-/D2- receptors. Recently, a protocol for the differentiation of iPSCs into medium spiny neurons was established . Though The role of glial cells in SZ pathogenesis was mentioned previously. Oligodendrocytes produce myelin, which wraps neuronal axons. A wide range of ultrastructural changes observed in post-mortem oligodendrocytes appeared to be associated with cellular stress, reduced protein and ATP synthesis .iPSCs from SZ patients show a two-time fold reduction in the differentiation rate of O4-positive oligodendrocytes . StudiesInterestingly, typical antipsychotics  are shown to stimulate the proliferation of OLs but inhibit maturation. Atypical antipsychotics  have the opposite effect. This may explain the better activity of the atypicals against negative symptoms . The potPatient-specific induced neurons could be obtained directly from fibroblasts by the overexpression of several transcription factors (at least three) together with the addition of miRNA . This apNon-neural cells such as HEK293 are also useful for the investigation of particular genes and proteins linked to SZ. The mutant isoform Kv11.1-3.1 of the primate-specific brain voltage-gated potassium channel lacks a channel-stabilizing Per-Ant-Sim (PAS) domain. This isoform displays abnormal folding and traffic to the plasma membrane and could be responsible for the extended train of action potential in the neurons of patients with SZ. The HEK293 line was used to develop a thallium flux assay to screen drugs that could restore Kv11.1-3.1 function. Proteasome inhibitors restored the traffic of the Kv11.1-3.1 isoform .DPYSL2 is also of interest. It encodes collapsin response mediator protein 2 (CRMP2), which is highly expressed in the central nervous system. CRMP2 is a synaptic protein that controls synaptic transmission via interaction with receptors and channels . SNPs inThese results suggest that HEK293 possesses predictive validity at the biochemical level while being constructively unrelated to neural cells.The pathologies of cortical development in SZ can be investigated in multicellular models, including neural rosettes, neurospheres and brain organoids. Neurospheres and neural rosettes, considered intermediates between iPSCs/NSCs and neurons, also contain valuable information about events in early ontogenesis.Rosettes possess a basal–apical polarity, nuclear interkinetic motion during mitosis and a lumen. The formation of neural rosettes reproduces events that take place during secondary neurulation in vivo. Rosette polarity and connectivity  can be studied in SZ cases compared to controls. Defects in complement signalling are known to be associated with SZ. The study of the role of the complement protein C5a and its receptor C5aR1 in neural rosettes has shown that C5a stimulates rosette formation through the PKCζ pathway. iPSC-derived neural rosettes from SZ patients displayed perturbed apical–basal polarity and disrupted adherens junctions relative to controls .Reynolds and Weiss, in their pioneering work, discovered that isolated NSCs could form floating spherical cultures that they termed “neurospheres”. Neurospheres could also be obtained from iPSCs . The appNeurospheres are a good model in which to study the molecular mechanisms of neurodevelopmental abnormalities. Neurospheres from patients with 22q.12 showed reduced size, neural differentiation efficiency, neurite outgrowth and cellular migration distances compared with healthy controls . MoreoveCo-cultures help in the investigation of pathogenic mechanisms of intercellular relationships. iPSC-derived glutamatergic pyramidal cortex neurons and GABAergic interneurons from patients with SZ and healthy controls were studied in co-cultures. Comparison of combinations of excitatory and inhibitory neurons showed that an inherent deficiency in inhibitory interneurons underlaid the decrease in synapse formation in patients with SZ compared with controls . IncreasSince glial cells are critical players in synaptic plasticity in the brain, co-cultures of neurons and glia have deepened our understanding of pathogenic intercellular interactions in SZ.Organoids are 3D models that reproduce the architecture of brain tissue. They can be used to reproduce the structural changes found in the brains of individuals with SZ. Organoids are derived from iPSCs that are differentiated into neuroepithelium. Most protocols require prolonged incubations in bioreactors with agitation. The stepwise process requires media containing different growth factors and small molecules at each step. However, organoid formation is only partially guided by growth factors. The main factor is self-organization which is controlled by intrinsic stimuli. Recently, methods to grow region-specific organoids—forebrain, midbrain and hypothalamic—have been established. The transcription of genes in human brain organoids at different growth times correlates with their transcription in embryos between 8 and 16 weeks after conception. Brain organoid epigenetics (CpG and non-CpG methylation) strongly correlate with the foetal pattern, and the stages of organoid growth and differentiation are comparable to those in the foetal brain. Since most of the SZ-associated genetic variants lie in non-coding regulatory regions , the preThe advantage of organoids is revealed in studying the impact of the FGFR1 signalling network on cortical development during ontogenesis. The consequences of FGFR1 encoding on receptor tyrosine kinase misregulation were studied in idiopathic organoids derived from patients with SZ. The FGFR1 misregulation led to abnormal migration of the Ki67+ NPCs. They scattered from the ventricle zone into the intermediate and cortical zones. The number of TBR1 pioneer neurons and RELN was significantly decreased. Neurons were depleted from the cortex and formed in subcortical regions instead. Experiments with normal organoids overexpressing the dominant-negative or constitutively active mutant FGFR1 or downregulating it with a synthetic inhibitor, PD173074, reproduced the observations made with the SZ organoids. Since the FGFR1 signalling network affects the expression of 84.4% of SZ-associated genes, it would be hard to estimate the physiological effect of FGFR1 misregulation without the constructive validity of the brain organoids .Brain organoids also helped to partially explain the molecular mechanism of SZ pathogenesis associated with the 16p13.11 chromosomal microduplication. This locus contains the gene NDE1 (nuclear distribution protein nudE) and miR-484. Brain organoids from three patients with SZ and five healthy controls, all having the same microduplication, were grown. The SZ organoids showed a markedly reduced number of proliferation zones and asymmetric cell division in those zones. Proliferating cells produced one NPC and one differentiated neuron instead of two NPCs. The inhibition of the NFkB-p65 pathway was the cause of the abnormal proliferation. Stimulating the NFkB pathway with the small-molecule activators SRI-22772 and SRI-22782 or the overexpression of p65 corrected the cell proliferation . These dDISC1 dysfunction, which has been studied extensively, was also recapitulated in organoids. Electroporation of brain organoids with a dominant-negative GFP-DISC1 765-835 form blocks the interaction of NdeI/NdelI with the wild-type DISC1. Since NdeI/NdelI interacts with kinetochore, its impaired interaction with DISC1 leads to a delay in mitosis in radial glial cells. The number of Ki67+ cells in the ventricular zone is significantly reduced compared to cells in the G0 phase. The observed phenotype reproduces the phenotype of organoids from patients with SZ carrying the DISC1 d598-854 deletion or frameshift mutation I808 .While only a few SZ studies have used brain organoids, much work has been done on other mental disorders, including ASDs and bipolar disorder (BD). In some cases, ASD- and BD-associated mechanisms can be translated to SZ. For example, transcriptome analysis of autologous organoids from patients with ASDs shows overexpression of the FOXG-1 transcription factor. This explains the elevated ratio of GABAergic inhibitory neurons to excitatory glutamatergic neurons. At the same time, the populations of Ki67+ proliferating cells were not significantly changed. The RNA interference of FOXG-1 abrogates the overproduction of GABAergic neurons and restores the balance between the number of inhibitory and excitatory neurons . FOXG-1 The chromodomain-helicase-DNA-binding protein 8 (CHD8) represents another protein that is associated with the pathogenesis of ASDs and SZ . To studMolecular mechanisms underpinning the abnormal brain vascularization observed in patients with SZ could be recapitulated in vascularized organoids . VasculaGWAS-guided investigation of in vitro models will advance our knowledge of the pathogenic molecular mechanisms of SZ. There are relatively few genetically engineered models of SZ, considered in comparison with those available for other common polygenic diseases. Post-GWAS in vitro studies of SZ represent a promising way to dissect the functional roles of disease-associated genetic variations. A wide range of processes in the brain could be reproduced and studied using cellular models . The cho


Several studies on micro-expression recognition have contributed mainly to accuracy improvement. However, the computational complexity receives lesser attention comparatively and therefore increases the cost of micro-expression recognition for real-time application. In addition, majority of the existing approaches required at least two frames  to compute features of every sample. This paper puts forward new facial graph features based on 68-point landmarks using Facial Action Coding System (FACS). The proposed feature extraction technique (FACS-based graph features) utilizes facial landmark points to compute graph for different Action Units (AUs), where the measured distance and gradient of every segment within an AU graph is presented as feature. Moreover, the proposed technique processes ME recognition based on single input frame sample. Results indicate that the proposed FACS-baed graph features achieve up to 87.33% of recognition accuracy with F1-score of 0.87 using leave one subject out cross-validation on SAMM datasets. Besides, the proposed technique computes features at the speed of 2 ms per sample on Xeon Processor E5-2650 machine. Micro-expression (ME) is described as a brief facial expression which appears on a person’s face according to the emotions being observed. ME occurs when people deliberately try to conceal their emotions, or unconsciously repress their emotions . ME becoME contains significant amount of information about the actual emotions of a person. These emotions maybe useful for applications including healthcare, security and interrogations . HoweverReliability of accuracy—A real-time ME system needs to be able to reliably spot micro-emotions from a person face. Existing ME techniques are however limited to certain datasets which curtails its reliability in multifarious settings.Computational performance—Given that MEs usually last for a very short duration, it is imperative for a ME system to be able to process and classify a person’s emotion in real-time. Although existing approaches in ME recognition emphasizes on accuracy, the computational complexities of these approaches are not readily applicable for a real-time system.Automatic onset-offset frames detection—Current state-of-the-art approaches in ME with high accuracies actually requires pre-defined spotting of the onset and offset frames. These constrain are not viable in real-time environment whereby the onset or offset frames cannot be pre-determined.In spite of these constrain, ME continues to attract the attention of researchers in the computer vision domain due to its vast potentials in security and interrogations, healthcare, and automatic recognition for real-time applications. In fact, current state-of-the-art methods are able to spot micro-level emotions with accuracies ranging between 65% and 80%. This in turn increases the viability of current ME techniques for real-world implementation. However, for ME system to perform in a real-time system, the following challenges need to be addressed:Generally, the process of recognising micro facial expression is divided into three parts, namely pre-processing, feature extraction and classification. Each part here plays an important role towards reliably classifying a person’s emotion. However, for automatic ME recognition, the features extracted should be more descriptive due to the subtleness of facial movement. Currently, the common feature extraction methods used for automatic ME recognition are Local Binary Pattern histogram from Three Orthogonal Planes (LBP-TOP) , HistogrX, Y and T represent the width, height and number of frames in a video stream, respectively [LBP-TOP represents a popular feature extraction method which considers the co-occurrences statistics in three directions  of a video sequence. Here, ectively . Howeverognition ,8 with GFor the HOG feature extraction approach, the number of occurrences of gradient orientation in localized portions of an image  is counted. The study in Reference  implemenOn the other hand, Reference  proposedAlthough the aforementioned methods demonstrate notable improvements in ME accuracy, the high computational cost and requirements for pre-defined spotting of onset and offset frames renders these methods impractical as a real-time solution. Looking into macro-expression detection and recognition, References ,17,18 suFACS-based graph features using facial landmarks is proposed for real-time ME recognition. The proposed technique addresses both the accuracy and computational cost for real-time ME systems. The proposed technique computes features for ME recognition based on single-frame sample only, which substantially increases its feasibility of ME recognition with high speed camera.Implementation of large-sample validation technique for single-frame geometric based features. Thus, multiple frames were selected from each video sequence and represented as samples of every corresponding class, which in turn increases the total number of samples of every class per dataset.The main contributions of this paper are:The rest of the paper is organized as follows: Comprehensive review on automatic ME recognition and analysis challenges have recently been presented in Reference , focusinHence, an acceleration of feature extraction has become necessary for real-time ME recognition in order to attain high throughput. In addition, from the feature perspective for ME recognition, there are three major approaches, namely—appearance-based approach, dynamic approach and geometry-based approach. Based on reported results in Reference , both apA to strongest E intensity. The main benefit of estimating AU strengths is that the qualified AUs would yield more information about the emotional involvement of a subject. Moreover, since humans can express their feelings in different ways under different situations, information conveyed by AU intensities can be exploited to adapt emotion recognition. Geometry-based feature extraction approach deals with symmetrical features that gives the locations and shapes of facial components . The stuTo date, the achievement of ME recognition accuracy using spontaneous ME datasets ranges from 40% to 88% using different validation approaches including leave one subject out cross validation, leave one video out cross validation and k-fold cross validation. For methods tested using all classes, the highest accuracy is 88.28% with F1-score of 0.87 with OFF-ApexNet method from Reference  over CASWhile the aforementioned studies lay a solid groundwork in ME recognition accuracy, the computation performance based on speed per frame remains unreported. Moreover, with the current advancement of technology for real-time machine learning based systems for automatic ME recognition, it is necessary to have a reliable feature extraction algorithm for real-time implementation of ME recognition systems. Looking into the FACS-based features, where a trained coder views facial geometric movements and expressions in video sequences, and then observe each muscle movements as AU. FACS is described as efficient, objective and comprehensive technique to present facial expression without any downside , and it This section presents the proposed facial feature extraction algorithms for ME recognition. The real-time system utilizes a high speed camera to capture video frames, then Facial Detection algorithm is applied to identify the presence of face for micro-emotion analysis within the processing frame. For every successful detected face, 68 landmark points will be identified for the subject’s facial components. Subsequently, the proposed technique utilizes these landmark points to compute FACS-based graph for different emotions, and then the distance and gradient of segments from the computed graphs are presented as features. These features are normalized and then presented to the Classifier for ME detection and recognition.The authors of Reference  demonstrn represents the index for the x and y coordinates of a landmark point. Then, k represents the number of computed elements. As shown in Algorithm 1, two feature elements are computed from every segment, where the first element is the distance between the two points computed using Euclidean algorithm and the second element is the gradient of the two points computed using slope equation. Thus, the total number of feature elements computed from the 2278 segments is 4556.Algorithm 1: Feature computation with full-face graph.Algorithm 1 presents the first method, that is, feature computation using the Full-face facial graph. This algorithm computes a total of 2278 one-to-all segments generated from the 68-points facial landmarks for every sample . Here, R represents the number of AUs for per emotion. While, Equation  expr expr3) eEquation  combinesEquation  to generEquation  to form Equation  deletes Equation , the newAlgorithm 2: Feature computation with FACS-based graph.Algorithm 2 describes how the features are computed using the FACS-based graph. Similarly, Algorithm 2 computes two feature elements for every segment, and this process is repeated for all the segments of the FACS-based graph to compute the complete 2356  features.As observed here, the total features computed with Algorithm 2 are lesser in comparison with the features computed in Algorithm 1. Note that the features are computed in the same manner in methods after the graph formation using Equation  as desc. To furtAs shown To further describe the FACS-based graphs for each emotion, To further justify our motive of the proposed single frame-based analysis for fast computation and better accuracy, this paper analyzes the performance of the single frame-based approach under three different setups. For each setup, set(s) of samples are extracted using the corresponding Equation from  to 7). . 7). MorIn this section, the experimental setups using four available spontaneous datasets are presented. These datasets are: Spontaneous Micro-Expression dataset (SMIC), Chinese Academy of Sciences Micro-Expression (CASMEII), Spontaneous Actions and Micro-Movements (SAMM) and A Dataset of Spontaneous Macro-Expressions and Micro-Expressions (CAS(ME)The SMIC dataset is spontaneous with 20 participants  collected using high speed (HS) camera set to 100 fps with resolution of 640 × 480 and normal visual camera (VIS) and near-infrared (NIR) set to 25 fps with resolution of 640 × 480 as well . The accCASMEII dataset is an improved version of CASME dataset . CASMEIIThe SAMM dataset is collected using a high speed camera with 200 fps with resolution of 2040 × 1088. SAMM dataset was designed in such was that each video stimuli was tailored to each participant, rather than getting self-reports after the experiment. This allowed for particular videos to be chosen and shown to participants for optimal inducement potential . This dapression .CAS(ME)The reasons of using these datasets for experiments are; first, the datasets are classified as spontaneous, which indicates that the emotions captured from the participants are genuine, then secondly, to compare the performance of the proposed feature extraction technique of FACS-coded datasets  with non-FACS-coded datasets As mentioned in This experiment selects only the mid-frame and present it as the only input frame from each video, this process is expressed in Equation . As suggIn this experiment, the frame-based datasets used for analysis are generated from mid-three frames of each video sequence using Equation . Figure This experiment generates frame-based datasets with the mid-half frames from each video sequence using Equation . Figure The number of samples generated by using Equations –7) from from7) fTo evaluate the proposed feature extraction algorithm tested on the single frame-based samples generated in this work, accuracy and F1-score are measured for four different datasets As shown in From these results, Experiment I outperformed Experiment II and III using the proposed FACS-based graph features analysis on SAMM with the highest accuracy and F1-score of 87.48% and 0.87, respectively. Similarly, Experiment I outperformed Experiment II and III using the Full-face graph features analysis on SAMM with the highest accuracy and F1-score of 80.28% and 0.80, respectively. As observed here, Experiment I achieved the highest accuracy due to two reasons; firstly, the size of samples per subject for each dataset is smaller and secondly, the selected frame  is more precise in comparison with other datasets To further evaluate the performance of the proposed graph algorithm, To sum up, the results presented in eference  on CASMEIn addition to the accuracy and F1-score, the computational time of the proposed feature extraction algorithm was investigated. The processing time of the proposed algorithm is analyzed on Xeon Processor E5-2650 v4 @ 2.4Ghz with 24 logical processors. The computation time taken to extract the features using one-to-all is approximately 3.1 ms. For the proposed feature extraction algorithm based on FACS, it takes approximately 2 ms to compute features per sample. Based on this analysis, the computational performance of the proposed feature extraction algorithm using either one-to-all or FACS-based significantly reduced the processing time of feature computation. This suggests that the proposed feature extraction algorithm is potential for real-time ME recognition with high speed camera integrated with fast facial landmark detection and accelerated SVM classification.While acknowledging the differences in computing resources may have potentially contributed to the superiority of our method in computation time, the benchmark algorithms require several pre-process stages including face detection from the original raw video sequence, face alignment, face cropping and onset-offset detection. These pre-processings introduce more challenges of computational time, which limits the performance of the accelerated feature extraction. In addition, these challenges have not been addressed by any research so far, which makes these algorithms more crucial for real-life applications.On the other hand, in the proposed method, the computed features using all landmark points requires 3.1 ms. In addition, the computed features by using selected landmark points based on FACS requires 2 ms. On the contrary, based on the benchmark studies, the proposed algorithms requires facial landmark detection as the only pre-processing stage. Then, by using the facial landmark points obtained from the processing stage, as described in Thus, in comparison to the benchmark studies, the proposed FACS-based graph features achieve well above the required speed of 200 fps for real-time ME recognition, leaving 1.2 ms to compute the facial landmark detection and classification, while 0.8 ms to compute the face detection and classification for Full-face graph features. However, the performance of the proposed method is limited due to two major reasons, namely; (i) the definition of AUs are based on the FACS system presented in Reference , which iThis paper presents the a fast feature extraction algorithm using facial landmark points for ME recognition in real-time. The proposed algorithm measures the geometric changes through the facial muscles to recognize micro emotions using 68 facial landmark points. The 68 landmark points are segmented based on all points for full face analysis or selected points based on FACS. This algorithm is analyzed using frame-based sample generated from the four spontaneous datasets using three different approaches . In the experiment, all generated frame-based samples from the video sequences are presented as as input frames for feature computation using the proposed algorithm. Results suggest that the best accuracy and F1-score achieved are 87.33% and 0.87 over the SAMM dataset using FACS-based graph features with only the mid-frame sampling approach. Furthermore, the proposed feature extraction algorithm based on FACS graph exhibits the best computational performance of 2 ms per sample. Therefore, this suggests that the presented feature extraction method outperformed the current state-of-the-art over SMIC, CAS(ME)The accuracy of the proposed method could be further improved by implementing geometric-based emotion magnification using the facial landmark points prior to computing the features. The magnification of subtle movements of facial components will enhance the visibility of micro-emotions and yield up to 90.0% and above of recognition accuracy, as reported in Reference  on macro


Enterobacter ludwigii outbreak.To describe the course and intervention of an hospital-wide IMI-Producing This was an outbreak interventional study, done at a tertiary care center in Tel-Aviv, Israel. Data was collected on the course of the outbreak and the demographic and clinical characteristics of all patients involved in the outbreak. The intervention measures included patients’ cohorting, contact isolation precautions, environmental cleaning and screening of contacts. The molecular features and phylogeny of outbreak-related isolates were studied by whole-genome based analysis.E. ludwigii and were identified in 24 wards throughout the hospital. Colonization was identified in the first 72 h of admission in 13/34 patients (38.2%). Most patients (91.2%) were admitted from home and had relatively low level of comorbidities. The majority of them (88%) had no recent use of invasive catheters and none had previous carriage of other multi-drug resistant bacteria. All available isolates harbored the blaIMI-17 allele and belonged to Sequence-Type 385. With the exception of two isolates, all isolates were closely related with less than a 20-SNP difference between them.The outbreak included 34 patients that were colonized by IMI-Producing E. ludwigii and the possible role of environmental sources in its dissemination.This outbreak had most likely originated in the community and subsequently disseminated inside our institution. More studies are required in order to elucidate the epidemiology of IMI-Producing  Klebsiella pneumoniae [Enterobacter cloacae [. In addition to KPC, several studies described outbreaks that were caused by VIM-producing E. cloacae [. In other countries, carbapenemase-producing E. cloacae is the third most common CPE species (following K. pneumoniae and Escherichia coli) [K. pneumoniae [Since the beginning of the millennium, carbapenemase-producing Enterobacterales (CPE) have become a major problem in health-care systems worldwide. In Israel, a nationwide outbreak of CPE emerged in 2006, consisting primarily of nosocomial spread of KPC-producing eumoniae . Even pr cloacae , 4. In oia coli)  or even E. cloacae complex (ECC) species may produce a species-unique carbapenemase named IMI. This type-A enzyme is mostly located on the bacterial chromosome, and has been reported, albeit rarely, from around the globe [In addition to common carbapenemase enzymes such as KPC or VIM that can be found in many different Enterobacterales species, the he globe . In Israhe globe  but thishe globe . In JuneThe Tel-Aviv Sourasky Medical Center (TASMC) is a 1,400-bed, tertiary care center in Tel-Aviv, Israel. The policies for the selection of patients for CPE screening by rectal surveillance cultures were determined according to instructions of the Israeli Ministry of Health . BrieflyAll patients with a positive sample of IMI-producing ECC between 01/01/2018 and 30/09/2019 were included. Data was collected from the computerized patient’s files and included: 1) demographic data; 2) previous use of healthcare services or medications; 3) baseline medical conditions, including the Activities of Daily Living (ADL) score and the Charlson Clinical Score (CCS). The study was approved by the institutional Ethics Committee. The isolation of isolate following 72 h of admission was defined as 'hospital acquisition' and 'healthcare exposure' was defined as either inpatient admission with 6 month or Surgery within 30 days.blaKPC, blaNDM, blaOXA-48 and blaVIM using an in-house assays [blaIMI was also performed routinely on all suspicious colonies using the following primers: IMIF-CCATATCACCTAATGACATTCC; IMIR-GCAAATGAACGATTTCCATTATGTA. In addition, carbapenemase activity was tested by the the β-CARBA test . Species determination was done by the VITEK-MS® MALDI-ToF system . Antimicrobial susceptibility testing was done by the VITEK-2 system .Surveillance for CPE colonization was done by rectal swabs. Swabs were inoculated onto the CHROMAgar™ and mSuperCARBA™ media  and incubated for 16–18 h at 37ºC. The analysis of suspicious colonies grown on the media was done at the Laboratory of Molecular Epidemiology and Antimicrobial Resistance according to instructions of the Israeli Ministry of Health [e assays . PCR forE. cloacae EcWSU1 NC_016514) and annotated using the Microbial Genomic Module of the CLC Workbench software. Molecular species identification was done by comparison of the dnaJ sequences using the BIBI database [https://pubmlst.org/ecloacae/) [blaIMI allele was determined by WGS.Whole genome sequencing (WGS) was done using the Illumina MiSeq system. Libraries were prepared using Nextera DNA Flex Library Prep Kit  along with Nextera DNA UD Indexes  were used to tagment the DNA libraries for sequencing. The library was normalized to 4nMol and sequenced on the Illumina MiSeq platform, using Illumina MiSeq reagent kit v2 300 cycles (2X150 bp), according to the manufacturer’s instructions. After sequencing of each library, FASTAQ files were imported into CLC Genomics Workbench version 12.0.3  included raw reads firstly trimmed based on read quality and to remove adapters, and the reads were de novo assembled into contigs. Illumina reads were mapped to a reference genome (database . PhylogeE. ludwigii (IMI-El) carriers between 6–9 of June 2019. Two patients were from the same ward, and were screened as following the detection of a positive KPC-producing K. pneumoniae case in the same ward. The other five patients were from different wards, and were detected incidentally on routine screening.From January 2018 until June 2019, only a single IMI-El carrier was detected (06.30.2018). The outbreak was noticed following the detection of seven IMI-producing The abrupt onset of the isolation of IMI-El in unrelated patients had led to the assumption of a pseudo-outbreak, possibly due to laboratory contamination. Therefore, patients were not transferred to the CPE cohort ward and were kept under contact isolation.2O2 gas and the lab was thoroughly cleansed. However, as additional new IMI-El carriers continued to be identified the outbreak was deemed to be real.Repeat testing of the original isolates using new reagents confirmed the initial identification of IMI-El in all samples, as was repeat culturing of several positive swabs. Repeat sampling of the seven initial IMI-El carriers was first negative, but one carrier was later tested positive. All of the laboratory bio-safety cabinets were disinfected using HOverall, 17 new cases were detected in June, eight in July and in August and one in September 2019 . All IMI-El cases were detected in surveillance culture without clinical infections, and were identified in 24 different wards with small clusters of 2–3 patients per ward. The largest cluster occurred in Surgical Unit C, where four patients were identified  and 17/34 (50%) were females. The majority of patients were admitted from home (91.2%), mostly via the Emergency Department (79.4%) to different medical and surgical wards (Table E. ludwigii (a member of the ECC) with an average nucleotide identity (ANI) of 99.9% followed by E. cloacae with an ANI of 96%. The isolates were resistant to ceftriaxone, piperacillin-tazobactam, ertapenem and meropenem but were tested negative for carbapenemase activity by the β-CARBA test. The isolates were susceptible to ceftazidime, ciprofloxacin, amikacin, gentamicin, nitrofurantoin and trimethoprim-sulfamethoxazole. The isolates harbored the blaIMI-17 allele and belonged to ST-385. The five unrelated isolates were all identified as E. cloacae with an ANI of 100% followed by E. ludwigii with an ANI of 95.8%. The isolates harbored the blaIMI-12 allele (four isolates) or the blaIMI-16 allele (one isolate). Two isolates belonged to the newly assigned ST-1335 and the rest were of unrelated ST’s .The analysis included 27 isolates that were available out of the 34 outbreak’s cases. We also included five unrelated IMI-producing ECC isolated that were previously identified in TASMC. The outbreak-related isolates were all identified as The results of the phylogenetic analysis of the ST-385 outbreak-related isolates is presented in Fig. Very little is known about the epidemiology of IMI-producing ECC. Most published studies are mainly isolated case reports , 16 or mE. ludwigii, we were not able to discern the origin of the outbreak or to track its dissemination via the WGS-based analysis. However, the high level of similarity (< 20 SNP’s difference) that was observed between most of the strains suggest that the outbreak originated from a single source and had disseminated within a short time frame.An integral part of outbreak investigation is the detection of its initial source, whether inside or outside the healthcare facility. Typically, the origin is deemed as community-acquired when the infection is detected within 48–72 h of admission. Such distinction is more problematic in case of colonization only, since it is determined by the timing of testing rather than the onset of clinical symptoms. The source of the outbreak described in this article is puzzling from many perspectives. Although colonization was detected in most of the patients after more than three days, suggesting hospital-related acquisition, in substantial number of patients  it was detected prior to that, including during the first day of admission. Second, the cases were identified throughout the hospital with no connecting link between most of them. Third, detection of carriage was transient in many of the patients. Fourth, similar outbreaks were not reported from outside of our institution during that time period. Lastly, although the molecular analysis had confirmed that all isolates belonged to a single sequence type of What can therefore be the epidemiological explanation for this outbreak? Our initial assumption was that laboratory contamination was responsible, at least in part to a pseudo-outbreak. This hypothesis was disproved for the most part by the lack of evidence for environmental source in the lab and the continued appearance of new cases even after thorough laboratory decontamination. Since neither community or healthcare acquisition alone can account for this outbreak, the explanation is probably a combination of both. Of note, community sources of IMI-producing ECC were identified in one report from Myanmar  and was Additional features that support the hypothesis that community acquisition of IMI-El played a part in this outbreak are the demographic and clinical characteristics of the carriers. The majority of the patients in our study were admitted from home and had relatively low level of comorbidity and high level of functioning. The majority of them had no recent use of invasive catheters and none had previous carriage of other MDR bacteria. This is in contrast with previous reports of patients infected/colonized with KPC- or VIM- producing Enterobacter species , 3, wherIMI-producing ECC poses unique challenges to microbiological laboratories. First, it is not detected by certain selective media as well as other, more common CPE types . Second,blaKPC, blaNDM, blaOXA-48 and blaVIM). Such isolate should be tested by blaIMI-PCR either locally or by a reference laboratory, irrespective of the results of carbapenem-hydrolysis assays.When and how should IMI-producing ECC be sought for, considering the aforementioned methodological challenges? Although this type of CPE is considered rare, our experience demonstrates the potential danger of rapid dissemination of this CPE. Had we lacked the ability to identify it in real time, it’ll have probably spread to the most susceptible populations in our hospital where the risk of clinical infection and mortality would have been much higher . Hence, The main limitation of this study is the fact that we were not able to determine its source. Since the outbreak had subsided by applying routine CPE prevention practices, we believe that regardless of its initial source, its continued dissemination was limited to our institution. Although it included only colonized patients, this outbreak still required significant institutional attention and resources. More studies are required in order to elucidate the epidemiology of IMI-ECC and the possible role of environmental sources in it's dissemination.


Fetal growth restriction (FGR), defined as a fetus failing to reach its genetic growth potential, remains poorly diagnosed antenatally. This study aimed to assess the ability of continuous-wave Doppler ultrasound of the umbilical artery (CWD-UmA) to detect FGR in healthy women with low-risk pregnancies.This prospective longitudinal descriptive cohort study enrolled infants born to low-risk mothers who were screened with CWD-UmA between 28–34 weeks’ gestation; the resistance index (RI) was classified as normal or abnormal. Infants were assessed at 6, 10, 14 weeks, and 6 months postnatally for anthropometric indicators and body composition using the deuterium dilution method to assess fat-free mass (FFM). Neonates in the abnormal RI group were compared with those in the normal RI group, and neonates classified as small-for-gestational age (SGA) were compared with appropriate-for-gestational age (AGA) neonates.Eighty-one term infants were included. Only 6 of 26 infants (23.1%) with an abnormal RI value would have been classified as SGA. The abnormal RI group had significantly reduced mean FFM and FFM-for-age Z-scores at 6, 10, 14 weeks, and 6 months compared with the normal RI group (P<0.015). The SGA group’s FFM did not show this consistent trend when compared to AGA FFM, being significantly different only at 6 months (P = 0.039).The main limitation of the study was the small sample size of the infant follow-up.Abnormal RI obtained from CWD-UmA is able to detect FGR and is considered a useful addition to classifying the neonate only by SGA or AGA at birth. The fg sonars . Postnatg sonars .TM device found abnormal RIs in 11.7%, including absent end diastolic flow indicating end-stage placental insufficiency in 1.5% [Doppler ultrasound of the fetal umbilical artery (UmA) can detect poor placental blood flow (measured by the resistance index—RI) and placental insufficiency, which is the major cause of FGR and stillbirths, with potential persistence of suboptimal growth and development beyond the neonatal period , 7–9. Th in 1.5% . The use in 1.5% . The chith centile) or appropriate-for-gestational age (AGA).This study examined whether a CWD-UmA cut-off determined by perinatal mortality for RI charts  in healtTM International study, which commenced in October 2018 and screened pregnant mothers between 28 and 34 weeks’ gestation in five low-and middle-income countries using the low-cost CWD (UmbiflowTM) device. Mothers with an abnormal CWD-UmA were referred to the local tertiary hospital for conventional ultrasound including pulsed-wave Doppler and obstetric management. Upon confirmation of the abnormal Doppler values, the mother continued with regular follow-ups at the hospital, with appropriate management of the pregnancy, e.g. use of steroids, admission for delivery. If the ultrasound measured a normal RI, the mother continued antenatal care at the local clinic until delivery. The South African sites in the Tshwane District contributed 1426 study participants. Women who were enrolled in the UmbiflowTM International study were approached after delivery at the two clinic sites and at the referral hospital and given a 6-week postnatal follow-up date to assess postnatal development of their infants, with inclusion of term infants only for this current analysis. Mothers were reminded telephonically of their 6-week postnatal appointment.This prospective longitudinal descriptive cohort study enrolled infants with documented abnormal and normal CWD-UmA examinations during pregnancy. Study participants were recruited from the South African site of the World Health Organization (WHO) UmbiflowTM International study were healthy women with low-risk singleton pregnancies  and GA between 28 weeks 0 days and 34 weeks 0 days at the time of UmbiflowTM screening who were expected to give birth in the study hospital or its catchment area. For the South African site, a woman was classified as having a low-risk pregnancy if she met the criteria for Basic Antenatal Care Plus (BANC Plus), which is the national antenatal care guideline based on the WHO recommendations for a positive pregnancy experience. Exclusion criteria included high-risk and multiple pregnancies, women who were not expected to give birth in the catchment area, and those who declined or were unable to give informed consent. Additional exclusion criteria for the infant follow-up were a mother under the age of 18 years or an infant with a severe medical condition or chromosomal or structural abnormality. Written informed consent for this study was obtained from the mothers before study inclusion of their infants.Inclusion criteria for the UmbiflowAs shown in th centile (including absent end diastolic flow) [th centile was used as this determined the best level to prevent perinatal mortality in a high-risk population. All infant assessments were blinded to the CW-UmA results in pregnancy. Other pregnancy and delivery information from the UmbiflowTM International study included maternal age, maternal HIV status, GA assessment, date of delivery, infant sex, and birth anthropometry  as done within the routine health services) and indices . Z-score calculation and classification of SGA and AGA at birth was done according to the INTERGROWTH-21 International Newborn Size Standards charts [th centile of BW-for-GA.Postnatal follow-up study visits were done at six weeks (w), 10w, 14w, and six months (m). The CWD-UmA result during the pregnancy was used to classify the infant into normal and abnormal RI groups, with the latter being an RI ≥75ic flow) . This cuL)-1)/(L*S) [The main study outcomes were the infants’ nutrition-related phenotype (growth and body composition) in the first six months of life using serial anthropometry, converted to age- and sex-normalized Z-scores as per WHO growth standards . No corr1)/(L*S) .Birth characteristics and outcome variables at each time point were assessed for normality with the Shapiro-Wilk test. Continuous variables with a normal distribution were presented as mean ± standard deviation. Continuous variables were compared between the abnormal and normal RI groups and between SGA and AGA groups using the independent t-test with Welch’s approximation, variables with a non-normal distribution were compared using the Mann-Whitney U test. Categorical variables were compared with the Chi-squared test. All statistical analyses were carried out using STATA version 13.1  and a P value <0.05 was considered to be statistically significant.Permissions to conduct the study were obtained through the University of Pretoria Research Ethics Committee (reference no. 283/2019) as well as institutional permissions from the relevant health services.TM International study was 6.9% and 5.3% for the infants born at term. The baseline characteristics of the 81 term infants included in this longitudinal follow-up study are shown in TM International study. The main overall difference was the percentage of abnormal RI infants, which was significantly higher in the infant follow-up study. There was no significant difference in the percentage of SGA/AGA infants between the original cohort and the infant follow-up study. Although the infant follow-up study overall was significantly different in terms of the maternal age, gestational age at birth, and many of the birth anthropometric measures compared to the original cohort, once the infants were classified into the normal/abnormal RI and SGA/AGA groups and then compared there were few significant differences between the studies, viz. the maternal age in the normal RI group and the AGA group and the percentage of abnormal RI infants in the SGA and AGA classifications.The overall prevalence of an abnormal RI in the South African site of the UmbiflowTables Weight-for-length Z-scores (WLZ), body mass index (BMI), and BMI-for-age Z-scores (BMIAZ) were not significantly different at all time points, except for BMIAZ at 6m.When comparing SGA and AGA infants, FFM was lower in the SGA infants throughout , but sigA visual comparison of the FFM over time, combining the RI and SGA/AGA groups, is depicted in This study demonstrated that in low-risk pregnancies an abnormal CWD-UmA RI at 28–34 weeks’ gestation detects FGR and is therefore considered to be useful in addition to measuring neonatal size. The FFM, and the age- and sex-adjusted Z-scores thereof, were significantly lower at all the measured time points until age six months in infants with abnormal RIs, compared to those with normal RIs, indicating continued altered post-natal growth. More importantly, more than three quarters of the infants with abnormal RIs would not have been identified as growth restricted using standard growth charts and the SGA/AGA classification. The results showed that both abnormal CWD-UmA RI and SGA are associated with lower FFM at all time points and lower FFMAZ at 6 months of age compared to the normal CWD-UmA RI and AGA infants, respectively and both methods identify infants who are at risk of altered postnatal growth. Infants falling into both the abnormal RI and SGA groups had the lowest FFM and FFMAZ at 6 months, with this group being most at risk of altered postnatal growth. At all the time points there were no significant differences in FFM between the AbN-RI/AGA and AbN-RI/SGA infants and the N-RI/AGA and N-RI/SGA infants, showing that the SGA/AGA classification alone did not seem to identify possible FGR shown by a reduced FFM. Interestingly, there was also no significant difference between the FFM of the AbN-RI/AGA and N-RI/SGA infants at all time points, showing that the impact in terms of the infant’s FFM postpartum was similar in infants who had either an abnormal CWD-UmA RI in pregnancy or were SGA at birth.Placental insufficiency leads to asymmetric FGR due to redistribution of fetal blood flow and fetal brainsparing, which can eventually lead to stillbirths, the catastrophic end result of severe placental insufficiency . A lowerin utero, as well as the future growth trajectory postnatally, and whether or not the infant has achieved its full genetic growth potential.SGA babies are just small by BW, and although associated with poor outcomes, size alone does not define FGR, which is defined as failure to reach the full genetic growth potential , 7, 22. TM has previously been shown to be a suitable instrument to screen a large number of low-risk pregnant women by low-level health workers, as it is an inexpensive and mobile apparatus that gives immediate results, facilitating prompt referral to next-level obstetric care. This makes it feasible for widespread use in low- and middle-income countries. It has already been established in the identification of fetuses at risk of stillbirth and reduction in perinatal mortality [Umbiflowortality , howeverTM) could reliably identify FGR. Although the risk of fetal compromise is higher in women with pregnancy complications, the absolute number of compromised fetuses is greatest from the LRM group. By measuring the neonate, the errors inherent in calculating the Estimated Fetal Weight were removed, giving the best possible groups for SGA/AGA neonates. Imaging ultrasound only gives a weight estimate and would be even less accurate than neonatal measurements. Study weaknesses include that not all women and infants were followed up, which could lead to bias, and the sample size of the infant follow-up cohort, which was limited by budgetary constraints, and resulted in a low number of SGA infants being included in the cohort, which resulted in a reduced statistical power for some of the analyses, especially for the SGA/AGA classification. Birth anthropometry measurements were done within the routine health services, possibly limiting the accuracy. The difference in mean gestational age at birth of 0.8 weeks in the AbN-RI compared to the N-RI infants may have accounted for some of the differences in anthropometry at birth and in the early postnatal period in this classification. The follow-up study was not an accurate representation of the infants in the original cohort as a significantly higher number of AbN-RI infants were enrolled in the study, which may have caused some bias and limit the generalizability of the findings. However, we consider that the purpose of the study was to compare the outcomes of infants with a N-RI and AbN-RI in a low-risk pregnant population, rather than to accurately reflect the participants in the original cohort.The main strength of this paper is the use of a solid postnatal measurement standard for assessing FGR. This assessment of body composition, including FFM, can only be used in research settings, but the information gained is a major value-add. Another advantage is that LRMs were recruited, thereby targeting a group of pregnant women often ignored within the clinical care setting, where a simple test 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 Dataset(XLSX)Click here for additional data file.


Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes  were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence. Colorectal cancer (CRC) ranks as the third most common type of tumor around the world and accounts for more than 7% of overall cancer-related death in China . DespiteWith the recent developments in bioinformatics, a number of well-designed and effective methods are now available for the comprehensive identification of biomarkers in cancer and the prediction of cancer-related signaling pathways . Among tIn recent years, WGCNA has been widely used to uncover the potential biomarkers associated with clinical parameters in various cancer types . In termIn the current study, WGCNA was constructed based on the GSE17536 dataset containing gene expression profiling results from 177 CRC patients. The specific module associated with the recurrence status of CRC was identified. More importantly, hub genes that play essential roles during CRC recurrence were dug out, and their upstream miRNAs and transcription factors (TFs) were also explored.The mRNA expression profiling dataset GSE17536 of human CRC with patient clinical information was downloaded from Gene Expression Omnibus (GEO) online database . GSE1753R package “WGCNA” was conducted . FirstlyIn this study, two methods were used to identify key modules associated with CRC recurrence. ME are the first principal component of a given module and could be considered as a representative of gene expression profile in a module. Module membership (MM) represents the correlation between genes and ME. Gene significance (GS) refers to the correlation between the genes and clinical data, and the average GS for all the genes in a module was defined as module significance (MS), and the module with the highest absolute MS value was regarded as the module with the most significant association with clinical information. Finally, the dissimilarity of the ME was calculated using the moduleEigengenes function in the R WGCNA package. GS was calculated by linear regression between gene expression and CRC recurrence, and MS related to clinical CRC recurrence was obtained.1 with a strict cut-off of FDR < 0.05 was used to present GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, a “ggplot2” R package was used to perform the first 10 enrichment terms of GO analysis and KEGG pathway analysis. The cutoff criterion of P < 0.05 was considered to be statistically significant.Gene Ontology enrichment analysis has become a widely used method in functional gene annotation. To further investigate the function of differentially expressed genes (DEGs) in the key module, clusterProfiler R package 1 with a 2) was employed to identify protein–protein interactions (PPIs) with a medium confidence interaction score of 0.4 (the turquoise module). In addition, Cytoscape software (3. The Molecular Complex Detection (MCODE) plug-in of Cytoscape tool was used to visualize the significant gene modules in CRC, as default, with degree cut-off = 2, node score cut-off = 0.2, k-core = 2, and max.depth = 100. Furthermore, the criteria for selecting the top four significant modules were set as follows: MCODE scores ≥8 and number of nodes ≥10. In addition, STRING was used to present the co-expression analysis of hub genes.Search Tool for the Retrieval of Interacting Genes   and the genotype-tissue expression (GTEx) projects. In this study, the Kaplan–Meier plotter was used to plot survival analyses of the top module genes, then the GEPIA webserver was used to confirm outcomes of survival analyses. For each gene, cancer patients were divided into two groups according to the median values of mRNA expression. Moreover, TCGA data of CRC were used to validate the mRNA expression of identified hub genes comparing with normal colon tissues. Therefore, we can verify the transcriptional levels of hub genes in CRC tissues. P < 0.01 was considered to be statistically significant.Based on the MCODE analysis, the genes of the top clusters were selected as candidate genes for further analysis. The GEPIA 4 is a we5 was applied to validate the hub genes by immunohistochemistry (IHC). The cBio Cancer Genomics Portal6 version: 2.2.0) is an open-access tool that provides analysis, visualization, and downloading of cancer genomics data sets for multiple tumor types. By using the cBioPortal tool, complex cancer genome profiles can be accessed, and this enables us to compare the genetic variations of the selected hub genes in CRC.The Human Protein Atlas7, a database for exploring microRNA-mRNA interaction maps, was used to predict miRNAs that bind to hub genes based on the screening criteria that CLIP Data ≥1 and expression was present in at least one tumor sample. Then, miRNAs with most intersections in seven databases  were selected. A co-expression network on account of correlation analysis of hub genes and cancer-related miRNAs was constructed by Cytoscape software. Then, the plugin iRegulon of Cytoscape is applied to forecast TF regulation networks.StarBase 7, a dataThe flow diagram of the study design is depicted in P = 9 × 10–5, R2 = 0.29), “WGCNA” package in R was applied to classify the DEGs with similar expression patterns into modules by average linkage clustering. As a result, a total of 19 modules were identified by merging similar modules when the MedissThres was set at 0.25 . The netTo investigate the potential function of the genes in the turquoise module, GO and KEGG pathway analyses were performed. As shown in Using the STRING database and Cytoscape software, a total of 926 DEGs of the turquoise module were mapped into the PPI network, including 926 nodes and 7045 edges. The top four significant clusters within PPI network were selected using MCODE plug-in in Cytoscape software . The functions of each module were further analyzed . PathwayP-value of the mRNA expression levels. To further confirm these results, the protein level of these five hub gene candidates was checked using IHC staining data obtained from The Human Protein Atlas database. Consistent with the GEPIA results, IHC data also showed the dysregulated protein level of these genes in CRC tissues  were identified as potential hub genes. To reduce the scope and further validate these observations, CRC patient survival analysis using Kaplan–Meier plotter was first conducted to unveil the prognostic information of these genes. After the above validation, only genes with significantly deteriorated survival curves were further validated by survival analysis with GEPIA. As shown in  tissues . In summWe next sought to compare the genetic alterations of the selected five hub genes in CRC from cBioPortal. As presented in We next sought to establish the transcriptional regulatory network of hub genes, miRNAs, and TFs by starBase. As revealed in It is generally accepted that CRC recurrence is possibly the most important factor that influences the survival of CRC patients . By perfAs a member of the tissue inhibitor of the metalloproteinase (TIMP) family, metallopeptidase inhibitor 1 (TIMP1) was originally discovered as a serum protein that plays a role in collagenase inhibition and erythroid progenitor cell growth . It has Secreted protein acidic and rich in cysteine-like 1 (SPARCL1) belongs to the SPARC-associated family of matricellular proteins and is frequently found to be decreased in a number of cancer types . Till noBeta-tropomyosin  encodes a thin filament-associated protein which has been proved to play a crucial role in the regulation of muscle contraction . Single-In this study, a regulation network of TFs-miRNAs-hub genes was constructed using StarBase and Cytoscape. We first established the regulatory network of TFs-miRNAs-target genes for the recurrence of CRC, involving 29 TFs, 58 miRNAs, and five hub genes, such as models GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, HSF1-MIR424-TPM2, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. Interestingly, TFs and miRNAs with high connective degrees in regulatory networks have been reported to be closely related to CRC, shown as in Our current study identified a number of five hub genes including TIMP1, SPARCL1, MYL9, TPM2, and CNN1, which may play vital roles during CRC recurrence. Their PPI network and upstream TF and miRNA regulators were also investigated to unveil the underlying mechanism by which these hub genes modulate the progression of CRC recurrence. It is anticipated that targeting these hub genes solely or combined therapy with currently available anti-cancer drugs may be served as an alternative method to benefit patients diagnosed with CRC. In general, this study may pave a novel way for the diagnosis, prognosis, and treatment strategies of the devastating disease.The original contributions presented in the study are included in the article/QD conceived the idea. SL finished the bioinformatics analysis and drafted the manuscript. FZ and GF involved in the data analysis and interpretation. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Mutation-derived neoantigens are now established as attractive targets for cancer immunotherapy. The field of adoptive T cell transfer (ACT) therapy was significantly reshaped by tumor neoantigens and is now moving towards the genetic engineering of T cells with neoantigen-specific T cell receptors (TCRs). Yet, the identification of neoantigen-reactive TCRs remains challenging and the process needs to be adapted to clinical timelines. In addition, the state of recipient T cells for TCR transduction is critical and can affect TCR-ACT efficacy. Here we provide an overview of the main strategies for TCR-engineering, describe the selection and expansion of optimal carrier cells for TCR-ACT and discuss the next-generation methods for rapid identification of relevant TCR candidates for gene transfer therapy. ACT demonstrated promising clinic outcomes in melanoma; with durable responses in 10-20% of patients , 4 and tTo circumvent these issues, the field is moving towards the genetic engineering of T cells to express either chimeric antigen receptors (CARs)  or tumor15 distinct αβ TCRs  can be used for TCR-engineering. AAVs are replication-deficient systems and are not known to induce any side effects, making them ideal candidates from a safety standpoint. AAV-based cancer treatments have not yet been used in the clinic, however multiple strategies have been developed and hold great promise for the future –41. It iin trans   . Over thprotein) . Alterna vectors , 46. All vectors , transcr vectors , 49, meg vectors , 51  of endogenous TCRs or of immune checkpoint such as PD-1  and transduced with a NY-ESO1 TCR   . Despite4426669) –59, CRIST lymphocytes are the most common source of cells used as carrier for gene transfer therapy. Following TCR engineering into recipient cells, TCR-T cells need to be expanded to reach sufficient numbers for ACT. The primary starting material is most often autologous peripheral blood   . Accumul in vivo , while A in vivo , 72. Naï in vivo –76 . Of interest, we developed a novel strategy to improve the detection of neoantigens in TILs, based on the addition of pools of predicted neo-epitopes at the initiation of the TIL culture , OX40, CD137 (4-1BB), CD39 and CD103  can also be exploited for neoantigen identification. IVS with antigen presenting cells (APC) loaded with neoantigen candidates have been extensively used to detect neoantigen reactivity , 107–110Upon their identification, neoantigen-specific T cells can be purified based on pMHC multimer staining or based on the up-regulation of activation markers following specific-activation, such as 4-1BB and OX40 , 112. IsInterrogation of neoantigen-specificity and antitumor-reactivity of candidate TCRs can be assessed following the expression of TCR candidates into recipient cells, a strategy hereafter referred as TCR cloning. Antigen-specificity can be challenged by transducing TCRs into activated PBLs or Jurkat T cells which are then co-cultured with APCs loaded with neoantigens , 121–123Of important note, the reactivity of validated neoantigen-specific TCRs to the wild-type peptide should be evaluated to avoid autoimmunity and thus ensure patient safety. This can done by performing a peptide dose response with APCs , 107. AnAs an alternative to the aforementioned time-consuming strategies , new developments enable the direct identification of tumor-specific TCRs by pre-selecting the most frequent clonotypes from fresh tumor samples  Figure , highligex vivo transcriptomic profiling. We foresee that these signatures will enable the direct identification of relevant TCR pairs from ex vivo tumor, which will considerably facilitate and accelerate the selection of TCR candidates for gene transfer therapy.Instead of direct TCR identification, combined single-cell transcriptomics and TCR sequencing  could beIn this review, we provided an overview of the available therapeutic engineering systems, but also of the optimal carrier cells for TCR gene transfer therapy, and finally we described strategies to identify new TCR candidates. The field is constantly evolving and future advances are likely to reshape the landscape of TCR-ACT. Multiple clinical trials are currently ongoing in different types of cancer  and the All authors contributed to the article and approved the submitted version.This research was supported by the Ludwig Institute for Cancer Research and grant 310030_182384 from the Swiss National Science Foundation (A.H.).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.