Today, vaccinologists have come to understand that the hallmark of any protective immune response is the antigen. However, it is not the whole antigen that dictates the immune response, but rather the various parts comprising the whole that are capable of influencing immunogenicity. Protein-based antigens hold particular importance within this structural approach to understanding immunity because, though different molecules can serve as antigens, only proteins are capable of inducing both cellular and humoral immunity. This fact, coupled with the versatility and customizability of proteins when considering vaccine design applications, makes protein-based vaccines (PBVs) one of today's most promising technologies for artificially inducing immunity. In this review, we follow the development of PBV technologies through time and discuss the antigen-specific receptors that are most critical to any immune response: pattern recognition receptors, B cell receptors, and T cell receptors. Knowledge of these receptors and their ligands has become exceptionally valuable in the field of vaccinology, where today it is possible to make drastic modifications to PBV structure, from primary to quaternary, in order to promote recognition of target epitopes, potentiate vaccine immunogenicity, and prevent antigen-associated complications. Additionally, these modifications have made it possible to control immune responses by modulating stability and targeting PBV to key immune cells. Consequently, careful consideration should be given to protein structure when designing PBVs in the future in order to potentiate PBV efficacy. Physicians have been aware of the effects of vaccination for over a millennium, though they had little understanding of the mechanisms through which immunity was achieved until the early nineteenth century. From the simple and dangerous live-pathogen variolation employed in ancient and medieval times to the recombinant protein and DNA vaccines we use today, vaccine development has followed a path of improving efficacy and safety due to an ever-increasing understanding of these mechanisms. The hallmarks of this understanding have been that an adaptive immune response cannot take place without an antigen and that the most effective antigens tend to be proteins. Ultimately, these two facts have led the field of vaccinology to focus on the research and development of protein-based vaccine (PBVs). As such, we now have a dense literature pool that can be used to recapitulate past and present PBV design concepts and illuminate fundamental structural vaccinology principles in PBV design.Bacterial toxin vaccines were the first PBVs to be developed. They originally consisted of antitoxin isolated from animals inoculated with small quantities of unmodified toxin, but later it was discovered that active immunization could be safely achieved if toxin was either 1) co-administered with a sufficient amount of antitoxin  or 2) treated chemically or thermally prior to vaccine administration (denaturation). Chemically inactivated toxin, dubbed toxoid, would go on to garner widespread celebrity due to its success in World War II and eventually become the primary means for immunization against Diphtheria and Tetanus  . Though Neisseria, Streptococcus, Staphylococcus, Haemophilus, and Pseudomonas generas. Before their discovery, vaccine formulations targeting these pathogens singularly consisted of polysaccharide . Although these polysaccharide vaccines were shown to elicit the production of protective antibodies, they proved to be tremendously ineffective at conferring protection in young and immunocompromised individuals and largely failed to elicit immunological memory  or damage associated molecular patterns (DAMPs) . GeneralE. coli, all expression hosts that are commonly used for recombinant PBV production incorporate glycans on protein surfaces  and stereometrically crowd antigen surface. This can result in masked immunogenicity of and/or immune responses being redirected away from important epitopes contained within PBVs. A perfect example of this phenomenon was reported by Ansari et al. when they observed improved in vitro viral neutralization and in vivo epitope-specific antibody response to glycoprotein 5 (GP5) of the porcine reproductive and respiratory syndrome virus (PRRSV) when key N-linked glycosylation sites were eliminated from the immunodominant, N-terminal ectodomain  through the selection of the expression host . Since Psurfaces . These gsurfaces . In factsurfaces –43, and surfaces –48. In osurfaces . A thorotodomain .in vitro expression of IFNα by peripheral dendritic cells (DCs) while simultaneously abrogating the binding of critical, broadly neutralizing antibodies  or post synthesis by using a number of biochemical techniques (conjugate approach). Mechanistically, fusion of protein-based PRR ligands to PBVs ensures proximity of adjuvant to antigen, thus increasing the likelihood of antigen-adjuvant co-delivery to key immune cells. Ultimately, this approach to adjuvanting is intended to improve immune response profile and intensity while simultaneously minimizing off-target effects . It is itibodies .in vitro  nanoparticles (NPs) and observed improved TLR5 activation in HeLa cells when compared with OVA NPs without adjuvant. However, there was no statistical difference when comparing OVA NPs that were conjugated to flagellin with those that were co-administered. These results indicated that conjugating adjuvant to antigen is a viable means of activating the innate immune system, but failed to implicate an effect of adjuvant proximity to antigen on PRR signaling . Alternain vitro , 60. TogOne example of recombinant fusion of PRR with PBVs are flagellin-fused antigens. These vaccines have intrinsic self-adjuvanting properties through their activation of TLR5 and, if the PBV is able to survive endocytosis, the NLRs NLRC4 and NAIP5 , 62. In in vivo not only varies among species but also results in a mixture of different lipoprotein structures that may have varying immunomodulating properties (Another example of the PBV-PRR fusion approach to vaccination are recombinant and synthetic lipoprotein-based vaccines (LPBVs). These have become a popular research topic due to their ability to self-adjuvant via TLR2/1–6 heterodimers . LPBVs coperties . This properties .E. coli has been observed, illuminating another mode in which choice of expression host can influence antigen composition (16−35) developed by Speiser et al. was able to successfully reach Phase IIa in clinical trials  and the B cell maturation process are used by the adaptive immune system to identify and neutralize linear and conformational epitopes exposed on the surface of antigens. Their activation eventually results in the proliferation of plasma cells and the subsequent secretion of antibodies that are highly specific for their target epitope. This, in turn, confers protection through various mechanisms that eventually result in antigen clearance and further stimulation of both the adaptive and innate immune system . TargetiMany structures can serve as BCR epitopes in PBV designs, though there are some limitations associated with BCR complimentary determining region  binding . To starH) cells  cells , 116. ThH) cells , 118. ThH) cells . ConsequH) cells , 121.A similar embodiment to the conjugate PBV is the chimeric, fusion PBV. By definition, the flagellin and lipoprotein fusion proteins described previously can be considered chimeric PBVs. However, within this context, the term most often refers to immunogens that have been rationally modified with recombinant epitopes. With this approach, instead of chemically attaching epitopes to immunogen surface, genes are recombined such that conformational or linear polypeptide epitopes are inserted within PBV immunodominant regions. These regions should be surface exposed if the intent is to activate a humoral immune response . If epitope insertions can be made within AIRs without negatively influencing protein folding, it ultimately results in B cell responses being redirected away from the previous AIR and toward the introduced epitope. This concept was demonstrated by Gillam et al. when they reported increased antibody titers to recombinantly inserted YSNIGVCK epitope and decreased titers to hepatitis B core antigen (HBcAg) VLP when evaluating a porcine epidemic diarrhea PBV in mice . A maximThe fusion approach to targeting epitopes is most commonly employed using VLPs as scaffolding, a technology which comprises the assemblage of multiple protein copies all containing the same immunodominant regions. In this way, high epitope densities per antigen can be achieved without sacrificing the intrinsic, immunogenic advantages provided by VLP shape, size, and structure . ChimeriRecent strides in vaccine development have been accompanied by increased interest in conjugate and chimeric BCR epitope PBVs. When combined, they present an outstanding opportunity for vaccinologists to generate vaccines that can target nearly all conceivable chemicals, biologicals, and polypeptides. In addition, they provide a means through which epitope densities can be increased on antigen surface such that BCR cross-linking and subsequent T cell-independent activation of B cells becomes more likely. However, the promise of a “vaccine for anything” provided by conjugate and chimeric PBVs has elicited various complications. Of these complications, carrier-induced epitopic suppression (CIES) is the most noteworthy issue. Both conjugate and chimeric PBVs require the use of existing immunogens as carrier proteins in order to elicit an immune response. This, along with the fact that there are a limited number of suitable immunogens available for use in vaccine formulations due to factors such as immunogenicity, toxicity, stability, and accessibility, leads to a situation where a select group of “preferred” immunogens are most often used. CIES refers to a phenomenon that occurs when the same immunogen is used in sequential, independent vaccine administrations targeting different epitopes, resulting in the sequestration, elimination, and/or inhibition of vaccine response to target epitope by pre-existing, immunogen specific antibodies and lymphocytes . As expeThough CIES is likely to always occur to some extent when simply boosting a conjugate or chimeric PBV, prevention of antibody specificity for new vaccines is paramount to the creation of more successful immunizations . It has H cells), destroy infected and malfunctioning cells (cytotoxic T (TC) cells), prevent T cell autoreactivity and terminate T cell activity at the end of an immune response (regulatory T (TReg) cells), provide tissue, effector, central, and virtual antigen memory (memory T (TM) cells), in addition to assuming many other roles  cells, mucosal associated invariant T (MAIT) cells, and gamma delta T (Tγσ) cells)  cells) . At the  pathway , 146. MaThe first step in the T cell activation process is uptake of antigen by cells that express MHC molecules. For the purposes of PBVs, this process is generally orchestrated by specialized APCs, though many other cell types can participate in the event of cellular damage or infection. In fact, the MHC class I pathway can be initiated by any nucleated cell. Alternately, activation of the MHC class II pathway can only be achieved after phagocytosis of antigen by APCs . For thiAntigen localization is one of the major controlling factors behind the type of T cell response initiated by exogenously administered PBVs. MHC class I pathway requires internalization and processing of antigen into short peptide sequences (8–10 amino acids) within the cytoplasm. In contrast, MHC class II pathway requires phagocytosis of antigen by APCs and subsequent lysosomal processing into somewhat longer peptide sequences (15–24 amino acids) . As suchC cells after exposure to extracellular antigen. This cross-presentation (CP) of antigen is key to the initiation of cellular immunity to many cancers, viruses, and exogenously administered PBVs , are unique in their ability to activate Tred PBVs . The majred PBVs –177. PBVred PBVs , 178–180ficiency . One stuepitopes . Anotherstration . When coresponse . For exaresponse . When paresponse , 185. WhAfter cellular processing of antigen, presentation of MHC-peptide complex to TCR can't take place if there are no antigen-derived, T cell epitopes specific for the MHC molecules expressed by the cell, as only MHC-peptide complexes can bind TCRs and activate T cells . For thiH cells via MHC class II pathway (UhTEs) and those that active TC cells via MHC class I pathway (UcTEs). Synthetic UhTEs, such as the Pan DR Epitope (PADRE) peptides, have also been engineered. Their development has typically been based on the fact that properties of residues at certain positions within an epitope are more important for MHC binding than others   and subsequently evaluated in an HLA-DR4 transgenic mouse model. Recall epitope assay indicated that 4 of the 5 epitopes successfully activated T cells and challenge assay results showed early activation of TH cells, elevated interferon and interleukin expression, and prolonged survival rates in vaccinated mice  showed promise as an anaphylactic HPV 16 vaccine when it reduced the tumor burden and improved the survival time of HPV tumor-bearing mice . In anotard DTA) . The epiard DTA) . A computed mice . Other sted mice –206.UTEs provide a rational means of potentiating humoral and/or cytotoxic immunogenicity of both peptide and protein-based vaccines. Their incorporation into PBV designs could also provide a means of overcoming the effects T cell competition when common antigens are used as vaccine . ExperimH, TC, and B cell epitopes of the LMP2 protein (a TAA found in EBV-associated cancers)  . Though cancers) .One of the primary reasons PBVs were explored as an alternative to live attenuated and inactivated vaccines in the past was their improved safety profile. This, however, was before genetic modification of antigen had become feasible. Today, modifications made to antigen structure can influence PBV safety profile both positively and negatively. For example, attempts to improve PBV immunogenicity via the many fusion protein approaches previously described could backfire in the form of adverse events, such as cytokine storm and molecular mimicry (autoimmunity instigated by epitopic similarities between foreign and self-immunogens) , 215. Onin vivo testing in order to insure the best translation from animal to human success. Only in this way can we hope to consistently elucidate the impact of PBV modification and formulation on vaccine safety and performance in humans. It is safe to assume, however, that there will always been some level of uncertainty prior to starting in vivo studies.PBVs must first prove themselves in numerous animal studies before they can be used in humans. Unfortunately, however, immunological and physiological interspecies differences make it unwise to extrapolate pre-clinical results to human studies even when using the most optimal animal model for the PBV being developed –219. OutAs has already been mentioned, conformation and stability play an important role in the immunogenicity of PBVs. This importance, however, goes beyond the ability of APCs to cross-present antigen . RecombiThe development of PBVs targeting antigenically variable pathogens (AVPs) and immune-resistant cancers (ARCs) is complicated by the effects of epitope masking, antigenic drift , antigenic shift , and immunoediting . These events are characterized by mutations within antigenic determinants that make it difficult for an adaptive immune response to hone in on antigen . MultiplFor PBVs targeting influenza, the most common approach is biannual reformulation of multivalent, recombinant hemagglutinin PBV such that the flu strains predicted to have the most impact on public health are targeted . Unfortupost-hoc analysis of the most successful HIV vaccine study conducted to date, which used an RV144 pox virus prime, recombinant HIV-1 gp120 (rgp120) boosts, and had an estimated 31% overall protection rate, supports this conclusion. Within the vaccinated population, the HLA A*02 genotype was a marker for success, with A*02+ individuals showing significantly greater protection than A*02− individuals (54 vs. 3% effective). Other studies have made similar observations (*02+ population when the presence of a lysine at position 169 in the V2 region of rgp120 was factored in (74 vs. 15% effective)  . Since tfective) . UltimatMuch like viruses, cancers are subjected to selective pressures by the immune system. The majority of malignant cells are recognized and eliminated during immunosurveillance via a variety of effector mechanisms. However, these cells are continuously incentivized to alter and/or hide their antigenic determinants in order to survive and proliferate. As a result, malignant cells that survive immunosurveillance and establish tumors frequently express specific, targetable TAAs that have evolved to maximize survival and minimize immunorecognition . This main vitro assembly . In one study evaluating this approach, researchers were able to recombinantly substitute threonine-15 of the MS2 coat protein with a cysteine residue without influencing folding efficiency . Anotherassembly . TogethePlasmodium falciparum erythrocyte membrane protein 1 that can be implicated in malaria pathogenicity) showed significant improvement in antigenicity over free ligand early on in vaccination timeline and similar efficacy in final blood draws when the two PBVs were evaluated in a mouse model , such as p-nitrophenylalanine, within PBV structure has been used to overcome autoimmune tolerance in vaccines against RANKL and TNFα , 251. Inse model . ClearlyModified PBVs present an effective means of overcoming many of the limitations encountered by today's vaccines. First, the addition of PAMP ligands to PBV structure insures that sufficient immune activation signals are co-delivered with vaccine upon administration. PBV modifications of this type have been shown to increase overall vaccine immunogenicity and should reduce the likelihood of initiating immune tolerance. Second, recombinant and/or chemical modification of PBVs with BCR epitopes can modulate humoral immune response to vaccine. Specifically, this type of modification makes it possible to (1) direct antibody specificity toward select epitopes, (2) design cross-reactive vaccines that can neutralize multiple epitopes, and (3) prevent CIES when the subject has previously been exposed to antigen. Third, the recombinant incorporation of TCR epitopes within PBV structure is useful in that it can (1) allow targeting of specific HLA genotypes/MHC phenotypes, (2) influence the type of cellular immune response that's initiated, and (3) overcome the effects of T cell antigenic competition. Finally, modifications can be made to PBV primary structure that influence stability and cellular uptake, both important factors when it comes to the magnitude and type of immune response initiated.Limitations associated with PBVs also exist. These are generally structural in nature and can result in the negative modulation of both safety and efficacy. First, it is possible for modification and/or misfolding of PBV to result in the incorporation of unintended PAMPs and antigenemic determinants, an effect that could lead to issues with immunotoxicity and/or autoimmunity. Second, the extensive structural variability cognate with PBV production processes and the general weakness of animal models as success correlates also makes it difficult and expensive to quantify just how well PBVs will work prior to direct evaluation in their target species. Along these same lines, issues with protein stability and interactions between vaccine species when making modifications to PBV formulations can add an additional confounding element to the design process, as the margins between protective immunity and immune tolerance are often very fine. Lastly, AVPs present an additional challenge when concerning the utility of PBVs due to the difficulty of targeting ever-changing, antigenic determinants.in vivo effects. The results from these studies have shown promise on a case-by-case basis, but thus far we have yet to realize the dream of a silver bullet, modified, PBV vaccination approach that would allow the rational targeting of any epitope in any species with a high response rate and without complications. It is possible that we never will, due to the complexity of the immune system and the sheer number of interacting variables that influence the outcome of each immune response. Ultimately, however, the state of PBV research and the sizeable impact that even case-by-case breakthroughs have on the veterinary and medical worlds more than justify continued research into structural vaccinology and the design of modified PBVs.From prophylactic use aimed at preventing hard-to-treat diseases such as HIV to anaphylactic use aimed at alleviating chronic conditions such as addiction, allergies, and autoimmunity, the utility of PBVs has advanced well-beyond what was previously imagined possible. Here, we have described the mechanisms behind PBV immunogenicity and listed many structural modifications that have been explored in the past as a means of modulating and/or potentiating PBV KS and FG initiated the review. All authors contributed to the writing and revision of the manuscript.FG is employed by Locus Biosciences. TL is employed by GlaxoSmithKline. The remaining 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.


Ventilator-associated tracheobronchitis (VAT) is an infection commonly affecting mechanically ventilated intubated patients. Several studies suggest that VAT is associated with increased duration of mechanical ventilation (MV) and length of intensive care unit (ICU) stay, and a presumptive increase in healthcare costs. Uncertainties remain, however, regarding the cost/benefit balance of VAT treatment. The aim of this narrative review is to discuss the two fundamental and inter-related dilemmas regarding VAT, i.e., (i) how to diagnose VAT? and (ii) should we treat VAT? If yes, should we treat all cases or only selected ones? How should we treat in terms of antibiotic choice, route, treatment duration? Diagnosis of ventilator-associated tracheobronchitis (VAT) remains unclear. Better diagnostic criteria necessary to avoid under/over-diagnosis.Novel molecular biomarkers and lung ultrasound (LUS) may help increase diagnostic sensitivity of VAT. However, further research into these methods is needed.To treat or not to treat: a continuing debate surrounding the uncertainties of the cost/benefit of antibiotic treatment of VAT.Controversial use of nebulized/aerosolized antibiotics for VAT in the face of limited evidence of their efficacy.Could treating VAT reduce ventilator-associated pneumonia (VAP) and its increased risk of mortality, mechanical ventilation (MV) duration and intensive care unit length of stay (ICU-LOS)? A reasonable assumption that still needs further clarification.Ventilator-associated tracheobronchitis (VAT) refers to a lower respiratory infection of intubated mechanically ventilated patients with no radiological infiltrate present . It has Despite the progress, diagnosis of VAT remains challenging and, consequently, treatment decisions remain a challenge as well. While most studies have found VAT itself is not associated with increased mortality ,5,6,8, sThe lack of a clear and widely accepted definition for diagnosis of VAT limits the potential for clinical research and hampers efforts of researchers and clinicians to adequately recommend guidelines for the diagnosis and treatment of VAT. The aim of this review is to discuss the fundamental and inter-related dilemmas—conflicting research and recommendations—surrounding VAT diagnosis and treatment. We will discuss and critique: (i) Diagnostic approaches and possible under- and over-diagnosis of VAT, and (ii) when to treat (and how) versus when not to treat.While our understanding of VAT pathophysiology has deepened significantly over the last two decades, several questions remain unanswered. All the pathogenetic theories agree that colonization of the lower respiratory tract (LRT) is the initial event of ventilator-associated lower respiratory tract infections (VARI). During ICU admission the oropharyngeal cavity primarily and the stomach secondarily, becomes colonized by endogenous flora and exogenous bacteria acquired by the ICU environment  . DisableTwo main diagnostic approaches of VAT exist: a) apart from the local signs (purulent secretions), there must be systemic signs and symptoms (fever and/or leukocytosis) as well as microbiological confirmation  for the diagnosis of VAT and, b) the ‘anatomical’ approach, requiring the presence of local signs (purulent secretions) and microbiologic ‘indication’ of infection . The first approach basically differentiates VAT from VAP only by the absence (VAT) or presence (VAP) of radiological infiltrates ,14,15,17ICU patients are inherently complex, afflicted by multiple pathologies which confound the origin of systemic symptoms, which may lead to an under-diagnosis of VAT. In mechanically ventilated patients, both colonization and VAT will frequently result in positive microbiologic cultures of endotracheal aspirates. The new onset of systemic symptoms, in theory, could be considered an indication that the positive cultures relate to infection. However, the clinical picture is complicated, ICU patients with pre-existing systemic symptoms, such as those due to other sources of infection or a systemic inflammatory response syndrome (SIRS) response, may miss a VAT diagnosis if their systemic symptoms are attributed to other pathology or the positive cultures presumed to be colonization.A 2018 multicenter cohort study analyzed ventilator-associated event (VAE) outcomes and their correlation to ventilator-associated pneumonia (VAP) and VAT diagnosis. This study utilized 2015 updated definitions: possible VAP (PVAP), infectious ventilator-associated complication (IVAC), and ventilator associated condition (VAC) and later compared them to the previous 2013 CDC classifications of VAP and VAT ,25,26. TOver-diagnosis and antibiotic treatment of VAT also presents its own issues, specifically in regard to increased adverse effects of treatment, along with selection pressure for microbiological resistance. In a post-hoc analysis from a prospective, observational trial on ICUs in the United States it was shown that 60% of patient diagnosed with SIRS were still treated with antibiotics . This anThe above diagnostic challenges highlight the need for adjunct and/or improved investigations, such as biomarkers or those which detect or exclude new or progressive lung infiltrates more accurately than CXR.p < 0.001) and the median PCT was elevated more significantly in VAP than VAT  [A prospective study evaluated the use of biomarkers in differentiating VAT from VAP. C-reactive protein (CRP) and procalcitonin (PCT) were used as biomarkers. The study found that the median CRP was elevated more significantly in VAP than VAT  . Unfortu< 0.001) .p < 0.002) of the time [Fortuitously, studies investigating WBC gene upregulation (42 biomarkers) and four RNA biomarkers  in the acute phase response of the innate immune system have shown promise ,30. The the time . These vthe time . In compthe time . The negthe time . Taken athe time . FurtherLung ultrasound (LUS) is becoming increasingly recognized as a reliable adjunct in the diagnosis of VAP ,32,33,34Dilemmas on treatment approach are a direct and expected consequence of the dilemmas around the diagnosis of VAT. Current treatment obstacles include when to treat, antibiotics of choice, delivery method of antibiotics  and when to cease treatment(s).One of the principal arguments in favor of the treatment of VAT is that no treatment or delayed antibiotic treatment would likely result in more severe clinical outcome otherwise avoided with earlier antibiotic treatment, including one or more of the following: progression to VAP, increased MV and ICU LOS, difficult weaning process from MV or increased costs ,14,17,35The first randomised control study performed on the treatment efficacy of VAT demonstrated decreased ICU mortality for treated VAT patients versus patients not receiving antibiotics , with the trial needing to be stopped early due to the apparent benefit of treatment . In addip = 0.009) with a decrease in associated mortality [p < 0.001) [p < 0.0001; crude OR, 0.21, 95% CI 0.11–0.41) [An observational study including patients with multidrug-resistant (MDR) pathogens showed no difference in mortality if VAT was appropriately treated, however did show an important decrease in progression to VAP   along wi11–0.41) .MDR pathogens are increasingly implicated as causative agents in VAT within the last two decades, which may add further evidence of the importance of appropriate empirical antibiotic treatment for VAT, as is likewise acknowledged for VAP ,8.Pseudomonas aeruginosa and Acinetobacter baumannii), whilst also increasing adverse effects associated with increased antibiotic use [Considering the almost universally high prevalence of VAT , without decline in mortality or MV duration, with the overall rate of respiratory complications observed being 9% [In a review and meta-analysis performed on adults under mechanical ventilation, nebulized antibiotics significantly decreased the emergence of antibiotic resistance in VAT patients  on the use of nebulized antimicrobials for the treatment of respiratory infections in invasively mechanically ventilated adults recommends avoiding the use of nebulized antibiotics as adjuvants to intravenous antibiotics for the treatment of VAT due to low quality of evidence . In addiIn another review and meta-analysis of inhaled colistin monotherapy for respiratory tract infections (including VAT) , inhaledFurther research on the role of aerosolized antibiotics is undoubtedly needed, with emphasis on specific indications, optimal dosage, delivery safety issues and aptitude to decrease systemic antibiotics’ duration, systemic adverse events and antibiotic resistance. Finding of the main VAT articles included in this review are summarized in the Given the vague nature of the most commonly applied diagnostic criteria for VAT, it is safe to assume that an ICU physician who decides to treat VAT empirically has little assistance from current clinical guidelines and available literature when determining whether a patient has VAT and not either a colonization or a true VAP episode. Whether VAT represents the intermediate step between lower airway colonization and VAP or a separate entity with distinct modes of acquisition and evolution, remains debatable. Future diagnosis and treatment hinder on the development of novel biomarkers and more accurate imaging techniques. SeptiCyte Lab or other (currently unknown) molecular signatures in conjunction with LUS may provide the diagnostic accuracy necessary to delineate colonization from VAT and VAP. Nonetheless, most studies have quite convincingly demonstrated that VAT is closely related to VAP in terms of frequency, microbial ecology and resistance patters, diagnostic procedures and associated morbidity and costs. On the contrary, in terms of mortality, a veritable association between VAT and ultimately unfavorable outcome has not been adequately shown. Nevertheless, if one accepts the relevance between untreated VAT and progression to VAP, it is reasonable to assume that overall avoidance of treating VAT will incur more frequent cases of VAP, possibly leading to increased mortality.Until a consensus definition of VAT is reached and guidelines on VAT management are either more widely implemented or ultimately overruled, partially or completely, an individualized case by case diagnostic and treatment approach of VAT should be the paradigm. To accomplish this tailored approach of every VAT episode, apart from the patient’s individual characteristics, medical conditions, and comorbidities, ICU physicians need to be aware of certain factors, including local epidemiological data on the prevailing pathogens and MDR rates, pertinence of the in-use diagnostic procedures, the overall infection prevention and control policy on VAT and VAP, and the overall antibiotic policy. Lastly, as other ICU-acquired infections, the VAT treatment approach should be regularly evaluated for its overall impact on the entire antibiotic use and antibiotic resistance rates in ICUs, especially those with high MDR prevalence.Future research into the topic must include sufficiently powered studies aiming to evaluate the actual effect of VAT treatment on clinical outcomes. Such studies should incorporate stringent and widely accepted definition criteria, along with accurate and timely diagnostic tests and updated policies on the most appropriate antibiotic regimens .


Sleep is crucial for healthy cognition, including memory. The two main phases of sleep, REM and Non-REM sleep, are associated with characteristic electrophysiological patterns recorded using surface and intracranial electrodes. These patterns include sharp wave-ripples, cortical slow oscillations, delta waves and spindles during Non-REM sleep, and theta oscillations during REM sleep. They reflect the precisely timed activity of underlying neural circuits. Here, we review how these electrical signatures have been guiding our understanding of the circuits and processes sustaining memory consolidation during sleep, focusing on hippocampal theta oscillations and sharp wave-ripples and how they coordinate with cortical patterns. Finally, we highlight how these brain patterns could also sustain sleep-dependent homeostatic processes and evoke several potential future directions for research on the memory function of sleep. Memory formation is the challenging process of selecting which new experiences will be stored and integrated into an existing structure of memories that needs to be simultaneously preserved and modified. During wakefulness, this occurs concurrently with an uninterrupted flow of new sensory experiences. Sleep provides a window of opportunity for the brain to sort and reinforce newly encoded memories in absence of the incessant barrage of external information. This process, called “consolidation”, leads to the generation of long-lasting “memory traces” or “engrams” whose activation during wakefulness supports the recall of information.During sleep, a myriad of neural networks involved in memory processing are endogenously activated. Their activity generates electrical potentials captured using noninvasive surface electrodes (EEGs) or intracranial electrodes which can record local field potentials (LFPs) as well as action potentials (spiking activity). A large amount of effort has been devoted to describing how we can use meaningful patterns in these electrical fluctuations to understand the brain. These patterns include oscillations (eg. theta rhythm), transient potentials with an identifiable waveform (eg. dentate spikes), and spiking activity patterns (eg. UP and DOWN states). Combining signal analysis, anatomical data as well as targeted intracranial recordings or manipulation of superficial and deep structures has boosted our understanding of the cellular basis of these patterns. Ultimately, these advances may lead to an understanding of the role that sleep brain patterns play in learning and memory.reactivation. Using a wide range of methods  complex . The hip methods , 5, subsreplay”,  Fig. 2).replay”, .The first causal studies for the role of reactivation in memory consolidation developed closed-loop paradigms  to distuThe development of algorithms for fast, online detection of specific replay content, as opposed to the mere detection of ripples on LFPs, is a necessary step to further our understanding of the role of sleep replay. Along this line, Gridchyn et al.  trained While this review focuses on sleep, SWRs also occur during awake immobility and non-exploratory behaviors . Although there are no clear qualitative differences between awake and sleep ripples, their replay content differs . A majorAll major theories for long-term memory consolidation involve communication between the hippocampus and the neocortex . During Transcranial stimulation in humans can be used to boost slow oscillations during NREM sleep and the manipulation enhances performance at retrieval on the next day . NumerouSWRs and cortical NREM sleep patterns are temporally coordinated in a manner that is believed to promote plasticity and long-term consolidation of contextual (or episodic) memories , 22. HipBecause of the robust conceptual framework provided by both the two-step consolidation theory and the idea of a gradual transfer of information from the hippocampus towards cortical areas, the majority of studies on sleep patterns and memory consolidation have focused on the hippocampo-cortical dialogue. However, many other structures are involved in memory formation. SWRs in the hippocampus are extremely powerful events that can synchronize activity across structures beyond the neocortex, potentially associating other features, such as emotional tone, to various forms of memories, during the consolidation process. For example, reward-located hippocampal place cells and reward-encoding ventral striatum neurons fire together during sleep SWRs following the rewarded experience, with hippocampal activity leading the striatal activity . Dorsal Despite longstanding general interest in REM sleep stemming from its association with vivid dreaming in humans, the functional physiology of REM sleep has been understudied compared to NREM sleep. REM sleep EEG/LFP activity closely resembles awake activity: it was originally called “paradoxical” sleep for this very reason. Indeed, the dominant rhythm during REM sleep is the theta oscillation, characteristic 5-12 Hz waves most prominent in the hippocampus, but recorded in the cortex and other subcortical structures as well. During wakefulness, hippocampal theta organizes place cell firing in sequences. This fine timing of hippocampal activity by theta oscillations is crucial for the encoding and subsequent consolidation of spatial memory through place cell replay during NREM sleep ripples . Comparain vivo and in real time. Because cortical slow-wave activity stems from highly synchronized activity through UP and DOWN states, their amplitude is thought to reflect synaptic strength between cortical neurons. Accordingly, slow oscillations are strongest after extended wakefulness and progressively diminish across prolonged sleep episodes, in line with the SHY model (Learning has been associated with Hebbian plasticity and synaptic potentiation (LTP). According to the synaptic homeostasis hypothesis (SHY), sleep plays a crucial role in homeostatic regulation by down-scaling synaptic weights to avoid saturation and allow for the formation of new memories during the subsequent wakefulness epoch. More specifically, this model predicts that global synaptic weights increase during wakefulness and decrease throughout sleep. While there is structural and molecular evidence for this process , it is dHY model ). FurtheHY model . In paraHY model , 42. DurHY model , 42. IntHY model , also trHY model , and theAlthough simple to state, the link between sleep and memory actually translates into an incredibly complex field of research. First, sleep is not homogeneous and is subdivided into stages and substages characterized by different rhythms and patterns. Second, there are many different types of memories  that rely on different, although sometimes overlapping, networks of structures, themselves exhibiting different sleep patterns. Further, episodic memories are not a complete and faithful representation of actual events. Episodic memory formation, therefore, encompasses the initial encoding of the information, modifications, merging with other memories, and even forgetting . Given tper se, as opposed to the mere activation of the place-cell assembly (or engram) within a short time window, is important for memory consolidation. Testing theories on the significance of spike timing during patterns will require more precise real-time tools to perturb or impose the precise timing relationships between specific neurons without altering their firing rate at a broader time scale . It is possible, and remains to be investigated, that consolidation and homeostatic processes differ or are absent in other structures, especially those with no detectable sleep reactivation and/or different firing rate distributions across brain states. This direction is especially interesting for the highly complex network of structures that have a controlling role over sleep states and transitions such as the pons, thalamus, hypothalamus, locus coeruleus, and basal forebrain. Indeed, in the same way that consolidation and homeostasis might be tightly related, control and function of the different sleep stages could also be linked .Fueled by emerging recording, manipulation and analysis technologies with increasing spatio-temporal precision, we are in the process of completing a multidimensional knowledge space of mechanisms for different types of memory, different stages and substages of sleep and their associated physiological patterns. Although we might never reach a unifying theory for the memory function of sleep, expanding and precising this space will allow us to better integrate consolidation and homeostasis, unravel new links within memory function in all steps of memory formation from encoding to retrieval through consolidation, and link mnemonic mechanisms with other aspects of sleep such as sleep control, circadian rhythm or pathology.


Skin and soft tissue infections (SSTI) are a common but preventable cause of morbidity and mortality among people who inject drugs (PWID). They can be severe, and hospitalisations of PWID with SSTI are rising. The most common SSTI presentations are abscesses and cellulitis.We used data from Care & Prevent, a cross-sectional community survey of PWID in London. We reported the lifetime prevalence of SSTI, severity of infections, key risk factors, and associated sequelae. Pictorial questions were used to assess SSTI severity.We recruited 455 PWID. SSTI lifetime prevalence was high: 64% reported an abscess and/or cellulitis. Over one-third (37%) reported a severe infection, 137 (47%) reported hospitalisation. SSTIrisk factors were: aged 35+ years, injecting once or more times a day, subcutaneous or intra-muscular injections, and making four or more attempts to achieve an injection. Those who reported having other health conditions were at higher odds of having an abscess or cellulitis, with risk tending to increase with number of reported conditions. Half (46%) employed self-care for their worst SSTI, and 43% waited for ten or more days before seeking medical care or not seeking medical care at all.Abscess and cellulitis are very common among PWID in London. We corroborate findings indicating SSTIs are associated with risks, e.g. venous access problems, as well as other co-morbid conditions: septicaemia, endocarditis, DVT, and kidney disease. These co-morbidities may impact SSTIs severity and outcomes. Delayed healthcare seeking potentially exacerbates infection severity, which in turn increases poorer health outcomes and complications. Skin and soft tissue infections (SSTI) are a preventable cause of morbidity and mortality among people who inject drugs (PWID) , 2. In tA recent systematic review of injecting-related injury and disease found past-month prevalence of SSTI among PWID between 6% (UK) and 32% (USA), and lifetime prevalence between 6%  and 69% (Ireland) . This vaCare & Prevent (C&P) is a mixed method project aiming to explore risk factors for, and prevalence of, SSTI and associated sequelae among PWID in London. Study rationale and methods detail have been published . EthicalParticipants were eligible for recruitment if they were aged 18 years or older at the time of the study and had a history of injecting psychoactive drugs. Recruitment was conducted through six drug treatment services and through a homeless outreach team visiting homeless hostels and day centres across London, UK. Participants were informed about the study through a notice in the service waiting room and through participant information sheets supplied by keyworkers and/or nurses during clinical appointments. Researchers were present at the sites on specified days to provide further information.Data generation methods comprised: a computer assisted researcher administered SSTI risk factor questionnaire, urinalysis for proteinuria, and in-depth qualitative interviews. This paper reports findings from the questionnaire data, generated between October 2017 and March 2019 using Open Data Kit (ODK) software . Data arThe questionnaire was developed through consultation with a panel of experts and drew on existing surveys such as the Unlinked Anonymous Monitoring (UAM) Survey, a National surveillance study with PWID conducted annually . QuestioSSTI risk factor questions included detail on reuse of injecting equipment, injecting hygiene practices, primary drugs injected, type and amount of acidifier used to prepare injection solutions, number of injections per day, week or month, body sites injected and number of times taken to achieve an injection. The latter question was included as it provides a strong indication of peripheral venous damage–a risk factor for SSTI . ParticiIn addition to SSTI and hospitalisation specific questions, participants were asked if they had received a medical diagnosis for the following health conditions: blood poisoning, arthritis, hepatitis B and C, deep vein thrombosis (DVT), diabetes, kidney disease, necrotising fasciitis, human immunodeficiency virus (HIV), chronic obstructive pulmonary disease (COPD), liver cirrhosis, tuberculosis, bone and/or joint infection, endocarditis, lymphangitis, and hypertension. These conditions were determined in relation to their potential to confound findings because they can cause inflammation, and/or affect the functioning of the immune or circulatory systems. We also asked participants whether they had ever had an invasive bacterial infection, defined as an infection of the blood, bones, joints, heart, or fascia. These infections were removed from the final analysis to demonstrate a clearer hypothetical causal pathway from comorbidities (other than invasive infections) to SSTIs to invasive infections.Descriptive statistics, including means, medians and ranges are presented for the study population, and those who reported lifetime history of an abscess and/or cellulitis. All variables in this study are reported across the participants’ injecting career, unless stated otherwise. Correlations between risk factors and having ever experienced an abscess and/or cellulitis were assessed using Chi-square tests of independence. Exposure variables associated with the outcome were assessed using logistic regression models on Stata version 15.1 . AnalyseFour-hundred and fifty-five participants completed the questionnaire . Three-qIn univariable analysis, SSTI was associated with older age, number of attempts before successful injection into a vein, injecting frequency per week, reusing needles and/or syringes, and reusing filters. Most participants with an abscess and/or cellulitis were aged 45 or older, injected once or more a day, required four or more attempts before successful injection into a vein, and reported reusing needles and/or syringes, and reusing filters.The relationship between abscesses or cellulitis and invasive infections (e.g. septicaemia and endocarditis) is summarised in The majority of participants employed self-care for their worst SSTI after first noticing symptoms , followed by seeking medical care . When asked how long they took to seek medical advice, 60% of participants (121) reported waiting for more than five days after first noticing symptoms, with more than a third with severe infections waiting for 10 or more days before seeking medical advice or not seeking advice at all . Of those who reported a bacterial infection, 137/291 (47%) reported an SSTI-related hospitalisation. The proportion reporting hospitalisation was higher among those with a severe infection, at 79/107 (74%).Lifetime SSTI was associated with being aged 35–44 or 45+ (compared to being aged under 35); injecting once or more a day; sometimes or always reusing needles, syringes, and/or filters; practicing sub-cutaneous or intra-muscular injection; and taking four or more attempts (skin punctures) to achieve an injection. Crude and adjusted associations are presented in Reported comorbidities, other than invasive infections, were common among those who have experienced a SSTI. Half  of the sample reported at least two or more diagnoses of health conditions. Those who reported having one or multiple health conditions were at higher odds of co-reporting a SSTI. There was a strong, graded association between the number of comorbidities and the likelihood of reporting a lifetime SSTI.We used a novel survey technique using photographs of injecting related wounds to measure prevalence, type and severity of bacterial SSTIs among a sample of people who inject drugs in London. Two-thirds of participants reported ever having had an abscess and/or cellulitis, with many prioritising self-care and/or taking more than five days to engage with medical care after first noticing an infection. Nearly half of those experiencing an SSTI reported a serious infection requiring hospitalisation. Invasive bacterial diseases were more commonly reported by those who had also reported a bacterial SSTI, particularly those with severe localised infections, suggesting that safer injecting and timely access to wound care in the community may help prevent serious infections.Our findings on the risks of injection frequency, and non-venous injections e.g. sub-cutaneous and intra-muscular, confirm those found by others , 24. A nIn the case of septicaemia and endocarditis, untreated bacterial infections can spread, through the blood, from the skin infection site causing serious systemic infection [We found a strong graded association between co-morbid health conditions and the risk of SSTI. This reflects a number of causal pathways, probably acting in both directions. For example, disease such as diabetes and HIV may reduce immunity and increase susceptibility to SSTI. On the other hand, inflammation associated with repeated SSTI may increase the risk of diseases such as arthritis and kidney disease . In the nfection We highlight an association between severity of infection and the time taken to seek healthcare. We found that most (60%) of our cohort indicated taking five or more days to seek medical attention after first noticing the symptoms of a bacterial SSTI. This duration has been previously used as a measure of care delay  and reflIt is well evidenced that PWID face significant barriers in accessing appropriate healthcare due to stigma and discrimination from healthcare professionals as well as structural difficulties in accessing and attending medical appointments –31. QualThe proportion of participants reporting a lifetime SSTI in our results (64%) is at the high end of a range reported in a recent systematic review . This maThis study captured a wide range of injecting-related risk factors and measured the severity of infections, which to our knowledge has not been measured in previous studies. The survey method allowed us to study detailed aspects of participants’ risk environment. The cross-sectional design meant that we were not able to establish a temporal relationship between bacterial SSTIs and these injecting risk factors, or report incidence. This contrasts with longitudinal studies using healthcare records, which provide more precise estimates of incidence but often lack detailed risk factor information  Self-repThis study is of importance due to its use of photographs to elicit SSTI recall, which contextualises and increases our understanding of risk factors. The validity of the approach of still based images for self-report of SSTI severity is not known. The images were chosen in consultation with skin infection specialists, but have not been validated or compared to a gold standard . Despite this, there is plausible predictive validity in the sense that those with more severe local infections (abscesses and cellulitis) had higher prevalence of invasive infections. Clinical diagnosis was not possible in this study as recruitment was opportunistic and access to skin infection specialist clinicians was not available.Recruitment through community rather than hospital settings captures a more thorough assessment of prevalence by engaging those who have restricted access to hospitals and services. Analysis has demonstrated that C&P sample is comparable to those of PWID participating in the larger National UAM surveillance survey . We haveWe found high lifetime prevalence of SSTI among PWID in London, with severity and health complications potentially exacerbated by delayed medical care seeking. Interventions to reduce SSTI prevalence, severity and sequalae need to attend both to injection practice risk factors but also the social structural barriers faced by PWID in accessing timely health care.S1 Data(XLSX)Click here for additional data file.


Poly(N-isopropylacrylamide) (PNIPAM)-based thermosensitive hydrogels demonstrate great potential in biomedical applications. However, they have inherent drawbacks such as low mechanical strength, limited drug loading capacity and low biodegradability. Formulating PNIPAM with other functional components to form composited hydrogels is an effective strategy to make up for these deficiencies, which can greatly benefit their practical applications. This review seeks to provide a comprehensive observation about the PNIPAM-based composite hydrogels for biomedical applications so as to guide related research. It covers the general principles from the materials choice to the hybridization strategies as well as the performance improvement by focusing on several application areas including drug delivery, tissue engineering and wound dressing. The most effective strategies include incorporation of functional inorganic nanoparticles or self-assembled structures to give composite hydrogels and linking PNIPAM with other polymer blocks of unique properties to produce copolymeric hydrogels, which can improve the properties of the hydrogels by enhancing the mechanical strength, giving higher biocompatibility and biodegradability, introducing multi-stimuli responsibility, enabling higher drug loading capacity as well as controlled release. These aspects will be of great help for promoting the development of PNIPAM-based composite materials for biomedical applications. Hydrogels are based on using hydrophobic and hydrophilic components to form three-dimensional 3D) network structures under physical and/or chemical interactions, which can imbibe a large amount of water molecules and freeze their movements ,2,3,4. ID networkSmart hydrogels can respond to a variety of external stimuli such as pH, temperature, light, electric field or ionic strength ,11,12,13A thermosensitive polymer usually possesses both hydrophilic and hydrophobic groups . Interac3)2) side chains and has a LCST of 32 °C, which is slightly lower than the body temperature of ~37 °C . I. I3K witindrance B 92,93]3K with PThe mechanical properties of hydrogels play crucial roles in their biomedical applications. However, poor mechanical strength is one of the drawbacks of PNIPAM hydrogels that greatly restricts their applications. The IPN hydrogels provide an effective strategy for enhancing the mechanical strength of PNIPAM-based hydrogels. Wei et al. have introduced salecan, a kind of natural and hydrophilic polysaccharide, into the network of PNIPAM hydrogels through free radical polymerization . The resBasically, PNIPAM hydrogels cannot load hydrophobic drugs efficiently due to the absence of hydrophobic binding sites. Feng et al. embedded nano-liposome micelles in poly[(N-isopropylacrylamide)-co-chitosan] (PNIPAM-co-CS) or poly[(N-isopropylacrylamide)-co-] (PNIPAM-co-SA) hydrogels to form composite systems . The lipHow the drug is loaded into the hydrogel and released from it are very crucial in achieving desirable therapeutic outcomes. It is the usual case that a required duration of drug availability and a well-controlled release profile are needed for a specific biomedical treatment. A variety of nanoparticles including carbon-based nanoparticles, polymeric nanoparticles, inorganic/ceramic nanoparticles and metallic nanoparticles can be introduced into PNIPAM hydrogels through physical or chemical cross-linking ,95,96. TThe biodegradability of PNIPAM-based hydrogels is less studied than their other properties, however, lack of biodegradability is a significant drawback of them for some practical applications. It may lead to an incomplete release of drugs in drug delivery applications. For tissue engineering, a secondary surgical process will be avoided by using degradable scaffolds that can be degraded via metabolism in the body and then discharged outside. Das et al. incorporated dextrin, a natural polysaccharide that can be easily degraded by amylase, into PNIPAM hydrogel through free radical polymerization to form an oral drug carrier. This delivery system turns out to be a potential dual drug carrier for controlled delivery of ornidazole and ciprofloxacin with good biodegradability .Injectable hydrogels are one kind of novel biomedical materials that keep fluid state outside body and transform into gels after injection into body ,99,100. PNIPAM-based hydrogels undergo a volume shrink at temperatures above the LCST due to strong intra- and intermolecular hydrophobic interactions . This prIn the above section, we present examples on PNIPAM-based hydrogels for drug delivery applications by emphasizing the strategies that can overcome the drawbacks of pure PNIPAM hydrogels. By choosing suitable materials to form composite hydrogels with PNIPAM, the properties and functionalities of the hydrogels can be greatly improved. In these examples, the thermosensitivity of PNIPAM hydrogels is retained, while the introduced components can either act as drug carriers to load more drugs or help to enhance the mechanical strength of the hydrogels and to provide biocompatibility and biodegradability to the systems. These aspects all highlight the enormous potential of PNIPAM-based composite hydrogels for efficient drug encapsulation and release. However, there are still some challenges for drug delivery applications of PNIPAM-based hydrogels. Current biomedical development invokes many needs for novel drug delivery materials. One great demand is to develop novel hydrogel materials that can meet the requirements of severe and complicated disease treatment, for example, cancer therapy, where multidrug delivery to targeted sites and combined therapeutic strategies may be needed. Furthermore, the gene-editing technology such as CRISPR–Cas9 requires efficient delivery of proteins and genes rather than traditional drugs to targeted disease tissues. For these applications, the hydrogels must be designed to protect proteins and genes before reaching the targeted cells and release them easily inside cells. These aspects all provide higher demands for designing PNIPAM-based hydrogels with precise control over the functionalities at the molecular level.Tissue engineering, also known as regenerative medicine, utilizes the basic principles and methods of cell biology and engineering for researching and developing biological substitutes in order to promote tissue regeneration and recover the morphology and function of tissues or replace the damaged organs ,13. In rHydrogels are appealing scaffold materials for tissue engineering by having structural similarity to the extracellular matrix of many tissues . The hydThe materials used to composite with PNIPAM will modify the properties of the resulted hydrogels by introducing new functionalities and characteristics. It has been demonstrated that the biocompatibility and degradability of PNIPAM hydrogels can be improved by introducing suitable nanomaterials into the system. Cell sheet harvesting (CSH) is an important technique for in tissue engineering. The thermosensitive phase transition of PNIPAM is of great potential for preparing thermo-responsive materials for CSH purposes. However, the native PNIPAM hydrogel is not suitable for CSH due to its low cell attachment. In a recent work, we developed a PNIPAM-based composite hydrogel by incorporating graphene oxide (GO) nanosheets into the system through free radical polymerization with polyethylene glycol dimethacrylate (PEGDA) as a cross-linker . The intg-PNIPAM hydrogels to mimic the extracellular matrix of stem cells [Another effective strategy to regulate the biocompatibility and biodegradability of PNIPAM hydrogels is linking PNIPAM with other polymer blocks of unique properties to produce copolymeric hydrogels that have enhanced biosafety and defined degradation routes introduced by the second polymer block. For example, Spizzirri et al. introduced chitosan, a hydrophilic polysaccharide, into the PNIPAM hydrogel by using free radical grafting, which can impart biocompatibility and biodegradability into the systems . In anotem cells . These hem cells . The thiThe mechanical properties of hydrogels play crucial roles in regulating the interactions between cells and extracellular matrix. To meet the criteria for tissue engineering applications, the mechanical strength of PNIPAM hydrogels can be greatly improved by linking PNIPAM with other polymeric blocks to produce copolymers. Tan et al. synthesized a thermo-sensitive comblike copolymer by connecting carboxylic end-capped PNIPAM and aminated alginate . The resInjectable hydrogels can be injected into the patients in an invasive manner under mild conditions, thereby avoiding the painful surgery. Moreover, the hydrogel matrices can support growth of cells for tissue regeneration . Atoufi For application of injectable hydrogels in tissue engineering, the mechanical properties of the hydrogels play crucial roles in determining the therapeutic effects. On the one hand, implanted hydrogels usually suffer from constant external mechanical force after injection, which can lead to deformation or damage to the hydrogels and can shorten the lifespan of the hydrogels . On the In brief, the copolymers synthesized by connecting PNIPAM with other polymeric blocks or functional components not only retain thermosensitivity, but also have highly improved mechanical strength and better biocompatibility and degradability. They can produce hydrogels that mimic very well the structures and properties of extracellular matrix, which can encapsulate cells efficiently and maintain their physiological activity for proliferation and differentiation. Therefore, such hydrogels are highly promising for practical tissue engineering applications. However, there are also many aspects that need to be stressed before clinical translation. One important aspect is to design hydrogel scaffolds that meet the requirements of complicated in vivo applications. First, the performance of the hydrogels should be unaffected by the microenvironments such as body fluids, tissue secrets and joint movement. Second, the implanted hydrogels should have a defined degradation profile that cannot produce toxic byproducts while the degradation speed keeps pace with the tissue regenerative speed. Moreover, the implanted hydrogels for long course tissue repair and regeneration must consider the immune problems, which may require the introduction of specific materials for controlled regenerative immunology.Wound treatment is very common in clinical medicine. Traditional materials for wound treatment include gauzes, cotton wools and adhesive bandages. However, these materials are usually considered as passive dressings because they can only provide a simple protection of the wounds and often cause a slow healing process . MoreoveSuperior mechanical performance is also crucial for wound dressing materials. To compensate for the inherent drawback of poor mechanical strength of PNIPAM hydrogels, Zubik et al. used cellulose nanocrystals (CNCs) to hybrid with PNIPAM via a free radical polymerization to fabricate composite hydrogel properties . CNCs haGrafting the hydrogel onto a supporting material with excellent properties is also an effective method to compensate its inherent drawbacks. Nonwoven fabric is a popular material that has merits of high mechanical strength and convenient handling. Hathaway et al. grafted PNIPAM-co-allylamine (PNIPAM-co-ALA) complex hydrogel on the nonwoven fabric through interactions between the functional groups of ALA and the fabric surface . The resMore significantly, the composite hydrogels with comprehensive properties can be obtained by rational design to incorporate various components. Appropriate water vapor transmission is a very important parameter for an ideal wound dressing to make patients comfortable. For that end, Li et al. first synthesized a PNIPAM/alginate composite hydrogel and then combined it with cotton fabric . The addStaphylococcus aureus and produced a good therapeutic effect for burn wounds. It is believed that the AgNP-polymeric composites formation improved dispersion of AgNPs and decreased their direct exposure to cells, which reasonably led to an enhancement of the bacteriostatic activities while reducing the cytotoxicity. Such a strategy has also been applied for scald administration, which is a very tough task in clinical therapeutics due to the great challenge of reducing the pain of patients and minimizing the infection of pathogens colonization. Liu et al. designed a PNIPAM-based wound dressing for first aid of scald by integrating PNIPAM hydrogel, sodium polyacrylate and AgNPs into a single system [Silver nanoparticles (AgNPs) have been well demonstrated to be an effective bacteriostatic agent that has a broad-spectrum antimicrobial activity without the development of bacterial resistance, which therefore are highly potential for treatment of wound infection . Howevere system . This drMoreover, through rational design, the PNIPAM hydrogel can be composited with other functional materials to accelerate wound healing by mimicking natural processes. Blacklow et al. have successfully designed a PNIPAM-based hybrid hydrogel by involving PNIPAM, alginate, silver nanoparticles (AgNPs), chitosan and carbodiimide . This hyThe adhesiveness of PNIPAM hydrogel to tissue/cell is an important parameter for wound dressing applications. For example, for skin wound treatment, the hydrogels are placed on dynamic surfaces and they need to adhere tightly on skin surfaces and be tough enough to tolerate the skin movements so as to speed up the healing process. However, pure PNIPAM hydrogels usually display a weak adhesion, therefore, it is of great demand to develop PNIPAM-based composite hydrogels with enhanced adhesiveness. Lu et al. introduced polydopamine nanoparticles (PDA-NPs) into PNIPAM network to synthesize the PDA-NPs/PNIPAM composite hydrogel . Since PTo summarize, the PNIPAM-based hydrogels have promising applications as wound dressings. Composite hydrogels formulation can help to optimize the properties of the wound dressings to have the merits of moisture retaining, enhanced adhesiveness, high comfortableness, temperature-triggered precise drug delivery, long time inhibition of infection and allowing supervision of the wound treatment process, which therefore can help to accelerate the healing process of the wounds. This strategy paves the way for application of hydrogels in practical clinical wound administration. Currently the challenging topics for wound dressing applications of the PNIPAM-based hydrogels focus on development of tough and highly adhesive hydrogels that can meet specific clinical requirements. For example, sometimes the inside tissues such as the heart may be injured accidently or by surgery. In this case, the wound dressing should adhere and conform robustly to the tissue surfaces with many body fluids and dynamic movements, which provide exceptional requirements for the superior mechanical strength and adhesiveness of the hydrogel.To summarize, PNIPAM-based thermoresponsive hydrogels demonstrate great potential in many biomedical areas, from drug delivery to tissue engineering and wound dressings. A specific advantage is that PNIPAM has a LCST of about 32 °C and can be easily triggered by body temperature to give a phase transition, which makes PNIPAM-based hydrogels highly suitable for practical applications. Though PNIPAM hydrogels themselves have the drawbacks of low mechanical strength, limited drug loading capacity, low biodegradability and so on, they can be formulated with other components to form composited hydrogels so as to make up for these deficiencies. Researchers have developed several effective strategies to improve the properties of PNIPAM-based hydrogels, which include incorporating functional inorganic nanoparticles or self-assembled structures into the system either physically or chemically and linking PNIPAM with other polymer blocks of unique properties to produce copolymeric hydrogels. These strategies can successfully enhance the mechanical strength, give higher biocompatibility and biodegradability, introduce multi-stimuli responsibility, or enable multidrug encapsulation and higher drug loading amount as well as controlled release, which therefore greatly promote the practical applications of PNIPAM-based hydrogels.However, despite being promising, there are still some major concerns and challenges in developing PNIPAM-based hydrogels for biomedical applications. Currently, it is still a great challenge to optimize the properties of the composite hydrogels by choosing suitable hybridizing materials and strategies. The practical biomedical applications usually face complicated conditions and require extremely strict property controls over the composite hydrogel. Therefore, controlled fabrication of PNIPAM-based hydrogels with required properties is of great importance to improve their therapeutic efficacy. Moreover, most state-of-the-art PNIPAM-based hydrogels are still at the stage that is far from clinical practice. For biomedical applications, materials fabrication is only the first step. After that, more preclinical toxicological and pathological studies must be performed to get a detailed understanding and control of the physiological stability, toxicity, immune response, pharmacokinetics as well as biodegradation and elimination of the biomedical materials . Despite


Plant phenotyping has been recognized as a bottleneck for improving the efficiency of breeding programs, understanding plant-environment interactions, and managing agricultural systems. In the past five years, imaging approaches have shown great potential for high-throughput plant phenotyping, resulting in more attention paid to imaging-based plant phenotyping. With this increased amount of image data, it has become urgent to develop robust analytical tools that can extract phenotypic traits accurately and rapidly. The goal of this review is to provide a comprehensive overview of the latest studies using deep convolutional neural networks (CNNs) in plant phenotyping applications. We specifically review the use of various CNN architecture for plant stress evaluation, plant development, and postharvest quality assessment. We systematically organize the studies based on technical developments resulting from imaging classification, object detection, and image segmentation, thereby identifying state-of-the-art solutions for certain phenotyping applications. Finally, we provide several directions for future research in the use of CNN architecture for plant phenotyping purposes. Food security is one of the biggest challenges for the world. The global population is likely to exceed 9 billion by 2050, which will necessitate more food, fiber, and fuel products from agricultural production systems . To fulfThere are two potential ways to address these issues: improving crops and improving crop management. Improving crops is aimed at breeding new crop cultivars such that crops can naturally have a higher yield, better quality, and improved adaptability to various environments . Improving crop management seeks to advance farming concepts, such as precision agriculture, which minimize the input  and maximize the outcome  for an agricultural production system through technological innovations . Both ways face the same bottleneck: the evaluation of a large amount of plants in the field. It is therefore paramount to develop new technologies to accurately evaluate crop plants in a high-throughput manner.High-throughput plant phenotyping (HTP) has been recognized as integral to overcoming this bottleneck –12. In tDeep learning (DL) is a subset of machine learning and allows for hierarchical data learning. The key DL advantage is that features will be learned automatically from input data, thereby breaking down barriers to the development of intelligent solutions to different applications. A commonly used DL architecture is deep convolutional neural networks (CNNs), which have achieved state-of-the-art performance for important computer vision tasks, such as image classification/regression, object recognition, and image segmentation (both semantic and instance). CNNs originated in the1980s  and showSeveral papers have been published in the last two years that provide comprehensive reviews of DL techniques for such computer vision tasks as image classification , 19, objThe goal of this review is to scrutinize thoroughly the current efforts, provide insights, and identify potential research directions for the utilization of CNNs for imaging-based plant phenotyping. This review focuses on key phenotyping tasks related to plant stress, development, and postharvest quality. By addressing this gap in research, it is expected that readers can bring CNNs into their research to benefit the plant phenotyping community. Deep learning and plant phenotyping are emerging research fields and grow extremely rapidly, so this review primarily focuses on studies published (1) in peer-reviewed (or open-reviewed) journals and conferences; (2) in the most recent 5 years (2015 to 2020); and (3) in the use of CNNs for imaging-based plant phenotyping. Literature has been collected from three main resources including Elsevier ScienceDirect, IEEE Xplore Digital Library, and Google Scholar. Keywords of “CNN” and phenotyping tasks  were used as combinations for literature searching. The rest of this review is organized in the following way: Since 2012, CNNs have dominated the solutions for computer vision tasks because of their superior performance. While efforts have been made to review thoroughly the development of various CNN architecture for computer vision tasks –21, we hImage classification is one of the core tasks in computer vision and is aimed at assigning images with predefined class labels. CNNs are artificial neural networks that combine a set of mathematical operations  using various connection schemes , and the operational parameters  can be learned from annotated images to predict image class labels  was reported and demonstrated breakthrough performance on image classification in the 2012 ImageNet Large Scale Visual Recognition Challenge (ILSVRC 2012) competition . It showIn addition to performance improvement, studies have been conducted to understand the mechanism of CNNs. This leads the development of techniques towards explainable artificial intelligence which helps develop interpretable and inclusive machine learning models and deploy the models with confidence. A pioneering work improved AlexNet to a new variant (ZFNet) using a visualization tool. This visualization tool is a framework integrated with CNNs that can map neuron activities back to the input pixel space. Pixel-wise activations, therefore, can be visualized after each convolutional layer. This would be particularly useful for researchers seeking to understand the CNN mechanism and improve architectural design. The study also showed that learned features could be generalized to various classifiers, suggesting CNNs could learn general representations of images rather than specific features for classification. Successive studies furthered this direction and developed various gradient-based methods that can visualize the importance/relevance of features to classification results. Commonly used methods include guided backpropagation, gradient-weighted class activation mapping (Grad-CAM), and layer-wise relevance propagation (LRP). Some general framework  can also be used to reveal important image regions to classification results. Details of these visualization methods can be obtained in separate reviews , 29.Object detection seeks to detect and classify all potential objects in a given image. The use of CNNs for object detection can be categorized into two groups: one-stage and two-stage CNN architecture , ROI pooling operation, and multitask loss function. An RPN was developed to generate candidate object ROIs using features extracted from CNNs, which simultaneously saved processing time and increased region proposal accuracy. An ROI pooling operation was developed to extract a fixed number of features from ROIs with varying sizes, thereby avoiding the repeated computation of features for different ROIs. A multitask loss function was used to unify the training process, which enabled an end-to-end training for object detection. With these three improvements, Faster RCNN has been used widely as either a benchmark for performance comparison or an object detector for domain applications  because it is easy to train and generally provides accurate detection performance. Although Faster RCNN provides state-of-the-art accuracy, its efficiency is still inadequate for use in real-time applications such as autonomous driving. This is mainly because the two-stage models spend time handling different components for inference . CompareRepresentative one-stage models include the you-only-look-once (YOLO) family  and the Semantic segmentation seeks to provide masks for objects with the same semantic meaning , whereas instance segmentation seeks to provide individual objects in a given image. In general, CNN architecture for semantic/instance segmentation can be classified into two groups: encoder-decoder-based frameworks and detection-based frameworks  for upsampling of extracted feature maps to per-pixel labels. Two techniques have been used to improve the segmentation accuracy of encoder-decoder models. First, a lateral connection scheme is used to link feature maps with the same spatial resolution between the encoder and decoder phases, which aids in the preservation of semantic meaning from input images to output segmentation results . Second,Plant stress phenotyping is aimed at identifying and evaluating plant responses to abiotic and biotic stresses, providing information for the selection of accession lines with high stress resistance and tolerance in breeding programs and the understanding of intrinsic mechanisms in genetics/genomics studies. In addition, plant stress detection, especially in early stages, is crucial for data-driven pest and weed management in agricultural production systems. Plant stress phenotyping can be categorized into four stages: (1) identification (presence of stress); (2) classification (type of stress); (3) quantification (severity of stress); and (4) prediction (possibility of stress occurrence) . From thhttps://plantvillage.psu.edu/) is a publicly available image dataset containing over 54,000 labeled plant leaf images from 14 crop species with 26 types of stress. This can be used to either evaluate a new CNN architecture or pretrain a CNN model for transfer learning. Data annotation for image classification is also relatively easy (compared with object detection and semantic/instance segmentation), so a large number of images in a newly collected dataset can be annotated within a reasonable time and cost, especially when a proper data collection procedure is used. As a result, studies related to plant stress detection typically have a sufficient number of annotated images  for model training. In addition, DL libraries have been developed to accelerate the implementation and training of CNNs for image classification. Commonly used DL libraries include Caffe , Theno , TensorFlow (Google), PyTorch (Facebook), CNTK (Microsoft), and Keras (open source). Key CNNs  have been implemented using various libraries, so researchers can develop computer programs quickly for training CNNs provided the annotated data are available. These advancements facilitate the use of CNNs for plant stress identification at the image level. By using good training practices , various studies have shown that CNNs achieved accuracies from 87% to 99% for stress identification and classification . In. In55]. iagnosis . Explanaiagnosis . AR-GAN In addition to image classification-based approaches, improved CNN models for object detection were used for plant stress phenotyping . Three rAdvanced imaging modalities  capture plant data in a wider spectrum than RGB imaging, providing useful information for plant stress identification. A very recent study explored the use of a custom CNN architecture to detect plant diseases in hyperspectral images . The novMorphological changes of plant shoot are key to describing plant development. Canopy coverage and leaf area are two commonly used parameters to quantify plant growth and development, especially in aerial image analysis. Calculating the two parameters requires accurate plant segmentation. Many studies have used color-based features  to segment plants, but they usually had imperfect segmentation because plant color could have large image-by-image variations due to illumination, shadowing, occlusion, and so on. Therefore, some studies explored the use of CNNs for plant segmentation –64. MostTwo studies treated morphological measurement as an object detection problem , 65. TheResearchers also combined CNNs with other DL methods ) for plant development characterization , 67. CNNIn addition to morphological measurements, CNNs could be used to monitor certain plant development events such as plant lodging . A new CCounting plants and plant organs are central to characterizing plant development. This section provides a comprehensive overview of studies related to the detection and counting of plants and plant organs. Based on data format, these studies can be classified into two categories: (1) detection and counting in still images and (2) detection and counting in image sequences and videos.(1) Counting in Still Images. Regression or image classification (can be considered discrete regression) is the simplest and most straightforward way to fruit/organ counting from the technical development viewpoint  to those estimated using manual counts (H2 = 0.982), indicating a great potential for incorporating DL for plant phenotyping and, therefore, breeding programs and genetics/genomics studies. However, the developed method has the major limitation of potential difficulty in generalizing the method for other plants with complex canopy structures and flowering patterns, such as cotton. Flowers in those plants are usually inside canopies instead of on the top of canopies, which can increase partial or full occlusions. If flowers cannot be imaged, it is not feasible to train any ML/DL model for detection and counting. Researchers also used the classification-based method for counting the number of pods in soybeans and obtained a similar performance as human experts . Experimental results showed that the regression-based counting method outperformed not only traditional computer vision-based counting methods but also CNN segmentation-based method. This suggests that postprocessing can be a limiting factor for the accuracy of trait measurement despite the use of CNNs for RSA segmentation.In addition to 2D imaging, CNNs have been adopted to segment RSA in X-ray imaging  and to cWhile the plant phenotyping community is primarily focusing on in-season plant performance, postharvest quality is also an important focus for plant phenotyping because postharvest properties significantly affect the eventual crop productivity and quality. Based on the nature of the analysis, postharvest quality assessment can be classified into two categories: qualitative assessment and quantitative assessment. Qualitative assessment provides scores/grades for crop fruit, such as defect detection and freshness grading, whereas quantitative assessment provides continuous values for crop postharvest properties, such as firmness and soluble solid content (SSC).Qualitative assessment of postharvest quality is similar to plant stress phenotyping, with its unique emphasis on fruit rather than plant. Most studies have investigated the use of CNNs to detect defects for fruits such as cucumbers , apples x-axis indicates excitation wavelengths (nm), the y-axis indicates emission wavelengths (nm), and the intensity of a pixel (x and y) is sample fluorescence excited at x (nm) by using emission light at y (nm). Images of EEM were used as input to train a custom CNN with 8 layers for regression. Sugar/acid ratio values were estimated using the trained CNN models for 20 testing samples, and results showed that the CNN-based regression model achieved the lowest prediction error of 2.48, which was 2 to 3 times less than conventional regression models. Another study investigated the use of a fully convolutional network (FCN) for segmenting bruised, nonbruised, and calyx end tissues for blueberries [Quantitative assessment of postharvest quality  can also be processed using CNNs. A study was conducted to develop a CNN-based regression model for estimating sugar/acid ratio for citrus . An excieberries . The FCNAll the methods reviewed for various phenotyping applications are summarized in The availability of diverse annotated datasets is a key factor for all DL-related studies. Adequate annotated datasets enable and ensure the swift development and evolution of DL methods. This generally holds true for domain applications such as plant phenotyping. For biotic/abiotic stress phenotyping, data annotation is relatively straightforward and has resulted in several large publicly available datasets, such as PlantVillage. For plant development, as sensing technologies are under development, few datasets are publicly available and there are also few annotated datasets. As the main purpose of DL is to learn features from data, it is very difficult to develop (or even use) DL techniques without sufficient annotated data. Data annotation itself comes with several challenges for plant phenotyping. First, data annotation sometimes requires domain expertise. For instance, it is easy to label cars, whereas it is difficult to label particular plant diseases because of the need of domain knowledge and working experiences. Thus, it is not easy to crowdsource annotation tasks, which limits the efficiency and throughput of data labeling. Second, unlike common uses, plant phenotyping oftentimes relies on advanced imaging techniques, such as thermal and hyperspectral imaging. Labeling of those data is considerably more difficult than labeling color images because of fewer visual cues. Third, there are many phenotyping applications that require object detection and segmentation , and these applications require instance-level (bounding boxes) and pixel-level (masks) annotations. Those are very time-consuming tasks and become the major limiting factor for using DL in plant phenotyping. Some challenges are common for general computer vision tasks, and researchers have proposed and developed some solutions. To significantly reduce the requirements of labeled data, one of the most important techniques is transfer learning. Transfer learning relies on the assumption that a very large dataset ensures that the learned filters are common for other datasets. Thus, for some domain applications with limited labeled data, transfer learning could significantly improve training efficiency and accuracy. However, the key challenge is whether phenotyping datasets are similar to very large common datasets , especially for some phenotyping applications using advanced imaging techniques . Active learning is another effort for the reduction in the cost of data labeling. Compared with conventional data annotation, active learning is aimed at finding and labeling samples that maximize model performance. Thus, the majority of samples do not need to be annotated to save time and labor cost. Crowdsourcing is also a viable way for data annotation, which requires less investment in labor cost. Some studies have demonstrated the capability of using crowdsourcing for quickly labeling large image datasets for machine learning applications. In particular, there are some commercial services for crowdsourcing annotation such as Amazon Mechanical Turk and CrowdFlower. Through those services, a reasonable quality and throughput can be ensured for data annotation. In addition, GANs have been originally proposed as a generative module for deep learning , but theAnother important consideration is the adoption of DL methods for plant phenotyping. Technology companies have released various DL frameworks that accelerate the development and implementation of new DL algorithms such as reinforcement learning and attention mechanism. In particular, the DL community encourages researchers to share source codes of original studies to facilitate other research projects. These efforts considerably ease the adoption of the latest DL methods for domain applications, such as plant phenotyping. However, there is still a delay in the use of the latest technologies for plant phenotyping. This likely occurs for three reasons. First, some of the latest DL methods require a significant investment in computational power, which cannot be achieved easily in ordinary research labs. Second, original DL solutions might not be directly usable for plant phenotyping applications. Additional efforts are necessary to adopt these advanced DL solutions, and sometimes these efforts are technically challenging. Educational programs are expected to be promoted, so more domain experts  can gain adequate knowledge and skills to expedite the adoption/modification of DL methods for challenging agricultural and biological applications. Thirdly, large private companies, who invest heavily in plant phenotyping, do not disclose their research efforts in this area to the public.3D imaging, an important imaging technique, has not been mentioned yet. An important plant phenotyping task is to characterize and understand plant morphology. While few studies reported the use of CNN in a scenario with 3D imaging, they have primarily focused on the detection in 2D images and projected the detections in 3D for processing, such as removal of redundant detections and determinations of detections with occlusions. None of them really utilized CNNs for plant morphology characterization and understanding. In particular, 3D point clouds can be collected using various approaches (such as LiDAR and photogrammetric methods) in plant phenotyping applications, and most of them need to be analyzed using conventional 3D processing methods. One possible reason is that even the DL community has not delivered many reliable tools for 3D point cloud processing. PointNet and PointNet++ are pioneering work for processing 3D point clouds, but they are limited to the number of points in each model (a couple of thousand points). If the point cloud is too large, there is no efficient computational solution for network training and inference. Thus, much 3D imaging work requires technical development from the DL community.In this review, CNN-based solutions to image-based plant phenotyping were comprehensively reviewed to provide advantages and disadvantages of using them for different tasks of plant phenotyping. Through these studies, CNN-based solutions demonstrated their great potential for solving the most challenging problems encountered in various plant phenotyping applications. In particular, some types of end-to-end CNN architecture have streamlined the process of extracting phenotypic traits from images significantly. This would enable the improvement of data processing and ultimately plant phenotyping applications.Several future research directions that use CNNs for plant phenotyping are identified. The first direction is to enrich the availability of labeled data. Although there are some datasets publicly available , they are not well integrated and designed for agricultural applications. This holds true especially for postharvest quality assessment that utilizes different imaging modalities and has limited samples. The second direction is to customize a deep learning framework that can facilitate the adoption of the latest DL techniques for plant phenotyping applications. Such a framework could provide a common interface for algorithm integration, so that newly developed models and tools can be added for use with little or no development effort, such as visualization tools for model explanation and reinforcement learning for model improvement. Experiences of adopting these newly developed DL methods can be promoted through educational programs and training workshops to advance DL-based data analytics for agricultural applications. The third direction is to adopt and develop CNN architecture for direct 3D and multimodal data processing, especially skeleton extraction, branch-pattern classification, and plant-development understanding.