Varicella zoster virus (VZV) is a neurotropic alphaherpesvirus and the causative agent of varicella (chickenpox) in humans. Following primary infection, VZV establishes latency in the sensory ganglia and can reactivate to cause herpes zoster, more commonly known as shingles, which causes significant morbidity, and on rare occasions mortality, in the elderly. Because VZV infection is highly restricted to humans, the development of a reliable animal model has been challenging, and our understanding of VZV pathogenesis remains incomplete. As an alternative, infection of rhesus macaques with the homologous simian varicella virus (SVV) recapitulates the hallmarks of VZV infection and thus constitutes a robust animal model to provide critical insights into VZV pathogenesis and the host antiviral response. In this model, SVV infection results in the development of varicella during primary infection, generation of an adaptive immune response, establishment of latency in the sensory ganglia, and viral reactivation upon immune suppression. In this review, we discuss our current knowledge about host and viral factors involved in the establishment of SVV latency and reactivation as well as the important role played by T cells in SVV pathogenesis and antiviral immunity. Primary VZV infection results in varicella , a disease characterized by a vesicular rash, fever, headache, and loss of appetite . Like ot vaccine .in vitro studies carried out using the attenuated Oka vaccine strain and in vivo studies utilizing a severe-combined immunodeficient (SCID) mouse model implanted with human fetal tissues (SCID-hu)  . Moreovein vitro  in this model allowed direct inoculation of VZV and resulted in several important insights into VZV pathogenesis . HoweverTo overcome these limitations an alternative animal model was developed where non-human primates are inoculated with Simian varicella virus (SVV), an alphaherpesvirus that causes a vesicular rash in Old World monkeys. SVV and VZV virions have a diameter of 170–200 nm and 80–120 nm, respectively, and are composed of a nucleocapsid of icosahedral symmetry surrounded by a viral envelope . The nucMacaca mulata) to a severe and life-threatening disease associated with high morbidity and mortality rates [cynomolgus monkeys (Macaca fascicularis) and African green monkeys (Chlorocebus sabaeus)] ] . This spabaeus)] , Elephanabaeus)] , and Alcabaeus)] . Moreoveabaeus)] . In contin vivo.Data from several studies carried out using the hu-SCID mouse model strongly suggest a critical role for T cells in VZV dissemination. First, direct inoculation of VZV-infected fibroblasts into human fetal thymus and liver xenografts placed under the kidney capsule of SCID mice revealed that T cells support VZV replication . FurtherIn both rhesus macaques and African green monkeys, different subsets of immune cells, including T cells, were shown to reach the ganglia as early as 3 days post intrabronchial inoculation (dpi) during acute infection , prior tin vitro studies using single-cell mass-spectrometry analysis (CyTOF) have reported that VZV infection of human tonsil T cells leads to upregulation of several immune genes including components of the TCR signaling machinery  virus  virus . Similarmacaques . Infectiresponse . Indeed,in vitro .Intrabronchial infection of rhesus macaques with SVV results in the development of both innate and adaptive immune responses in the lungs concomitant with a decrease in the SVV viral loads observed . The muc®) contains an adjuvanted form of VZV gE that was shown to elicit a robust humoral and cell-mediated immunity (TM induces a lower VZV-specific cell-mediated immunity including a reduced gE-specific memory T cell responses compared to Shingrix®(The anti-SVV T cell responses during acute infection in rhesus macaques is broad with CD8 T cell responses directed mainly against immediate-early (IE) and early (E) viral proteins whereas CD4 T cell responses were mostly specific to late (L) proteins . During immunity . In contShingrix®.The importance of T cell responses during acute infection in the establishment of latency is evidenced by the detection of high level of viral transcription in ganglia of animals depleted of CD4 T cells during acute infection . It shouOther studies have attempted to induce reactivation in SVV-latently infected rhesus macaques using a combination of total body irradiation (2–8 Gy) and immune suppressant regimens (cyclosporine and tacrolimus). In some of these studies, cynomolgus and rhesus macaques were irradiated before receiving tacrolimus and prednisone, resulting in clinical reactivation in 25 and 100% of animals, respectively . In anotFollowing reactivation, SVV antigens were detected in multiple tissues, including skin and lymph nodes in rhesus macaques despite the lack of viremia at the time of HZ . In skinAlthough studies over the last few decades have led to significant advances in our understanding of VZV pathogenesis, several questions remain unanswered. Specifically, although it is now well established that that T cells play a critical in the pathogenesis of both VZV and SVV, the exact mechanisms by which VZV/SVV modulate T cell functions to alter their migratory properties and confer ability to access into the central nervous system are not known. Furthermore, the viral and cellular factors that control establishment and maintenance of SVV/VZV latency in sensory ganglia remain poorly understood. Notably, the role of the ORF61 anti-sense transcript during the transition from lytic to latent phases has yet to be investigated. Similarly, the role of epigenetic modifications (such as histone/DNA methylation or histone acetylation) in the maintenance of latency remains to be studied. Future studies should uncover the impact of persistent transcriptional changes within the ganglia on neuronal function. SVV infection in rhesus macaques provides a model well-suited to further our knowledge of varicella viruses’ pathogenesis. The availability of this model together with a versatile bacterial artificial chromosome  that facOS and IM wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The idiosyncratic nature of drug-induced liver injury (DILI) represents a current challenge for drug developers, regulators and clinicians. The myriad of agents  with recognized DILI potential not only strengthens the importance of the post-marketing phase, when urgent withdrawal sometimes occurs for rare unanticipated liver toxicity, but also shows the imperfect predictivity of pre-clinical models and the lack of validated biomarkers beyond traditional, non-specific liver function tests. After briefly reviewing proposed key mechanisms of DILI, we will focus on drug-related risk factors  recently proposed as predictors of DILI and use cyclin-dependent kinase 4/6 inhibitors, relatively novel oral anticancer medications approved for breast cancer, as a case study to discuss the feasibility of early detection of DILI signals during drug development: published data from pivotal clinical trials, unpublished post-marketing reports of liver adverse events, and pharmacokinetic properties will be used to provide a comparative evaluation of their liver safety and gain insight into drug-related risk factors likely to explain the observed differences. Drug-induced liver injury (DILI) is a public health issue of utmost interest for drug companies, regulatory agencies, and hepatologists: though from different perspectives, all these stakeholders are concerned with early and timely identification of liver damage both during drug development and in clinical practice.The most challenging form of DILI is the so-called idiosyncratic one, because, by definition, it is unpredictable: it is usually unrelated to the dose  guideline: a predictive algorithm assembling drug- and host-related factors, as well as mechanistic considerations, is awaited  providing brief key insights into proposed mechanisms of idiosyncratic DILI, focusing on drug-related risk factors ; b) using cyclin-dependent kinase (CDK)4/6 inhibitors, relatively novel oral anticancer medications approved for breast cancer, as a case study to discuss the feasibility of early detection of DILI signals during drug development. Published data from pivotal clinical trials, unpublished post-marketing reports of liver adverse events, and pharmacokinetic properties will be used to provide a comparative evaluation of their liver safety and gain insight into drug-related risk factors likely to explain the observed differences.The diagnosis of DILI is particularly challenging because it is largely based on exclusion of other causes: the timing of the onset of injury after the administration of implicated agent (latency), resolution after the drug is stopped , recurrence on re-exposure , knowledge of the agent’s potential for hepatotoxicity (likelihood), and clinical features (phenotype) are the major diagnostic elements . There aDetermining the true incidence of hepatotoxicity by medicinal products remains problematic, also because epidemiological estimates depend on local pattern of prescriptions. Despite increasing awareness by stakeholders and advancements in designing less hepatotoxic compounds, the occurrence of hepatotoxic reactions appears to be stable over time, likely reflecting increased prescriptions and available medications .The list of drugs associated with hepatotoxicity is ever-growing  and inclDifferent DILI studies are collecting prospective data through population-based design and dedicated registries: the former found large differences in the incidence rate  and drug-related risks (highest for azathioprine and infliximab in Iceland); the latter consistently identified antibiotics as the most frequently implicated drug class and hepatocellular pattern as the most common pattern of liver damage . Recent Garcinia cambogia have been recently identified as novel hepatotoxic compounds, possibly causing acute liver failure  is emerging as a worldwide epidemic, not only in Asia but also in the United States and Europe.  failure , and an  failure .Drug development is facing a major paradigm shift, especially in oncology with the introduction of immunotherapy. The increasing demanding costs to achieve marketing authorization was not accompanied by a parallel increase in the rate of introduction of new molecular entities: the reported mean likelihood of approval for drugs entering clinical development for diverse disease areas during the period 2006 to 2015 was 9.6%, with a very low probability of success (<3%) for antineoplastic, immune-modulating, and nervous system agents . AlthougDILI is erroneously considered to be among the most frequent causes of late-stage drug development interruption . The casThus, the answer to the question in this section’s subtitle is probably no, and cardiotoxicity still remains one of the main reasons for drug development termination, both during pre-clinical and clinical stages. The reason for this most likely lies in the fact that significant advancement in understanding the mechanistic basis of cardiotoxicity prompted the refinement of new strategies with higher sensitivity and specificity to early detect cardiac liabilities . The expThe imperfect prediction of DILI risk during drug development makes the post-marketing phase vital to early identification of liver safety signals . TherefoOn November 9, 2017, the Pharmacovigilance Risk Assessment Committee of the European Medicines Agency (EMA) recommended restrictions on the use of the daclizumab, with strict liver monitoring due to unpredictable and potential fatal immune-mediated liver injury up to 6 months after stopping the drug. On March 7, 2019, the EMA also recommended immediate suspension of the medicine’s marketing authorization in the EU and a recall of batches from pharmacies and hospitals following 12 cases of serious inflammatory brain disorders , including encephalitis and meningoencephalitis; the daclizumab case is paradigmatic of the importance of proactive post-approval safety monitoring to early and timely intercept idiosyncratic clinically significant cases of DILI .Animal models of DILI hold great promise and expectations for accurate prediction because they can theoretically gain insights into mechanistic bases. Besides ethical issues, the study of DILI in animals poses substantial technical challenges .Three major approaches rely on induction of inflammation, suppression of immune tolerance, or genetic manipulation of mitochondrial function . More rein vitro models investigated in DILI research, especially for drug-induced cholestasis. However, their inherent limitations  make it unlikely that they will fully replace animals for DILI research. Several in vitro assay systems have been developed especially to investigate inhibition of hepatic transporters (see below): the reader is referred to an extensive review on the various pre-clinical models, differing in their goal, complexity, availability, applicability, and relevant predictivity to get closer to real hepatocyte phenotype , and feasibility issues .The threshold for signal detection of DILI in clinical trials is still debated and evolving. In patients without underlying liver disease and liver chemistry being normal at baseline, DILI should be suspected if aminotransferases exceed 3× ULN, triggering close observation and workup for alternative causes. In 2011, a cutoff value of ALT > 5× ULN was proposed for DILI signal in the absence of liver-related symptoms or elevated serum total bilirubin (TBL) . This hiThere is uncertainty related to identify and manage DILI signals in patients with pre-existing chronic liver disease, and debate exists whether these individuals have higher susceptibility to DILI . In thisUse of multiples of baseline ALT rather than multiples of ULN was suggested as a threshold for suspecting DILI . Moreovehttps://www.fda.gov/media/116737/download).Hy’s law still represents the most sensitive and specific predictor of a drug’s potential to cause severe hepatotoxicity, and is recognized as a key biomarker in drug development: the FDA’s Guidance on DILI, underlined that finding two Hy’s law cases during clinical development is highly predictive of severe DILI in the post-marketing phase 2 × h)] to calculate the extent of hepatocyte loss during an acute DILI event through the maximum value and the AUC of serum ALT observed or estimated , and converge on the involvement of adaptive immune system pathways . Moreovea posteriori once remission with corticosteroids is achieved: drug-induced autoimmune hepatitis does not usually relapse after withdrawal of immunosuppressive therapy.The involvement of the immune system is corroborated by different lines of evidence: 1) the large number of genome-wide association studies and candidate gene approaches identifying specific genetic susceptibility and correlations between human leukocyte antigen (HLA) polymorphisms and DILI occurrence  the The common view postulated that an interplay between drug properties and host factors may play a crucial role in occurrence of DILI : susceptThere is a large body of evidence indicating that RMs are implicated in the pathogenesis of DILI and other idiosyncratic adverse events . TherefoThe fact that the dose  may play a role in DILI was highlighted in 1999 by in vivo models (Different studies have investigated the relationship between daily dose and lipophilicity (often measured as the log of octanol–water partition coefficient [LogP]), referred to as the “rule-of-two” (RO2): drugs with highly lipophilicity (logP ≥ 3) and a daily dose ≥100 mg/d are associated with increased risk of DILI . Notablyo models .via multiple mechanisms. A comprehensive analysis of 228 compounds found that the predictive performance of the mitochondrial assays is superior for hepatotoxicity versus cardiotoxicity and nephrotoxicity, when the analysis was done at 100* Cmax, and LogP emerged to be significantly associated with mitochondrial toxicity , a correlation was observed between the potency of in vitro BSEP inhibition and its propensity to cause DILI in humans, although discrepancies exist in which methods to use and the extent to which BSEP inhibition predicts clinical DILI  and in vivo drug exposure. Both parameters are challenging to be determined experimentally, and there is debate on the BSEP IC50 cutoff values to identify “concerning level” of BSEP inhibition (from 25 to 300 µM). The latest international transporter consortium perspective proposed IC50 < 25 µM during the drug discovery phase to indicate the need to further explore potential correlation with maximum total plasma concentration  during early clinical drug development  opening and direct impairment of oxidative phosphorylation process, which can induce necrosis and/or apoptosis thereby leading to cytolytic hepatitis, as well as inhibition of mitochondrial fatty acid oxidation (FAO), by direct inhibiting FAO enzyme, indirectly compromising mitochondrial respiratory chain activity, and causing depletion or damage of mitochondrial DNA, thus finally resulting in microvesicular steatosis and steatohepatitis . Notablytoxicity . Howevertoxicity . Inhibitcal DILI ; moreoveelopment . For ins failure . It was  failure . When BS failure .The role of concomitant drugs warrants a final remark. In clinical practice, determination of the most likely causative agent is an achievable clinical task , although disentangling the role of drug interactions in DILI onset among poly-treated individuals is not straightforward, apart from the case of a drug with recognized modulating effect on metabolism (inhibition or induction of cytochrome activity). The analysis of the WHO pharmacovigilance database described the liver event reporting frequency of drugs commonly associated with hepatotoxicity and suggested both beneficial (TNF inhibitors/folic acid and isoniazid) and detrimental  interactions . HoweverCDKs were expected to be key therapeutic targets in cancer and pan-CDK inhibitors were initially designed, albeit with disappointing results . The devIn general, CDK4/6 inhibitors share different chemical and pharmacokinetic features, including metabolism mediated by CYP3A4 , and biliary clearance as the main elimination pathway Table 1.The most common side effect for palbociclib and ribociclib is neutropenia, whereas gastrointestinal toxicity is associated especially with abemaciclib . These differences may be particularly relevant in the adjuvant setting where even grade 2 diarrhea may be considered unacceptable compared with asymptomatic grade 4 hematological toxicities . Higher These recommendations on liver monitoring under ribociclib originated from data from pivotal phase III trials, in particular MONALEESA-2, where four cases of Hy’s law were confirmed (three suspected to be related to study treatment) : two casBased on these data from pre-marketing clinical trials, there is interest in determining the existence of a specific drug-related liver toxicity rather than a class effect. Therefore, we carried out a two-fold “from bedside to bench” approach.https://www.fda.gov/drugs/questions-and-answers-fdas-adverse-event-reporting-system-faers/fda-adverse-event-reporting-system-faers-public-dashboard, searches performed on 07/06/2019; data as of March 31, 2019). It is important to quickly remind here about the drawbacks of this analysis, especially considering the different time on the market of the three anticancer drugs. Because of these inherent limitations, including data quality , the likelihood of under-reporting, the potential influence of external factors (time on the market and media attention), the lack of exposure data (drug prescription/consumption), and inability to establish firm causality, incidence, risk assessment, and risk ranking cannot be provided. These data only provide a general picture of the current liver reporting pattern with CDK4/6 inhibitors. Second, we collected publicly available information on chemical and pharmacokinetic features of CDK4/6 inhibitors, previously discussed to likely contribute to DILI occurrence: this critical insight into pharmacovigilance and pharmacological data would potentially reveal differences among the three compounds and related contributing factors to advise on further investigation for better understanding the mechanistic basis.First, we used the public dashboard of the FDA adverse reporting system (FAERS) to extract adverse events suspectedly attributed to CDK4/6 inhibitors and describe their current reporting pattern in the real-world  and HepatoPred  were used to verify whether CDK4/6 inhibitors share similar “pharmacophores,” suggesting DILI risk: they were all classified as “potential hepatotoxic”, with the exception of abemaciclib resulting as “uncertain” in ADVERPred. These findings suggest that the three agents are likely to possess SAs and generate RMs, which have recognized role in idiosyncratic DILI occurrence, although there are no dedicated published studies to our knowledge.A synopsis of collected physiochemical and pharmacological features is presented in However, the RO2 failed for ribociclib and palabociclib, but was positive for abemaciclib, likely due to the high lipophilicity of the drug. In the light of these discrepancies and considering that the DILI risk model by in vitro assays up to 100*Cmax (in vitro inhibition with in vivo relevance), especially BSEP. In particular, ribociclib causes dual inhibition of BSEP and basolateral efflux systems , which are additional susceptibility factors for cholestasis. Conversely, palbociclib does not inhibit BSEP, and the inhibitory effect of abemaciclib on these transporters was not tested during drug development, and no data are published so far to our knowledge.As regard drug-related properties potentially indicating non-immunological DILI mechanisms, only palbociclib was tested for mitochondrial toxicity and emerged with negative liability in 100*Cmax . Conversa priori identification of both host factors and pharmaceutical features conferring a DILI risk has led to the development of numerous cell-based systems, animal models, and in silico algorithms. Notwithstanding these efforts, our mechanistic understanding is still imperfect, and both immune and non-immune factors may synergistically interact by increasing DILI susceptibility and its eventual occurrence.Idiosyncratic DILI is a current challenge for drug developers, as demonstrated by the various collaborative initiatives (public–private partnerships) aiming at minimizing drug attrition. The quest for predictive tools to in vitro findings do not inform on the underlying mechanism, and correlation does not necessarily mean causation), these data should not be viewed as a “stop-or-go” criterion toward marketing authorization, but rather as an early risk minimization strategy to direct post-marketing phase and timely intercept a potential liver signal. At present, there is room for improvement both in the FDA and EMA regulatory guidelines; the former, published in July 2009, addresses only the pre-marketing clinical evaluation (https://www.fda.gov/media/116737/download), whereas the latter, dated July 2010, is a reflection paper providing a general perspective \and stating that “standard non-clinical toxicity studies are the cornerstone of preventing of hepatotoxicity in humans” . Conversely, both FDA (https://www.fda.gov/media/82734/download) and EMA (https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-drug-interactions_en.pdf) guidelines on the pre-marketing investigation of drug–drug interactions specifically recommend testing drugs for BSEP inhibition and other hepato-biliary transporters. An updated unified comprehensive DILI guideline is warranted to create an integrated DILI risk assessment  project, which has created the largest reference drug list ranking  by annotating severity and causality of 1036 drugs , with promising results, as compared with RUCAM, in discriminating the actual culprit agent in subjects taking multiple medications , comparable to that observed for ribociclib. While inhibitory property on hepatic transporters by ribociclib potentially suggests the hypothesis of a non-immunological mechanism, cases of autoimmune hepatitis emerging from MONALEESA-2 trial and recorded in the FAERS database do not allow to rule out an immune-related etiology and strengthen the importance of: a) investigating the role of immune tolerance using the aforementioned animal models; b) conducting multicenter post-authorization safety studies specifically devoted to assess liver safety in subjects using CDK4/6 inhibitors. In fact, despite possessing the most favorable pharmacological property , hepatic failure with palbociclib was recorded in a quarter of liver reports in FAERS: these findings, together with the potential occurrence of pseudocirrhosis with liver failure recently documented in two patients , strengtDedicated pharmacovigilance studies should be designed to better characterize the reporting pattern of idiosyncratic DILI, accounting for major bias  and correlate the observed reporting frequency with binding affinities  and all pharmacokinetic parameters  to actually verify the putative relationship between the risk (reporting) of liver damage and pharmacodynamics/pharmacokinetics. We believe that this approach  can be extended to other promising oral anticancer drugs for breast cancer  to timely identify DILI signals and early intercept specific drug signatures.ER and FP contributed to the conception and design of the review. ER collected and analyzed the data, and provided the first draft of the manuscript. FP revised the manuscript for important intellectual content. Both authors contributed to final manuscript revision, and read and approved the submitted version.No sources of funding were used to assist in the preparation of this study. The authors are supported by Institutional Research Funds of the University of Bologna .ER reports personal fees from Novartis (consultancy for drug-induced liver injury). The remaining author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Reactive oxygen species (ROS) are well known for their capacity to cause DNA damage, augment mutagenesis, and thereby promote oncogenic transformation. Similarly, agents that reduce ROS levels (antioxidants) are frequently thought to have anti-cancer properties given their propensity to minimize DNA damage and mutagenesis. However, numerous clinical studies focused on antioxidants suggest that this is a facile premise and that antioxidant capacity can be important for cancer cells in a similar fashion to normal cells. As a consequence of this realization, numerous laboratories have been motivated to investigate the biological underpinnings explaining how and when antioxidant activity can potentially be beneficial to cancer cells. Relatedly, it has become clear that the reliance of cancer cells on antioxidant activity in certain contexts represents a potential vulnerability that could be exploited for therapeutic gain. Here, we review some of the recent, exciting findings documenting how cancer cells utilized antioxidant activity and under what circumstances this activity could represent an opportunity for selective elimination of cancer cells. Dietary intake of compounds such as vitamin A, vitamin C, vitamin E and β-carotene has long been associated with a diminished risk of developing a variety of human cancers ,2,3. It Curiously, clinical studies examining the hypothesis that dietary intake of antioxidants antagonizes or limits tumorigenesis suggest that this premise is overly simplistic in some cases and outright incorrect in others. For instance, in 1985, an eight-year clinical trial including over twenty-nine thousand male smokers between the ages of 50 to 69 was executed to investigate the anti-cancer effects of beta carotene (BC), a precursor of vitamin A with strong antioxidant properties . ParticiThe fact that the data obtained from these clinical trials do not lead to a general conclusion regarding links to the consumption of dietary antioxidants and tumor development is perhaps not surprising. Indeed, understanding the basic biological mechanisms that may underlie these findings is complicated by a number of factors. The selection of specific antioxidant molecules, the limited number of agents tested to date, and the use of pharmacological (in lieu of dietary) doses all complicate the interpretation of these data and any efforts to make more generalized conclusions . That be1 cell-cycle arrest, and subsequent induction of cell death. Similar findings using compounds with antioxidant capacity and cytotoxic chemotherapies  were observed in cervical, ovarian, and lung cancer cells as well [For many years, numerous laboratories have investigated the possibility that antioxidant compounds, when delivered in combination with certain cancer therapies, could function synergistically to eliminate cancer cells. There have certainly been promising findings amid these efforts. For example, a study utilizing the antioxidants pyrrolidinedithiocarbamate (PDTC) and vitamin E in combination with DNA-damaging chemotherapeutic agents (5-fluorouacil (5-FU), doxorubicin) investigated various combinatorial regimens efficacy against colorectal cancer cells . The aut as well . However as well .For instance, in a number of distinct cancer contexts, the stabilization of the nuclear factor erythroid 2-related factor 2 (Nrf2) transcription factor, a master regulator of the intracellular antioxidant program and redox homeostasis, can facilitate the development of chemoresistance . Under nMore recently, a number of elegant studies have revealed that alterations in cancer cells that promote the stabilization of Nrf2 and a concomitant antioxidant response can promote chemotherapeutic resistance. Interestingly, upregulation of iASPP, a known inhibitor of p53, is correlated with the advanced stages of multiple malignancies, such as glioma, prostate cancer, and melanoma . It alsoIn further support of the idea that antioxidant capabilities can be beneficial for cancer cells are multiple, recent, high profile studies that link antioxidant activity and tumor progression. This area of inquiry was perhaps initiated by a seminal study published in 2011 demonstrating a direct relationship between activation of K-Ras, B-Raf, or Myc, an increase in Nrf2 levels, and the consequent elimination of ROS . This stAdditionally, recent research has demonstrated that high doses of vitamin C induce cell death in colorectal cancer cells with oncogenic mutations in K-Ras or B-Raf . The mecHexokinase 2 (HK2) and Gapdh which results in metastasis dependent upon glucose metabolism (null (NSG) mice, the other study demonstrated that NAC treatment promoted melanoma metastasis while having no significant effect on the size of the primary, subcutaneous tumors [Expanding on these exciting findings, multiple studies have now contrasted the impact of antioxidant activity on cancer cells present in metastatic lesions with the necessity of ROS neutralization at the site of the primary tumor. In K-Ras and B-Raf-driven mouse models of lung cancer, it was discovered that dietary antioxidant supplementation could enhance tumor progression and reduce survival . Mechanitabolism . On the s tumors . The undAs discussed above, there is now abundant evidence indicating that antioxidant activity can promote tumor progression and metastasis in certain contexts. While there are undoubtedly numerous mechanisms underlying this relationship between diminished ROS and tumor progression, one context in which antioxidant activity has been found to be particularly important is in the absence of integrin-mediated attachment to extracellular matrix (ECM). Normally, ECM-detachment results in the activation of a caspase-dependent cell death process known as anoikis . HoweverThe observation that ECM-detached cells lacking the capacity to undergo anoikis could still die in a programmed fashion was made in MCF-10A cells grown in three-dimensional culture as mammary acini ,41. StudOver the years, additional studies have uncovered additional mechanisms involved in redox homeostasis during ECM-detachment. In addition to the observed changes in glucose metabolism, glutamine oxidation was found to be impaired in ECM-detached cells. Instead, reductive formation of glutamine-derived citrate is enhanced in a fashion that is highly dependent on cytosolic isocitrate dehydrogenase-1 (IDH1) . In addi2+ influx in response to ROS generation which results in elevated expression of the anti-apoptotic protein Mcl-1 and cancer cell survival. While TRPA1 is a direct transcriptional target of Nrf2 and does respond to the elevation of ROS levels, this mechanism by which higher levels of ROS are tolerated does not appear to involve regulation of the quantity of ROS. Instead, this mechanism counteracts the capacity of ROS to trigger apoptosis by inducing upregulation of Mcl-1. Extending these findings to sensitivity to cancer therapies, TRPA1 was found to promote resistance to the traditional, platinum-based chemotherapeutic carboplatin through a mechanism dependent on the Ca2+-dependent anti-apoptotic mechanism. This observation aligns with other studies investigating the relationship between chemotherapeutic treatments and antioxidant activity and provides additional evidence of circumstances in which antioxidant response programs can protect cancer cells from death induced by chemotherapy.Despite the fact that all of the aforementioned studies in ECM-detached cells involve altered intracellular metabolism to regulate the antioxidant machinery, recent work has uncovered a mechanism that permits tolerance to oxidative stress in the absence of alterations in the abundance of ROS . FocusinFurthermore, metabolic reprograming is not limited to ECM-detachment and is, more broadly, considered an emerging hallmark of cancer cells used to promote cell growth, survival, proliferation, and maintenance . MetabolOther recent studies have observed additional non-traditional mechanisms by which metabolic pathways are altered in cancer cells in a fashion that promotes redox homeostasis. For example, inhibition of lactase dehydrogenase A (LDHA), canonically known for its role in converting pyruvate to lactate at the final steps of glycolysis, was found to cause an elevation in intracellular ROS that are derived from oxidative phosphorylation . More reAnother gene known to functionally link alterations in metabolism in cancer cells to a vulnerability to alterations in redox metabolism is ARID1A . Loss ofMultiple additional studies also touch on glutathione synthesis as a potential vulnerability in cancer cells. GSH synthesis was initially identified as critical for tumor initiation where interfering with GSH production ahead of tumor initiation could slow tumor growth . This vuSimilar to the vulnerability to GSH inhibitors discovered in ARID1A-deficient cancer cells, the iron exporter ferroportin (FPN) has been observed to be dysregulated in tumor cells. Later stage breast, prostate, ovarian, colorectal, and multiple myeloma cancers have been associated with low FPN expression relative to neighboring healthy tissues ,66,67,68One of the critiques of the unsuccessful clinical trials examining the effects of antioxidants on individuals at high risk for cancer was the use of pharmaceutical reagents as opposed to antioxidants derived from normal dietary components. Many natural compounds are a genuine source of bioactive compounds and many have been demonstrated to have anti-cancer activity ,74. WithIn addition to RE, the naturally occurring compound phenethyl isothiocyanate (PEITC), found mostly in cruciferous vegetables, has been investigated for anti-cancer activity by modulating intracellular ROS . In tranAs discussed here, oxidative stress can function as a barrier to tumor progression due to its capacity to induce deleterious changes to cancer cells. Although antioxidant supplementation was once thought to provide clinical benefits for cancer patients, the data to support such a model are decidedly mixed. Mounting evidence suggests that antioxidant supplements can aid tumor cells much in the same way that they can aid normal cells. Additionally, rewiring of the endogenous antioxidant program can significantly impact the sensitivity of cancer cells to any exogenous manipulations in levels of oxidative stress. Among the most important factors is Nrf2, as its activity is observed to play a crucial role in promoting cancer cell survival and chemotherapeutic resistance in numerous and distinct contexts. This activity includes canonically inducing the transcription of antioxidant genes as well as promoting increased calcium uptake to inhibit apoptotic induction and tolerate intracellular ROS. In addition to promoting Nrf2 stabilization, oncogenic signaling can also engage factors responsible for migration, invasion, and metabolic reprogramming to produce reducing agents that neutralize ROS. Numerous perturbations in either intracellular antioxidant genes or genes that can influence redox homeostasis are present in cancer cells, and when targeted they reveal a vulnerability suggesting that low ROS are a requisite part of their survival. Taken together, the findings discussed here give credence to the idea that therapeutic approaches designed to elevate ROS levels may ultimately have some specificity towards tumor cells. Ultimately, despite the significant advances discussed here, much work remains to determine the precise context(s) are dependent on antioxidant activity. As things currently stand, the basic biology is not sufficiently understood to allow for meaningful translation of these findings into cancer patients. Nonetheless, the promise of selectively targeting the reliance of cancer cells on antioxidant activity for therapeutic gain is an exciting and innovative idea that warrants further investigation.


Background: Northern New South Wales in Australia is a “hotspot” for natural disaster declarations with recent extensive flooding in early 2017. With limited knowledge about how climate change affects mental health and resilience, robust local assessments are required to better understand long-term impact, particularly in communities prone to extreme weather events.Methods: Six months post-flood, a cross-sectional survey of adults living in the region during the flood was conducted to quantify associations between flood impact and psychological morbidity (post-traumatic stress (PTSD), anxiety, depression, suicidal ideation) for different exposure scenarios, and respondent groups. We adopted a community-academic partnership approach and purposive recruitment to increase participation from marginalized groups.Results: Of 2,180 respondents, almost all (91%) were affected by some degree of flood-related exposure at an individual and community level (ranging from suburb damage to home or business inundated). Socio-economically marginalized respondents were more likely to have their homes inundated and to be displaced. Mental health risk was significantly elevated for respondents: whose home/business/farm was inundated ; who reported multiple exposures ; and who were still displaced after 6 months .Conclusion: The 2017 flood had profound impact, particularly for respondents still displaced and for socio-economically marginalized groups. Our community-academic partnership approach builds community cohesion, informs targeted mental health disaster preparedness and response policies for different sectors of the community and longer-term interventions aimed at improving community adaptability to climate change. There is compelling evidence and wide consensus that anthropogenic activities are causing climate change, leading to more frequent extreme weather events with adverse consequences for public health, disproportionately so for the poorest populations , 2. In aRisk of climate change effects and adverse impacts are known to exacerbate existing inequalities in all countries regardless of their level of development , 6. LandFloods are the most expensive weather-related event in Australia with an average annual damage bill of over $300 million . Such anIn Australia, inequality in the distribution of income and wealth has resulted in sectors of the community experiencing significant poverty, disproportionately so within the Aboriginal and Torres Strait Islander population , 16. Comflood impact on mental health framework” (the framework)  . It descamework) . Our objamework) . The proThis paper presents initial results from the project and contributes new knowledge by quantifying the associations between intensity of fluvial flood exposure (how many sites of importance were flooded) and five mental health problems. These include two directly event-linked problems [still distressed about the flood and flood-related post-traumatic stress disorder (PTSD)] and illustrates how these associations vary according to socio-economic circumstance. There is also opportunity to contribute learnings to an international initiative tracking health impacts from climate change .A cross-sectional survey was undertaken 6 months after flooding in communities within six Northern NSW Local Government Areas   which haThe project's community-academic partnership approach was integral to the design, recruitment to and implementation of the study . It inclThe survey was available online and in paper form between September and November 2017. The online version of the survey, suitable for use on computers and mobile telephones, was generated using Qualtrics software . Potential respondents were provided with participant information and advised that completion of the questionnaire would signify consent to participate in the study.We utilized a purposive snowball sampling technique to recruit respondents via personal, social and local organizational networks, the CAGs and other business groups and community organizations. This was supplemented by an extensive local media campaign , advertising campaign and a door-to-door survey conducted at the end of the recruitment period in randomly selected neighborhood blocks from flooded areas of Lismore and Murwillumbah  . The advOur aim was to recruit participants from the local community experiencing different degrees of flood impact, including the key groups described earlier, some of which are hard to reach via conventional sampling strategies. Where certain subgroups are few in number and a degree of trust is required to support their participation, community-partnered snowball sampling approaches or “ascending” methods (working from the ground up) are preferable to “descending” methods, such as household surveys , 21. As The questionnaire included participants' socio-demographic characteristics, flood exposure measures (including evacuation and displacement) and mental health screening tools. Socio-demographic data were age, sex, Aboriginal, and Torres Strait Islander status, relationship status, employment status, type of income support payments, and educational qualifications.a priori and included self-reported damage to five physical infrastructure sites: suburb; non-liveable areas of their home ; liveable areas of their home ; income-producing property (business/farm); and the home of a significant other as well as evacuation and length of displacement. Those who did not indicate any of these exposures were termed “non-exposed” and this group formed the internal comparison against which exposed groups were compared. To examine cumulative impacts, we derived a cumulative exposure index for individuals by summing the number of damage sites experienced. The index ranged from zero (no sites damaged) to five .Flood exposure measures were selected We measured health status using brief clinical screening tools for depression, anxiety, and post-traumatic stress. The Patient Health Questionnaire (PHQ-2) for depression has previously shown acceptable diagnostic accuracy, reliability, construct and criterion validity, and sensitivity to change in primary care and other clinic settings in western countries , 24. TheA total of 2,530 people responded to the survey (76% online), 350 (14%) of whom were excluded from the primary analyses because of missing socio-demographic data, leaving a final sample of 2,180. Minimal differences in parameter estimates and no differences in patterns of results were found between the full dataset and the dataset with missing socio-demographic records removed . Respondp-value was set conservatively at <0.01. Stata  was used for statistical analysis.Separate binary logistic regression models were constructed to calculate the odds of experiencing symptoms (yes/no) related to five types of mental health problem  by single exposure  as well as cumulative flood exposure relative to the non-exposed group. We adjusted the models for all measured socio-demographic characteristics. Potential interactions between these characteristics were checked for significance. Respondents who did not complete a health outcome measure were excluded from analysis for that indicator only. Adjusted predictions of the probability of reporting a mental health outcome for different levels of exposure were calculated by using the marginal standardization method. As we conducted multiple analyses, the n = 315) of respondents reported being displaced and 4% (n = 85) were still living elsewhere 6 months after the flood . Around three-quarters reported suburb damage and almost two-thirds had a home of a significant other flooded . Liveablhe flood .Over one-fifth (22%) of respondents reported being still distressed about the flood, 16% with probable anxiety, 15% probable PTSD, 15% probable depression and 7% suicidal ideation. Around 27% of respondents reported at least one of these and about 20% reported two or more of these problems. The odds of any mental health problem were significantly elevated across most exposure measures compared with the non-exposed group, particularly those whose homes and/or businesses/farms were evacuated or flooded and those who were still displaced after 6 months . RespondIncreasing intensity of exposure, as indicated by the cumulative exposure index, was associated with the likelihood of progressively worse mental health . For exan = 129) did so within 4 days. Compared to short-term evacuees, those displaced for longer than 6 months were twice as likely to report being still distressed and having symptoms of PTSD, anxiety and depression .Our findings are in keeping with those of previous studies describing how flooding across different scenarios of impact can harm mental health –32. For There was an exponential increase in the likelihood of respondents experiencing continuing distress and flood-related PTSD with each additional exposure. For example, while there was no substantial difference in mental health outcomes between respondents experiencing one exposure compared to non-exposed, those reporting three exposure sites  had, respectively, five and six times the odds of reporting continuing distress and PTSD. Further, while immediate-term evacuation and displacement are known stressors , 32, ourIn our study, Aboriginal and Torres Strait Islander respondents and respondents in receipt of income support fall disproportionately within the high-risk sub-group described above. It is recognized that elevated risk of psychological morbidity is pre-existing for these groups due to their poorer underlying health and socio-economic status . This doOur findings have improved understanding of the local context by highlighting the relationship between severity of flood exposure and mental health outcomes, including for respondents most in need. Joint design and analysis of the study with community representatives has enabled the sharing of knowledge and recognition of strengths and gaps in local policy and practice, particularly for at-risk groups. For example, NSW emergency services engage with non-government welfare agencies to provide immediate post-disaster support. Our findings underscore the importance of these initiatives and indicate the additional necessity for first responders to be able to assess and react appropriately to multiple or high-risk exposures. Care pathways that are individually tailored and sensitive to specific exposures and risk factors may be more effective in preventing the onset of symptoms and in promoting recovery. In addition, the focus of disaster recovery programs needs to be extended beyond the immediate aftermath given research has shown that mental health problems persist for many years . AnecdotMore generally, a multi-sectoral agency approach in disaster preparedness and response, consistent with the guidelines from the Sendai Framework, should be used to promote flexible services adapted to meet the needs of community members according to their economic and social circumstance . For heaOur capacity to generalize our findings to other settings has limitations. This is a self-report, cross-sectional design which constrains our ability to make causal inferences: pre-existing mental health status can bias responses and we cannot be sure flood experiences directly caused outcomes . FurtherWe included two mental health measures specifically related to the flood (including PTSD) as well as general measures of depression, anxiety, and suicidal ideation, and we adjusted our analyses by a wide variety of socio-economic factors known to predict psychological morbidity . A partiSix months after the 2017 Northern NSW flood event, survey respondents revealed a substantial continuing mental health burden; we have characterized and quantified this burden and its inequitable distribution in a rural Australian context. The community-academic partnership approach used in this study means that local communities helped generate the knowledge they need to begin work to address the findings. In the context of climate change, weather disasters will become increasingly frequent, intense, and unpredictable with the potential for correspondingly severe effects on mental health. A recent systems framework highlights the complexity of interactions between climate change and mental health . Such frThe datasets generated for this study are available on request to the corresponding author.The study was approved by the University of Sydney Human Research Ethics Committee (reference-2017/589) and the Aboriginal Health and Medical Research Council Human Research Ethics Committee (reference-1294/17). Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.VM performed the data analysis. VM, JL, and HB interpreted the data and drafted the manuscript. All authors contributed to the study design, critically reviewed draft versions and provided important intellectual content during revisions, and accept accountability for the overall work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: The clinical and etiological heterogeneity of mood disorders impede identification of effective treatments for the individual patient. This highlights a need for early neuronal and behavioral biomarkers for treatment efficacy, which can provide a basis for more personalized treatments. The present systematic review aimed to identify the most consistent neuronal and behavioral predictors of treatment efficacy on mood symptoms and cognitive impairment in mood disorders.Methods: We identified and included 60 original peer-reviewed studies investigating neuroimaging and behavioral predictors of treatment efficacy within the domains of emotional and non-emotional cognition, structural neuroimaging, and resting state functional connectivity in patients with unipolar or bipolar disorder.Results: Lower baseline responsivity in limbic regions coupled with heightened medial and dorsal prefrontal responses to emotional stimuli were the most consistent predictors of response to pharmacotherapy for depression. In contrast, heightened limbic and ventral prefrontal reactivity to emotional stimuli seemed to predict efficacy of psychological interventions. Early modulation of fronto-limbic activity and reduction in negative bias were also associated with treatment response. Better performance on non-emotional tests at baseline was relatively consistently associated with efficacy on mood symptoms, whereas the association between neural activity during non-emotional tests and treatment response was less clear. Other baseline factors associated with treatment response were greater white matter integrity, resting state functional connectivity, more prefrontal gray matter volume as well as an early increase following short administered treatment. Finally, emerging evidence indicates that baseline cognitive deficits are associated with greater chances of achieving treatment efficacy on cognition.Conclusions: Patients' profile of emotional and non-emotional cognition and neural activity—and the early treatment-associated changes in neural and cognitive function—may be useful for guiding treatments for depression. While cognitive deficits at baseline seem to improve chances of treatment efficacy on cognition, more studies of this association are urgently needed. Unipolar depression (UD) and bipolar disorder (BD) are among top contributors to the global burden of disease, with UD being the single largest contributor to global disability worldwide . At a glPresently, first-line treatments for mood disorders include pharmacological treatment with selective serotonin reuptake inhibitors (SSRI) and/or evidence-based psychotherapy, such as cognitive-behavioral therapy (CBT) . HoweverThe clinical and etiological heterogeneity of patients with mood disorders implicates distinct pathophysiological profiles for each individual patient , 13. ThiMore recently, studies have begun to investigate treatments that directly target residual cognitive impairments in mood disorders. Specifically, recent studies have found global or selective cognitive difficulties in 50–70% remitted patients with mood disorders, and poorer quality of life, more stress and impaired work capacity in cognitively impaired patients relatively to those who are “cognitively intact” . While tTaken together, there is a need for insight into what are the most robust biomarkers of treatment efficacy on mood symptoms and cognition to aid more effective, personalized treatments. The aim of the present systematic review is therefore to provide a “landscape” view of putative functional and structural neuroimaging and behavioral predictors of treatment efficacy on depressive symptoms and cognition in mood disorders. Based on this, a discussion will be formed on the identified putative biomarkers and how they may be integrated in the clinical assessments of patients to aid speed and efficacy of future treatment strategies.The initial search criteria were defined in accordance to PICO framework . We included original peer-reviewed articles involving predictive intervention studies on patients with a mood disorder (unipolar or bipolar disorder) and no comorbid schizophrenia/schizoaffective disorder. The primary criterion was a focus on prediction of treatment response or remission using either neuroimaging (fMRI or MRI) or objective neurocognitive testing as a measure. We excluded articles that were naturalistic in design with no control of treatment; involved pediatric, adolescent or geriatric participants; only assessed cognitive measures with subjectively informed ratings; only looked at single drug administrations (with no follow-up of treatment efficacy following longer term treatment). Other reasons for exclusion were: other languages than English; meeting abstract, case report or study protocol; animal studies; comorbid schizoaffective disorder.A systematic computerized search was performed on PubMed/MEDLINE, EMBASE and PsychInfo databases from inception up until October 2017. The search profile included three elements: “biomarker,” “neuroimaging OR cognition” and “mood disorder AND therapy/treatment” with each their combinations in the respective databases .Preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement (Two of the authors (IS and HLK) independently performed a primary title/abstract screening for potentially eligible articles and, following this, a secondary full-text screening was conducted. In both primary and secondary screening, we considered each of the unique references according to inclusion/exclusion criteria, but only provided information on the specific reasons for exclusion of papers in the secondary screening. Finally, a hand search was performed by tracking and screening the citations of the included articles for possible extra inclusions. Agreement between the two authors who performed the screening (IS and HK) was good , and any disagreements were discussed and consensus was reached in all cases. This systematic review has followed the procedures of the tatement , and a Pmood symptoms: 26 investigated “hot”  cognition with behavioral and functional neuroimaging measures, 15 investigated neuroimaging and behavioral measures of “cold”  cognition as predictors of treatment response on mood symptoms, ten investigated resting-state functional neuroimaging measures, and eight investigated structural neuroimaging measures. Only two studies investigated predictors of treatment efficacy on cognition using demographic variables and behavioral measures of cognition.The initial screening identified 2030 articles (duplicate hits excluded). Out of these, 158 articles were included for titles/abstracts screening, resulting in 89 full-text articles evaluated for eligibility. Of these, 60 met inclusion criteria and were included in this review. In total, 58 studies explored different predictors of treatment efficacy on The 26 studies of “hot” cognition as a putative biomarker of treatment response examined behavioral and neuroimaging measures of facial emotion processing and regulation, implicit processing of emotion pictures, emotional self-referential processing, and reward processing . In keeping with this, the study reported an association between amygdala hyper-activity to sad facial expression and non-response to venlafaxine compared to healthy controls  in the presence of meaningful distractor stimuli  exhibited amygdala controls , 34. Furcontrols . One stu stimuli . Notably stimuli  did not greater anterior cingulate cortex (ACC) response to fearful, angry and sad faces compared to non-responders  and baseline prefrontal activity in UD and BD , 27, 31.sponders , 30, 31.Finally, three studies reported an association between greater functional connectivity (FC)  and treatment response to chronotherapy or pharmacotherapy , 31, 35.lower dorsal ACC (DACC) activity to sad faces at baseline compared to non-responders  in ACC, insula, amygdala, and thalamus reactivity to fearful faces after 1 week characterized responders vs. non-responders to escitalopram  compared to non-responders, as well as an increase in lower dorsal regions (DLPFC and DMPFC) to negative faces  after six weeks of treatment relative to non-responders  in bilateral middle occipital cortex (relative to baseline) during encoding and recognition of faces with (task-irrelevant) emotional expressions  explored whether efficacy , 29, 33.sponders . This sugreater baseline activity to negative images in the ACC and premotor cortex and to positive images in the posterior cingulate gyrus and precuneus than non-responders  activity at baseline during attempts to suppress positive emotions elicited by pleasant pictures was associated with greater reduction in anhedonia after venlafaxine or fluoxetine treatment  to negative images and to pictures in general  predicted symptom improvement after CBT  pictures after 1 week of either lithium or quetiapine treatment. Also, while amygdala activity at baseline and after short-term treatment administration did not predict treatment remission, non-remission was associated with baseline hypo-activity in the amygdala in comparison to healthy controls and remitted subjects  –45. Delahyper-activity and low subgenual ACC (sgACC) reactivity during self-referent processing of negative emotional words displayed the most improvement after CBT  , 47 foungreater recruitment of ACC and/or lowered limbic and visual cortical reactivity during the processing of emotional stimuli than non-responders. Accordingly, particularly less limbic and occipital reactivity to task-irrelevant emotional aspects of faces in preference for cognitively demanding tasks was associated with better antidepressant efficacy. In contrast, responders to psychological interventions seem to be characterized by a pattern of greater baseline limbic reactivity, less PFC response to emotional stimuli and greater neural response to reward stimuli.In sum, responders to pharmacotherapy tend to be characterized by heightened PFC top-down control as well as change in neural activity after 1–6 weeks of pharmacological treatment consistently indicate that treatment-related reduction in limbic activity and increase in DPFC top-down control to negative valence emotional stimuli are putative early predictors of response to distinct biological interventions.Additionally, the small number of studies investigating A total of 13 studies investigated “cold” cognition as a putative biomarker for treatment response on mood symptoms  at baseline as well as less recruitment  of brain areas important for cognitive control and/or interference resolution, including the ACC, left VMPFC and right VLPFC  as potential predictors of treatment response on depression symptoms in patients with UD and BD , rTMS, and ECT for depression  between the same regions was associated with remission in medication-treated patients  in fronto-limbic connectivity during resting state.Taken together, the findings support the idea that greater positive fronto-limbic connectivity during resting state at baseline is predictive of treatment response to a psychotherapeutic intervention. In contrast, decreased fronto-limbic connectivity is predictive of response for antidepressant medication treatment. Additionally, response to antidepressant treatment was associated with early Four studies investigated the association between gray matter (GM) and treatment response in UD , 68–70 , 70. In Four studies investigated whether white matter (WM) integrity is predictive of treatment efficacy –74 see , 72. OneOverall, findings from structural neuroimaging studies point to lower hippocampal GM volume and greater ACC volume at baseline being predictors of response to pharmacotherapy and ECT in UD.Only two studies to date have explored the impact of cognitive performance at baseline on treatment efficacy on cognition , 19 see or ≥1 onbaseline and early change biomarkers that were predictive of subsequent clinical efficacy on either depressive symptoms or cognitive impairments. An overview of the results is presented in Figure pharmacotherapy. Further, early treatment-related increase in happiness recognition and modulation of neural activity to negative stimuli in the cortico-limbic circuitry were found in several studies to predict response to several biological treatments. In contrast, greater baseline reactivity in limbic regions and lower PFC response to negative information, greater fronto-striatal connectivity as well as sustained ACC activity to reward stimuli were the most consistent predictors of response to psychological interventions. In addition, resting state fMRI studies showed some evidence for lower fronto-limbic connectivity at baseline and for an early increase in fronto-limbic connectivity predicting response to pharmacological interventions. In contrast, more positive fronto-limbic connectivity was found in resting state fMRI studies to predict response to psychotherapeutic interventions. Finally, lower baseline hippocampal GM volume, greater ACC volume and greater FA were found in structural neuroimaging studies to predict response to pharmacotherapy and ECT, while one study found that increased volume in hippocampus and amygdala after only two ECT sessions predicted later clinical response. In contrast to the large number of studies investigating predictors of mood improvement, only two studies investigated baseline predictors of treatment efficacy on cognition. These randomized, controlled studies revealed preliminary evidence for a strong association between objectively measured cognitive deficits at baseline and subsequent clinically relevant cognitive improvement. Notably, no published studies explored whether improvement in cognition could be predicted by neuronal response during cognitive testing, resting state functional connectivity or structural neuroimaging measures.There is a pressing need for insight into how we can most effectively adapt treatments for mood disorders to the individual patient. This systematic review identified sixty functional or structural neuroimaging and/or behavioral studies of Neural responses to emotional stimuli as well as functional connectivity during resting state seem to differentially predict treatment response to pharmacotherapy vs. psychological interventions and thereby aid treatment selection. For pharmacotherapy, the studies showed the best treatment response for patients exhibiting close to “normal” neural responses . Pharmacotherapy is hypothesized to normalize aberrant fronto-limbic activity to emotional stimuli by reducing the overwhelming influx of automatic negative cues early in treatment . This maOverall, the included studies reported highly consistent evidence for better performance on non-emotional cognitive tests as a predictor of antidepressant treatment efficacy on mood symptoms. In addition, greater ACC volume and FA at baseline, as well as early volume increase in limbic regions, were predictors of response to biological treatments. Taken together, the greater cognitive performance and PFC volume in treatment responders may reflect greater capacity for neuroplasticity and is consistent with evidence for a link between good treatment prognosis and a cognitive reserve  . Notablylower task-related PFC activity during unsuccessful inhibition as well as a verbal working memory tasks at baseline predicted treatment response  responded better to pharmacological treatment. This adds to the notion that better brain function at baseline is a predictor of treatment response. Considering this, the discrepancies in results are likely due to the features of the different cognitive tasks employed , as well as task difficulty, which have considerable effects on the strength and extent of the neural response , and hence these factors were not controlled for. Also, the inclusion criterion for study design was non-specific and did not only include randomized controlled studies, adding to a question of study quality. Adding to this, another methodological limitation to the present systematic review is that only original peer-reviewed articles were included, and a current matter in neuroimaging literature is that studies with small sample sizes or negative results may be prone to publication bias , 82. HowIn conclusion, this systematic review revealed several promising baseline biomarkers for prediction of treatment efficacy on mood symptoms including behavioral and neural measures of emotional and non-emotional cognition as well as cortico-limbic functional connectivity. The review also highlights a need for more studies of early treatment-related changes in these measures, since recent emerging evidence points to informative early change in emotional and non-emotional cognition before any clinical response in symptom reduction. While cognition is a new important treatment target in mood disorders, only two studies assessed the predictors of treatment response on cognition. These two reports found greater chances of treatment efficacy on cognition in patients presenting objective cognitive deficits at baseline. Nevertheless, there is a paucity of studies examining predictors of treatment-associated cognitive improvement. This highlights a pressing need for further investigation of cognitive measures and associated neuronal networks that can guide in the development of new treatment strategies targeting cognition.KM as principal investigator had the overall responsibility of the systematic review. IS conducted the literature searches, under supervision of KM. IS and HK conducted the primary and secondary screening of articles for inclusion. IS and HK wrote the initial draft of the manuscript in collaboration with KM. All authors contributed to and approved the final report.KM declares having received consultancy fees from Lundbeck. 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.


Modern society is hugely dependent on finite oil reserves for the supply of fuels and chemicals. Moving our dependence away from these unsustainable oil-based feedstocks to renewable ones is, therefore, a critical factor towards the development of a low carbon bioeconomy. Lignin derived from biomass feedstocks offers great potential as a renewable source of aromatic compounds if methods for its effective valorization can be developed. Synthetic biology and metabolic engineering offer the potential to synergistically enable the development of cell factories with novel biosynthetic routes to valuable chemicals from these sustainable sources. Pathway design and optimization is, however, a major bottleneck due to the lack of high-throughput methods capable of screening large libraries of genetic variants and the metabolic burden associated with bioproduction. Genetically encoded biosensors can provide a solution by transducing the target metabolite concentration into detectable signals to provide high-throughput phenotypic read-outs and allow dynamic pathway regulation. The development and application of biosensors in the discovery and engineering of efficient biocatalytic processes for the degradation, conversion, and valorization of lignin are paving the way towards a sustainable and economically viable biorefinery. Modern society is largely dependent on natural geological supplies, including crude oil, coal, and natural gas. Our reliance on these fossil fuels is, however, responsible for many causes of global concern, particularly greenhouse gas emissions and the depletion of natural resources , 2. ThesThere is a particular global socioeconomic interest in leveraging aromatic chemicals derived from lignocellulosic biomass , 8–10. TEnzymatic cocktails are extensively used in second-generation bioethanol production from cellulose ; thus, tMetabolic engineering and synthetic biology present an emerging opportunity to develop direct routes to value-added chemicals from lignin. Aromatic precursors can be fed into functionally reconstructed biotransformation routes or modified to allow their introduction into de novo biosynthetic pathways. Lignin monomers can consequently be upgraded into fine chemicals such as flavouring agents, fragrances, and pharmaceuticals. Such approaches have enabled the production of numerous aromatic acids, alcohols, and aldehydes , and of Strategies for pathway optimization and protein engineering of biocatalysts are generally based on the generation of large genetic variant libraries with the final aim of yielding highly producing strains and biocatalysts. Millions of variants are designed and obtained via rational or random mutagenesis techniques and often aided by computational predictions . HoweverIn nature, cells have evolved sophisticated genetic regulatory systems to perceive changes in environmental conditions and detect intra- and extracellular metabolites . In thesSeveral molecular systems have been used to create biosensors, including RNA riboswitches and several ligand-dependent proteins and receptors such as histidine kinases (HK) and allosteric transcription factors (aTFs) , 36, 37.Transcription factors are proteins capable of regulating gene transcription by binding to specific DNA operator sequences within promoters, in turn controlling RNA polymerase activity. These regulators may activate (activators) or repress (repressors) the expression of actuator genes and regulators . AllosteGenetically encoded biosensors are well suited for phenotype screening when the detection of a target metabolite is coupled to fluorescent protein expression . These s3 clones per day, and are time-consuming and laborious. In contrast, biosensors and FACS-mediated screening can enable the high-throughput screening of up to 107 clones per day , 3527, 3 per day . Transcr per day , 43, 45.echnique . Other gechnique , lysine echnique . In addi per day . In geneBesides providing information about the intracellular presence of target metabolites, biosensors can alternatively be employed as actuators when effector binding is coupled to expression of genes encoding enzymes with activity towards the effector Fig. . Heteroll-valine , 7242, 7Release of unmodified aromatic monomers from lignin following harsh chemical pre-treatment has proven challenging . In contHigh-throughput screens using genetically encoded biosensors allow for the detection and selection of novel biocatalysts from environmental metagenomic samples, which constitute a rich source of genetic information for the discovery of biocatalysts, transporters, and regulatory elements Fig. a 79, 8080. This When genetically encoded biosensors are integrated within other screening systems such as FACS, methods can be developed that offer a powerful system for metagenomic sample screening. One such system includes the substrate-induced gene expression (SIGEX) system, a high-throughput promoter-trap method can that can activate expression of reporter genes upon target aromatic induction, and subsequently uses FACS to isolate clones from metagenomic DNA libraries . SIGEX hAcinetobacter sp. ADP1 was used in the enzymatic screening and selection of dehydroshikimate dehydratase enzymes (AsbF) with PCA-producing activity. Using FACS, individual biosensor cells carrying the desired AsbF could be isolated from an inactive AsbF population [Pseudomonas to detect benzoic acid and 2-hydroxybenzoic acid and regulate expression of lacZ and the tetracycline resistance gene tetA. The system was successful in the selection of biocatalytically active cells from an enzymatic library encoding a benzaldehyde dehydrogenase (xylC), as these active mutants allowed benzaldehyde-dependant cell growth [Determination of substrate and product concentrations is a major bottleneck for enzymatic optimization and directed evolution processes see “” sectionpulation . van Sinpulation  utilizedl growth .P. putida to optimize enzymatic activity and alleviate product inhibition in chorismate pyruvate-lyase (UbiC). Along with the engineered 4HB biosensor–enzyme coupling, benzoic acid was utilized as a product surrogate that inhibited UbiC activity. As a result, they generated an UbiC variant library with reduced product inhibition and isolated a clone that eventually allowed a twofold yield increase in the bioproduction of muconic acid from glucose. Moreover, the p-coumaric acid-responsive biosensor developed by Siedler et al. [p-coumaric acid production after co-encapsulation within microfluidic droplets. This system was subsequently used in the screening and sorting of high-producing strains from a yeast producer mutant library, indicating that the system could be used to enrich p-coumaric acid producing strains [Applying biosensors for enzymatic screening can also facilitate the optimization of productivity of aromatic-transforming enzymes and pathways. Recently, Jha et al.  developer et al.  based on strains .Several biosensors have also been developed and integrated into biosynthetic pathways for metabolic engineering applications , 87. Balp-coumaric acid sensing module, metabolic stress was lowered by twofold, while bioproductivity was improved fivefold [Lo et al.  achievedfivefold .Furthermore, an autoregulatory lignin valorization system was developed to diminish aromatic toxicity and circumvent required addition of exogenous inducers . The sysBesides utilizing genetically encoded biosensors to respond to lignin degradation products and intermediates, it is important to develop and implement regulatory systems that can respond to sugars derived from lignocellulose to establish a fully integrated biorefinery process. Hemicelluloses in lignocellulose comprise a very heterogeneous group of polysaccharides, including xylans, arabinoxylans, and cellulose . The hydd-arabinose based on the naturally occurring XylR and CelR and on an engineered AraC transcription factor, respectively [d-arabinose [d-arabinose, glucose, and glutamate, using the AraF, MglB, and YbeJ bacterial periplasmic-binding proteins (PBPs), respectively [xylF promoter by 40%, resulting in increased GFP signal output in the presence of xylose.To date, several regulation systems have been developed that focus on the detection of these lignocellulose-derived sugars Table . Transcrectively –92. The rabinose . FRET biectively , 94. Morectively  developel-rhamnose inducible rhaBAD expression system to identify alternative orthogonal effectors. Among these, they found that the sugar analogue l-mannose provided the greatest response fold change [These sugar-inducible regulatory systems constitute valuable mechanisms that could be utilized for the simultaneous degradation and biotransformation of hemicellulose and lignin fractions while maintaining reduced product inhibition and increased productivity. Furthermore, the scope of sugars and their analogues that can be detected using biosensors should also be extended. Kelly et al.  developed change .Owing to their importance in the chemical, energy, and pharmaceutical industries, lignocellulosic feedstocks continue to be an attractive source of aromatic compounds. To this end, biomass-derived bioproduction has been modest, achieving low productivity when compared to commercial-scale demands . EffectiThe application of these biosensors is particularly interesting for sampling environmental metagenomes , as thesFurthermore, bioproduction of aromatics will need to be incorporated with regulated synthetic pathways to achieve fully integrated dynamic control and production of metabolites to achieve an overall improved bioproduction process. Dynamic pathway control mediated by sugar or aromatic-based regulatory systems will provide a beneficial bioproduction approach by allowing on-demand expression of lignocellulose-transforming biosynthetic pathways when they are most required. To accelerate these biosensor-mediated processes, the current selection of products and intermediate metabolites that can be detected will need to be expanded. Development of novel genetically encoded biosensors will be aided by developments in protein engineering techniques and computational design to engineer novel ligand specificities . In addiGoing forward, the increased adoption of evolutionary strategies is anticipated to aid chemical bioproduction and metabolic engineering developments. Overcoming these current productivity limitations will offer great opportunities for the use of genetically encoded biosensors in pathway engineering for lignocellulose valorization. Advancements in these areas will help diversify the array of products that can be obtained from lignin and provide efficient biocatalysts for their integration into economically viable biorefinery processes.


The requirement of innovative big data analytics has become a critical success factor for research in biological psychiatry. Integrative analyses across distributed data resources are considered essential for untangling the biological complexity of mental illnesses. However, little is known about algorithm properties for such integrative machine learning. Here, we performed a comparative analysis of eight machine learning algorithms for identification of reproducible biological fingerprints across data sources, using five transcriptome-wide expression datasets of schizophrenia patients and controls as a use case. We found that multi-task learning (MTL) with network structure (MTL_NET) showed superior accuracy compared to other MTL formulations as well as single task learning, and tied performance with support vector machines (SVM). Compared to SVM, MTL_NET showed significant benefits regarding the variability of accuracy estimates, as well as its robustness to cross-dataset and sampling variability. These results support the utility of this algorithm as a flexible tool for integrative machine learning in psychiatry. Biological research on psychiatric illnesses has highlighted the scale of investigations required to identify reproducible hallmarks of illness ,2. In scThe combined “mega-analysis” of data across cohorts and modalities has advantages compared to the more traditional meta-analysis ,7, as itThe application of machine-learning techniques on biological problems in psychiatry has already yielded impressive results, including on the prediction of genetic risk, the identification of biomarker candidates, or the exploration of etiological mechanisms . For exaIn the present study, we used MTL to differentiate schizophrenia patients from controls across multiple transcriptome-wide expression datasets. We hypothesized that MTL is particularly suited for this task, since it allows the consideration of different cohorts as separate classification tasks. As MTL aims to identify predictive patterns that are shared across tasks, it should uncover expression patterns that are biologically reproducible across cohorts. This may result in better and biologically more relevant classifiers compared to those derived from conventional single task learning (STL), which may be unduly influenced by strong signals present in individual cohorts. To test this, we performed a comparative analysis of different MTL and STL approaches in five transcriptome-wide datasets of schizophrenia brain expression. A ‘leave-dataset-out’ procedure was applied to explore and compare the generalizability of the models, with specific focus on classification accuracy, and variability thereof, as well as model sensitivity to cross-dataset and sampling variability.In dn = 4 (four datasets used for training), suggesting that MTL required a higher dataset number to identify a reproducible biological pattern. However, we observed that the variation of accuracies for MTL_NET substantially decreased with increasing numbers of training datasets . First, raw expression data were read using the ‘ReadAffy’ function. Then RMA . For each dataset, propensity score matching was used to obtain a sample with approximate 1:1 matching for diagnosis, sex, ph, age, and post-mortem interval (pmi). Next, all datasets were concatenated for quantile normalization and covariate correction. Specifically, the ‘Combat’ function from the R library sva [2, pmi, and a dataset indicator). Finally, datasets were separated again for feature standardization (z-score) to remove bias from the expressed genes with large variance and for downstream machine learning analysis.Preprocessing was performed using the statistical software, R ( Average ) was apprary sva  was applFor MTL, multiple across-task regularization strategies were tested, such as MTL with network structure (MTL_NET), sparse network structure (MTL_SNET), joint feature learning (MTL_L21), joint feature learning with elastic net (MTL_EN), and low-rank structure (MTL_Trace). As a comparison, we selected logistic regression with lasso (LR), linear support vector machines (SVM), and random forests (RF) as representatives of conventional STL methods. For all models (except for RF), stratified five-fold cross validation was used to select hyper-parameters. Methodological details of the respective methods are described below. All machine-learning analyses were performed using Matlab (R2016b).For all MTL formulations, the logistic loss , as illustrated in To compare the consistency and stability of markers between algorithms, we used the correlation coefficient as the similarity measure of pairwise transcriptomic profiles  learnt by algorithms. A high similarity between profiles implied that models shared important predictors with respect to their weights and signs. Using this similarity measure, ‘consistency’ and ‘stability’ were defined, respectively. These measures were derived from 100-fold stratified bootstrapping of subjects from a set of datasets. In each bootstrapping sample, we tested across the number of training sets  datasets. For this, we differentiated two types of consistencies: ‘Horizontal’ and ‘vertical’ consistency as illustrated in Stability: To quantify the stability of an algorithm against the sampling variability, we observed the variation of transcriptomic profiles learnt from different bootstrapping samples as illustrated in Success rate: In addition to consistency and stability, to perform a side-by-side comparison of algorithms, we defined the success rate as the proportion of cases where one algorithm outperformed the other. For example, we quantified the success rate of consistency as the proportion of bootstrapping samples where the first algorithm demonstrated higher consistency than the second (see supplementary methods for details). The success rate of stability was quantified as the proportion of models, which were more stable for the first algorithm than that for the second (see supplementary methods for details). This work evaluates the performance of MTL and STL for biomarker analysis across five transcriptomic schizophrenia expression datasets. Several quality control procedures were employed to remove unwanted variation in the investigated datasets and to improve the biological generalizability of the obtained results. Despite this, the presented results should be interpreted in the light of the specific datasets investigated. Since other data modalities, including neuroimaging or gene methylation, show similar cross-dataset heterogeneity and correlation structures across variables, the present results may not be limited to expression data, although this remains to be empirically demonstrated. Furthermore, future investigations should include systematic simulation studies to explore the performance of MTL and its robustness against factors typically affecting machine learning performance, including data dimensionality, predictor effect sizes, and biological as well as experimental variability across datasets.The present study demonstrates the utility of MTL for integrative machine learning in high-dimensional datasets, compared to classical single-task learning. Mega-analyses that require integration of data across numerous datasets are becoming more frequent, but thus far, have rarely used machine learning approaches. The present study shows that MTL bears substantial promise for such applications. This particularly applies for scenarios where inter-dataset heterogeneity far outweighs the illness associated signal, a typical case for high-dimensional datasets in psychiatric research.