Mycobacterium bovis exposure has been documented and heritability estimates of 0.06-0.18 have been reported. Despite their moderate magnitude, these estimates suggest that host resistance to bTB is amenable to improvement with selective breeding. Although relatively slow, genetic progress can be constant, cumulative and permanent, thereby complementing ongoing disease control measures. Importantly, mostly no antagonistic genetic correlations have been found between bTB resistance and other animal traits suggesting that carefully incorporating the former in breeding decisions should not adversely affect bovine productivity. Simulation studies have demonstrated the potential impact of genetic selection on reducing the probability of a breakdown to occur or the duration and severity of a breakdown that has already been declared. Furthermore, research on the bovine genome has identified multiple genomic markers and genes associated with bTB resistance. Nevertheless, the combined outcomes of these studies suggest that host resistance to bTB is a complex, polygenic trait, with no single gene alone explaining the inherent differences between resistant and susceptible animals. Such results support the development of accurate genomic breeding values that duly capture the collective effect of multiple genes to underpin selective breeding programmes. In addition to improving host resistance to bTB, scientists and practitioners have considered the possibility of reducing host infectivity. Ongoing studies have suggested the presence of genetic variation for infectivity and confirmed that bTB eradication would be accelerated if selective breeding considered both host resistance and infectivity traits. In conclusion, research activity on bTB genetics has generated knowledge and insights to support selective breeding as an additional measure towards controlling and eradicating the disease.Bovine tuberculosis (bTB) persists in many countries having a significant impact on public health and livestock industry finances. The incidence and prevalence of new cases in parts of the UK and elsewhere over the past decades warrant intensified efforts towards achieving Officially Tuberculosis Free (OTF) status in the respective regions. Genetic selection aiming to identify and remove inherently susceptible animals from breeding has been proposed as an additional measure in ongoing programmes towards controlling the disease. The presence of genetic variation among individual animals in their capacity to respond to  Mycobacterium bovis (M. bovis), the key pathogen agent responsible for bovine tuberculosis.Tuberculosis is a key disease with multiple pathogen and host species involved in transmission and consistently ranks in the top five most significant diseases worldwide . AccordiBovine tuberculosis (bTB) presents a global problem to the industry. As a zoonotic disease, bTB receives due attention as a public health, financial, and political issue. As such, monitoring, control, and eradication programmes have been established in multiple afflicted countries and regions.In the United Kingdom (UK), bTB is endemic and costly to the tune of £175-200 million annually , 4. The There is evidence that cattle vary genetically in their susceptibility to bovine TB and, once infected, there may be genetic variation in their propensity to spread the infection to other animals. It is thus possible to select for better disease susceptibility and transmission traits as part of cattle breeding programmes.” [Selective breeding has been proposed as an additional possible means to control bTB, thereby contributing to the ongoing monitoring and eradication programmes. The main premise is that individual animals exposed to the same pathogenic conditions responsible for a disease react and respond differently: some animals remain healthy, others become a little sick, others more so, and some actually die. This variation is partly attributed to genetic factors manifested in protein-coding genes and/or regulatory sequence elements that render certain animals inherently more resistant or susceptible to the disease than others. In the case of bTB, identifying animals that carry genetic variants contributing to infection resistance and selecting them for breeding can promote the overall population resistance and contribute to bTB control. In a similar but more conservative scenario, individual animals bearing genetic variants that render them susceptible to the disease are identified and removed from the breeding process, thereby removing said variants from the subsequent generations. The potential of selective breeding in bTB control is reflected in a relatively recent strategy review commissioned by the UK government, led by Sir Charles Godfray of the University of Oxford  where a rammes.” .The present review discusses the genetic component of variation in host response to bTB infection and demonstrates how this variation may be applied in selective breeding programmes towards enhancing cattle resistance to bTB. Results from relevant studies are summarised showing and quantifying the potential impact on disease control and eradication. Further to disease resistance, the role of genetics in reducing animal infectivity regarding bTB is briefly discussed.The genetic basis of host resistance and susceptibility to bTB infection was addressed in a 2010 review  and poteMore recent studies included animal genomic data based on genotyping with genome-wide DNA arrays in the calculations and reported higher heritability estimates of 0.21-0.27 –19. The The overall magnitude of heritability reported so far may seem moderately low but for most animal traits of interest estimates normally do not exceed 0.50. Heritability of health-related traits is known to be generally modest to low, usually less than 0.15. Nevertheless, the genetic variation manifested in the above heritability estimates for bTB resistance is enough to achieve progress with selective breeding. The latter has been decisively demonstrated for other cattle health traits with similar or even lower heritability values such as clinical mastitis, lameness, and metabolic diseases, which now feature prominently in selective breeding programmes worldwide .M. Bovis infection. Selective breeding programmes would then need appropriate genetic evaluation systems and tools in place to properly identify the inherently resistant and susceptible animals in order to inform breeding decisions that will underpin enhanced resistance in the subsequent generations.In conclusion, there is confidence that genetic variation in cattle for bTB resistance is indeed sufficient to identify animals that are inherently more resistant than others to Research conducted on bTB surveillance data in the UK led to the development of a national genetic evaluation of dairy cattle for bTB resistance . This syM. Bovis culture results, to define the health status of each animal, which would constitute their individual phenotype for bTB infection. Furthermore, probabilities of animal infection at different stages of a breakdown were assigned to each animal that eventually tested positive to the SICCT test [The study first combined SICCT test and post-mortem data, namely records on bTB lesions and CCT test . These pA genetic model was developed to analyse these bTB phenotypes . The modFurther to non-genetic effects, the model includes an animal additive genetic effect that, after data analysis, provides an estimate of the genetic merit of each individual animal for resistance to bTB that accounts for all other sources of systematic variation fitted in the model. Here, although the phenotypic data pertain only to milking cows, breeding values are also estimated for their sires, through the pedigree connections that are included in the data analysis. Actually, the sire breeding values are more accurate than those of individual cows on the account of the former being associated with multiple progeny with records in the system. In a validation exercise, the correlation of the sire estimated breeding values with the proportion of infected milking daughters was -0.68, suggesting that sires with highly positive values of genetic merit are associated with reduced infection rate in their progeny . SimilarImportantly, the correlation between genetic evaluations for bTB resistance and other animal traits is mostly zero, suggesting that selective breeding to enhance animal resistance to the disease would not compromise improvement in the other traits . In factA subsequent study expanded the bTB genetic evaluations to include genome-wide marker data from animal genotyping using DNA arrays . DiffereResearch on the genetics of bTB resistance in dairy cattle has led to the development of the official UK national genetic evaluation, run since 2016 at the Edinburgh Genetic Evaluation Services on behalf of the Agriculture and Horticulture Development Board. The genetic evaluation outcome, the actual selection index, has been termed “TB Advantage”  and is nAnother research project investigated the feasibility of a genetic evaluation for bTB resistance in UK beef cattle. Data analyses were conducted on 437,235 animals, progeny of 36,790 sires from 53 beef breeds. These data pertained to 8,648 bTB breakdowns where 7.3% of the animals were infected . Significant genetic variation was detected for bTB resistance and was manifested in variation in the resulting estimated breeding values of the sires, thereby demonstrating the feasibility to distinguish breeding animals expected to produce bTB resistant from susceptible progeny. As was the case with dairy breeds, correlations of these breeding values with beef traits such as animal growth, carcass characteristics and lifespan were either negligible or moderately favourable, suggesting that genetic selection to enhance bTB resistance in beef cattle would not compromise the current breeding goal. Incorporation of bTB in the official national genetic evaluation process of beef cattle is imminent.Genetic evaluations for bTB resistance are also available in the Republic of Ireland  and are Despite being expressed on distinctly different scales in Ireland and the UK, estimated breeding values for resistance to bTB offer essentially the same information, namely, they identify and separate genetically resistant and susceptible individuals. Thus, they have the same potential utility in supporting selective breeding programmes in the respective countries. The key is in the interpretation and proper use.These genetic evaluations are now well tested and validated nationally, so that combination and a joint analysis of data from the two countries to produce across-country estimated breeding values for bTB become a realistic option. Experience with the international genetic evaluations provided by the International Bull Evaluation Service (Interbull)  since 19The advent and broad implementation of bovine genome-wide DNA arrays (chips) based on tens or hundreds of thousands of Single Nucleotide Polymorphism (SNP) markers have enabled research that cast closer insights on genomic regions and genes associated with animal traits of interest. The key principle is that these SNPs are within or in high linkage disequilibrium with genes and genomic regulatory regions that control important animal traits. This approach has found widespread use in livestock breeding programmes .Multiple genomic association studies using data from the above mentioned DNA arrays have been conducted on bTB resistance in various bovine populations in different countries , 28–31. In addition, a few regional heritability mapping studies have been conducted using genome-wide SNP data , 18, 32.Using publicly available bovine genome assemblies, several annotated genes were identified neighbouring SNPs or being located within genomic regions associated with bTB traits in the aforementioned studies. Further studies more closely examined specific candidate genes affecting the host’s resistance or susceptibility to the disease –38. ThesTable Genetic improvement with selective breeding is a long-term process and benefits become visible in future generations. From the moment the genetically most resistant breeding animals are identified and mated, it would take at least one generation to see the effect in their progeny. The process will continue in the subsequent generation and then in the following one and so on, and benefits gradually accumulate. The process is slow, but the effects are permanent and cumulative. The benefits of selective breeding have been observed in multiple livestock traits not least those associated with animal production, health, fertility, and longevity over the past century and have been duly documented .Presence of heritable genetic variation and the feasibility of harnessing it in the estimation of accurate genetic evaluations of animals, as discussed above, may underpin selective breeding practices aiming to enhance resistance to bTB and contribute to the overall control and eventual eradication of the disease. In a generational context, these selection tools have become available relatively recently and the full effects are expected to materialise in due course in the subsequent generations.In the meantime, simulation studies have been conducted to predict and quantify the long-term effect of selective breeding for enhanced animal resistance or reduced susceptibility to bTB. In one such study, animal data were simulated reflecting the current bTB dynamics in the UK regarding disease prevalence, and size and duration of bTB breakdowns . A modelResults showed that any level of selective breeding would be associated with a faster ending of the epidemic compared to the scenario of no selection . As expeThe above research was based on a model reflecting the “worst-case” scenario where an animal becomes infectious and starts transmitting the disease before it can be detected as infected and removed from the herd. Although this assertion is consistent with the suggestion that cattle with bTB lesions in the respiratory tract should be considered potential transmitters of the pathogen and sources of infection for other animals in the herd , previouKey conclusions drawn for this research were that genetic selection could accelerate bTB eradication, as a complementary measure to already existing ones. Thus, selective breeding for enhanced animal resistance to bTB can contribute to herds and regions achieving their OTF goals faster.Further to improving animal resistance to bTB, a disease eradication programme would also benefit if the rate of transmission from one animal to another decreased. There is increasing evidence, albeit mostly empirical, that individual animals differ in their capacity to infect their herd-mates. The presence of inherently super-spreader individuals is now widely accepted  and idenRelevant genetic-epidemiological simulation studies have suggested that selective breeding for reduced infectivity together with enhanced resistance to bTB would lead to faster disease eradication than selecting only for enhanced resistance or, of course, not selecting at all , 46. TheHowever, the genetic basis of infectivity is still largely unknown. Defining and characterising the proper animal phenotype is a serious challenge. Work is currently being conducted on this topic and a recent study on dairy cattle data reported significant genetic variation among index cases regarding the number of secondary cases attributed to them . Here anAvailability of informative individual animal phenotypes for the traits of interest is the key and most crucial component of modern selective breeding programmes. This entails data of high quality that reflect the true biology of the animal as closely as possible, available in sufficient quantities to allow accurate calculations. Without said phenotypes, even the most advanced genomic technologies and the most elaborate statistical analysis models would have very little opportunity to demonstrate their utility.M. bovis culture results constitute the phenotypes in current national genetic evaluations [In the case of bTB, SICCT test records combined with post-mortem visible lesions and luations , 25. ThaOther diagnostics that may provide new animal phenotypes with improved sensitivity are worth consideration. Gamma-interferon assays have been long used for bTB diagnosis  often inAlternative phenotyping approaches have been proposed in livestock improvement based on molecular traces in the milk of dairy cows that emanate from various animal physiological processes . Mid-infIn a recent study, extensive cow milk MIR data were combined with bTB national surveillance records and machine learning was deployed to jointly analyse the data and deliver a prediction pipeline of the bTB status of individual animals from their MIR spectral profiles . After oBovine tuberculosis is a complex issue, and an array of factors may determine whether an animal becomes infected, and a breakdown is declared. Complex problems require complex strategies and solutions, and indeed this is the case with ongoing bTB control and eradication programmes in different countries. Genetic selection of inherently resistant individuals that will breed enhanced natural resistance into the subsequent generations is proposed as an additional component within these programmes.Further improvements in genomic evaluations are in scope with more targeted genotyping both in terms of animals (bulls and cows) and DNA arrays, and incorporation of identified genomic regions with significant effects on the trait in the calculation of breeding values. Decreasing DNA array genotyping costs, genotype imputation improvements, and new approaches such as genotyping by low pass sequencing combined with imputation provide useful opportunities in this regard.M. bovis infection is now well accepted. Future genomic studies of DNA array and whole genome sequence data combined with post-genomic  research will cast further insights into the complex architecture of the trait, including focus on the location and function of both protein-coding genes and regulatory elements [As previously mentioned, the polygenicity of host resistance to elements . Improveelements  certainlM. bovis infection, understanding the genetics of infectivity at the individual animal level is only now starting and we have some way to go before being able to usefully inform genetic selection programmes aiming to decrease the rate of animal-to-animal transmission. Nevertheless, this area of scientific research and development is topical and warrants continuing attention and effort. Future bTB control programmes should be able to combine selective breeding for increased host resistance with reduced animal infectivity.Beyond host resistance to Furthermore, as has been experienced with the genetics of just about any important animal trait, multi-actor collaboration is a prerequisite to the successful development and implementation of selective breeding programmes. There is scope for continuing interdisciplinary research to understand why and how individual genes affect host traits and how host genetics interact with pathogen variation. Moreover, there are opportunities for across-country cooperation to facilitate international trade that is of key importance to the bovine industry. There are national genetic evaluation systems for bTB in place in at least the UK and Ireland and it is possible to pull data together and produce international genetic evaluations, as is the case with several dozens of other animal traits at the moment .As already mentioned, selective breeding is a long-term process, it takes time to see the benefits, but it can work. Of course, this requires faith and good judgement, and everybody to be on board, not least farmers, practitioners, breeder associations, breeding companies, scientists, governments, and policy makers. Only then would the benefits discussed here truly materialise, contributing decisively to the control and eventual eradication of the disease.


A series of fused bithiophene imide dimer‐based polymers, PO8, PO12, and PO16, incorporating distinct oligo(ethylene glycol) side‐chain to optimize σ is reported here. Three polymers show a monotonic electron mobility decrease as side‐chain size increasing due to the gradually lowered film crystallinity and change of backbone orientation. Interestingly, polymer PO12 with a moderate side‐chain size delivers a champion σ up to 92.0 S cm−1 and a power factor (PF) as high as 94.3 µW m−1 K−2 in the series when applied in OTE devices. The PF value is among the highest ones for the solution‐processing n‐doped polymers. In‐depth morphology studies unravel that the moderate crystallinity and the formation of 3D conduction channel derived from bimodal orientation synergistically contribute to high doping efficiency and large charge carrier mobility, thus resulting in high performance for the PO12‐based OTEs. The results demonstrate the great power of simple tuning of side chain in developing n‐type polymers with substantial σ for improving organic thermoelectric performance.n‐Doped polymers with high electrical conductivity ( A series of fused bithiophene imide dimer‐based polymers with distinct side‐chain size is developed to synergistically improve electron mobility and doping efficiency, which demonstrates remarkable electrical conductivity and power factor when applied in organic thermoelectrics. The thermoelectric performance is assessed by a dimensionless figure of merit of 𝑍𝑇 = 𝜎𝑆2𝑇/𝜅, where 𝜎, S, T, and k are the electrical conductivity, Seebeck coefficient, temperature, and thermal conductivity, respectively. To realize high‐performance organic thermoelectric modules, it is required for both p‐type and n‐type materials with high and comparable performance. To date, p‐type organic thermoelectric (OTE) materials, especially p‐type OTE polymers, have been intensively investigated and achieved the state‐of‐the‐art performance, exemplified by the benchmark p‐type polymers P3HT and poly with ZT > 0.4, which is originated from the high power factor  of >300 µW m−1 K−2. Nevertheless, the n‐type counterparts lag greatly behind with much lower PFs typically ranging from 1 to 10 µW m−1 K−2, mainly suffering from the inferior electrical conductivities (𝜎s) typically in the range of 5–20 S cm−1. From the view of materials development, the unsatisfactory n‐type performance is mainly restrained by the scarcity of highly electron‐deficient building blocks with good solubility, compact molecular geometry, and optimized electronic properties.Polymer semiconductors provide an excellent opportunity to function as low‐temperature (<200 °C) thermoelectric materials due to their advantages of solution processability, minimal toxicity, small thermal conductivity, and excellent mechanical flexibility,5, 6 and perylene diimide (PDI). Their incorporation into donor–acceptor (D‐A) type polymers greatly improved the n‐type OTE performance at that time. However, the phenyl‐based NDI and PDI suffer from sizable steric hindrance with neighboring (hetero)arenes and hence twisted backbone in the resulting polymers, which significantly limits the electron mobility, thus leading to a poor 𝜎 (0.1–0.5 S cm−1) and PF (0.5–2 µW m−1 K−2). Since then, a great number of electron‐deficient building blocks have been devised to improve the performance of OTEs of the resulting n‐type polymers arene‐based polymers, boron‐nitrogen coordination bond‐based polymers, and ladder‐type polymers. For example, Pei et al. reported an amide‐functionalized n‐type polymer TBDOPV, which achieved a 𝜎 of 90 S cm−1 and a high PF of 106 µW m−1 K−2. Recently, Huang et al. reported a ladder‐type poly(benzodifurandione) (PBFDO) with low‐lying LUMO and good backbone coplanarity and found that it has ultrahigh conductivity of 2000 S cm−1 and a promising PF approaching 90 µW m−1 K−2. Nevertheless, the performance parameters of most polymers are still much inferior to their p‐type counterparts. Therefore, it is highly imperative to further design and synthesize high‐performance n‐type polymers for advancing the OTE field.At beginning, the widely used electron‐deficient building blocks were the historic imide‐functionalized arenes, i.e., naphthalene diimide (NDI)28 and According to the equation: σ = nµq, where n, µ, and q are charge carrier concentration, charge carrier mobility, and elementary charge, respectively, hence both electron mobility and charge carrier concentration  are equally important to realize high σs for n‐type polymers. Via backbone optimization, the resulting polymers could exhibit planar and linear backbone and high crystallinity, which results in improved charge transport in organic thin‐film transistors (OTFTs), but could be inclined to yield poor miscibility with dopant molecules and hence low doping level. Therefore, it is highly challenging to simultaneously achieve high electron mobility and doping level to improve the σs of n‐doped polymers.Based on the OTE performance parameters, it is clear that the low 𝜎 value is the major factor limiting the performance of n‐type organic and polymer semiconductors.47 Acc have been proven to be the excellent electron‐deficient building blocks for accessing high‐performance n‐type polymers with large electron mobility  achieved in OTFTs owing to their merits of excellent solubility, good backbone coplanarity, and high electron deficiency. Thus a great number of BTI derivatives have been invented to construct donor–acceptor (D‐A) and acceptor–acceptor  polymers for OTFTs and all‐polymer solar cells. For example, polymer f‐BTI2‐FT comprising of a fused bithiophene imide dimer (f‐BTI2) with alkyl side chains as acceptor unit and 3,4‐difluorothiophene as donor co‐unit showed unipolar n‐type character with a high µe,OTFT of 1.13 cm2 V−1 s−1 in OTFTs. When replacement of alkyl chain by oligo(ethylene glycol) (OEG)‐type chain, the minor structurally modified polymer f‐BTI2TEG‐FT maintained a high degree of backbone planarity and low‐lying lowest unoccupied molecular orbital (LUMO) energy level but with a much higher degree of n‐doping efficiency, thus resulting in an improved 𝜎 of ≈70 S cm−1. Nevertheless, the µe,OTFT is only 6.34 × 10−4 cm2 V−1 s−1, which limited the conductivity improvement. It is well known that the introduction of thienylene–vinylene–thienylene (TVT) unit can lead to increased conjugation length and more planar backbone compared to thiophene unit, demonstrating the advantages of improving microstructural ordering and charge transport in thin films for the resulting polymers  and its derivatives51 hav In addition to the polymeric backbone, the side‐chain also shows a significant effects on polymer chain stacking and film crystallinity, thus greatly influencing the device performance. In this contribution, we systematically study the impact of side‐chain size on the polymer optical/electrochemical properties, charge transport characters, n‐doping efficiency, and OTE performance. As shown in Figure −1 as well as a remarkable PF of 94.3 µW m−1 K−1, much higher than the devices based on polymers PO8 (𝜎 = 18.1 S cm−1 and PF = 14.7 µW m−1 K−1) and PO16 (𝜎 = 40.5 S cm−1 and PF = 62.1 µW m−1 K−1). To the best of our knowledge, the PF of 94.3 µW m−1 K−1 is among the highest values of n‐doped polymers for OTEs. The morphology analysis unravels that PO12 has a moderate crystallinity with bimodal orientation (both face‐on and edge‐on), which are beneficial to achieving high doping level and large electron mobility simultaneously, thus yielding high OTE performance. Overall, our work demonstrates that synergistical optimization of backbone orientation and side‐chain size provides a powerful avenue to develop n‐type polymers for high‐performance OTEs.Based on the great success of cyanation for polymers with improved electron transport properties and TVT with minimized steric hindrance, cyano‐functionalized TVT −1,2‐bis(‐(3‐cyano‐5‐(trimethylstannyl)thiophene‐2‐yl)ethene (TVTCN‐2Sn) under typical Stille coupling‐based polycondensation to afford product polymers PO8, PO12, and PO16 with a yield of 74%, 81%, and 85%, respectively. The synthetic details can be found in the Supporting Information. After polymerization, the polymers were precipitated into methanol and then purified by successive Soxhlet extraction to afford the final polymer products. Using gel permeation chromatography (GPC) with hexafluoroisopropanol (HFIP) as the eluent, the number average molecular weight (Mn)/dispersity (Đ) was found to be 11.7 kDa/1.6, 23.8 kDa/1.9, and 33.1 kDa/2.1 for PO8, PO12, and PO16, respectively  unraveled that three polymers have superior thermal stability with a decomposition temperature over 270 °C, and differential scanning calorimetry (DSC) analysis showed no distinctive transition peaks from 30 to 250 °C for all three polymers  located at 463 nm. From solution to film state, all monomers exhibit a redshift of ≈10 nm as a result of the increased backbone planarity and chain aggregation. After polymerized with TVTCN unit, three polymers show distinct absorption features in the range of 400–700 nm. For PO8, a strong absorption peak is found at 561 nm in solution, associated with the intramolecular charge transfer (ICT) between f‐BTI2 and TVTCN units, while both PO12 and PO16 featured similar bathochromically shifted absorption peaks at 571 nm. Compared to solution, the λmax of three polymer films exhibited a pronounced redshift of ≈20 nm due to the fact that they have a higher degree of polymer chain ordering in film state. The polymer optical bandgaps (Egopt) were determined from the absorption onset of polymer films, corresponding to 1.79, 1.77, and 1.77 eV for PO8, PO12, and PO16, respectively.The absorption properties of f‐BTI2g‐2Br(O8), f‐BTI2g‐2Br(O12), and f‐BTI2g‐2Br(O16) in chloroform solution and as thin film are depicted in Figure Egopt.Please note that PO12 and PO16 demonstrate significantly bathochromically shifted absorption compared to PO8 in both solution and film states. The temperature‐dependent UV–vis absorption was characterized to investigate the polymer aggregation properties. As shown in Figure + as the reference electrode and ferrocene/ferrocenium (Fc/Fc+) redox couple as the external standard in 0.1 m tetra(n‐butyl)ammonium hexafluorophosphate acetonitrile solution  energy levels of three polymers were probed by cyclic voltammetry (CV) with Ag/Agn Figure , and Tab2.3Figureµe,OTFT of 0.013 ± 0.02 cm2 V−1 s−1, which was slightly higher than both PO12  and PO16 , indicative of a large influence of OEG chain size on charge transport in OTFTs. The OTFT mobilities of ≈0.01 cm2 V−1 s−1 achieved from PO8 device are among the highest values for n‐type polymers functionalized with OEG‐type side chains, which could be beneficial to obtaining high electron mobility after doping. Please note that these OTFT mobilities are significantly less than those analogues with alkyl side chains. We guess that the OEG side chain would induce water‐related electron traps because of its hydrophilicity and result in widening interfacial charge transport density of states due to its high polarity.The charge transport properties of three polymers are studied by fabricating top‐gate/bottom‐contact (TG/BC) OTFTs with a device structure of glass/Au/polymer/CYTOP/Al, in which a fluorinated perfluoro(1‐butenyl vinyl ether) polymer (CYTOP) is used as dielectric layer. The details of device fabrication are depicted in the Supporting Information, and the output/transfer characteristics of the optimal devices are displayed in 2.4N,N‐Dimethyl‐2‐phenyl‐2,3‐dihydro‐1H‐benzoimidazole (N‐DMBI) was selected as the dopant for three polymers due to its good air‐stability, strong reducing ability, and excellent solution processability. As shown in FigureN‐DMBI has successfully doped three polymers. Compared to PO8 and PO16, PO12 exhibits much stronger (bi)polaron absorption, which suggests more efficient n‐doping of PO12 film.To explore n‐doping properties, UV–vis–NIR absorption spectra of three polymers were first investigated. The polymer films were doped by sequential protocol instead of traditional blend doping due to its advantage of achieving more ordered film morphology of doped polymer.69N,NElectron paramagnetic resonance (EPR) spectroscopy Figure  was furt2.52/water de‐doping. The optimal device performance of PO8 and PO16 was achieved using chloroform as the solvent, and the optimal performance PO12 was attained using hexafluoroisopropanol. The N‐DMBI concentration was systematically varied from 0.1 0.5, 1, 2, 3, 4 to 5 mg mL−1, and the related performance parameters are summarized in Figure Table After doping with a low dopant concentration of 0.1 mg mL−1, the conductivity increases substantially due to the generation of mobile charge carriers. With a further increase of dopant concentration, the conductivity was gradually enhanced, and it was found that all three polymers yield a saturated conductivity at 4 mg mL−1N‐DMBI concentration. The average conductivities are found to be 17.5, 90.1, and 40.1 S cm−1 for PO8, PO12, and PO16, respectively. The highest 𝜎 of PO12 is over five and two times higher than those of both PO8 and PO16, respectively. In order to highlight the crucial role of sequential doping, we also performed blending doping for three polymers. As shown in Figure −1, respectively, at optimal dopant ratio. Hence, compared to sequential doping, the blend doping leads to the inferior conductivity, mainly attributed to the reduced ordering of polymer morphology when blended with dopant.Thermoelectric devices were fabricated and characterized in glovebox to minimize interference by Oσ difference for three polymers, the carrier concentration (n) and mobility  were obtained by AC magnetic field Hall measurements. At optimized doping concentration, the doped PO12 exhibited a significantly higher carrier concentration of 9.04 ± 0.4 × 1020 cm−3 in comparison to two other polymers (PO8: 6.18 ± 0.1 × 1020 and PO16: 8.30 ± 0.1 × 1020)  and PO16 (0.33 ± 0.2 cm2 V−1 s−1). The results demonstrate that the doped PO12 film achieved efficient charge transport and large mobile carrier concentration synchronously, which directly contributed to the higher conductivity. Furthermore, the doping efficiencies of three polymers at optimized doping concentration were estimated to be 37.6%, 63.3%, and 66.4% for PO8, PO12, and PO16 films, respectively, based on the carrier concentration. Note that the values of doping efficiencies may not be the real ones due to the great challenge of obtaining the densities for three polymers, the comparison of the relative trends should be meaningful. For PO12 and PO16, the large values of doping efficiencies indicate higher doping levels, which is likely originated from both relatively low crystallinity benefiting the penetration of dopant molecules (vide infra).To gain insight into the S) of the doped polymer films was further probed by systematically varying temperature gradient (ΔT) across the samples from 0 to 2.8 K with a step of 0.7 K then back to 0 K. The related S and calculated PF values are summarized in Figure S values gradually decrease as N‐DMBI concentration increases due to the fact that S is in negative correlation with charge carrier concentration. As a result, low dopant concentration delivered significantly higher S as compared to high concentration. By balancing σ and S, the highest PFs are achieved at 1, 2, and 1 mg mL−1 concentration of N‐DMBI for PO8, PO12, and PO16, affording the value of 13.1 ± 1.2, 92.5 ± 2, and 57.8 ± 4 µW m−1 K−2, respectively. Clearly, the PO12‐based devices attained the highest OTE performance than the shorter branched side‐chain functionalized PO8‐ and longer side‐chain functionalized O16‐based devices, attributed to the optimized morphology (vide infra), large charge mobility, and high doping efficiency of polymer PO12. To the best of our knowledge, the PF of 94.3 µW m−1 K−2 and conductivity of 92 S cm−1 are among the highest values for the solution‐processed n‐doped polymers  first. As displayed in qz value of 0.37 Å−1 (corresponding to a lamellar stacking distance of 17.0 Å) in out‐of‐plane (OOP) direction and a pronounced (010) diffraction peak at 1.79 Å−1 (corresponding to a π–π stacking distance of 3.51 Å) in plane (IP) direction.Two‐dimensional grazing incidence wide‐angle X‐ray scattering (2D‐GIWAXS) characterization was further employed to investigate film crystallinity and polymer packing. As shown in Figure qz = 1.74 Å in combination with a (100) scattering at qxy = 0.27 Å−1 (lamellar stacking distance of 23.3 Å) in IP direction. Among them, PO8 exhibited an edge‐on orientation with the strongest crystallinity, which matches well with its highest electron mobility in OTFTs. After doping, three films still maintained the orientations of the annealed ones, indicating negligibly disrupted crystalline domain and molecular orientation using sequential doping strategy. The existence of multiple parallel and perpendicular orientations of polymer chains which can form 3D conduction channels is conducive to high charge mobility in OTE devices due to the fact that grain boundaries (or traps and defects) exist in polymer microstructures. The relatively large ravine of grain boundaries (or traps and defects) exist in polymer PO12 microstructures compared with PO8 and PO16 with single orientations would be beneficial for dopant permeation, thus leading to the fast doping process. Moreover, PO12 and PO16 with the relatively low crystallinity and large packing distance of polymer chains (both lamellar and π–π stacking distances) should better accommodate dopant molecules than PO8 after doping due to the fact that the dopants or dopant cations tend to exist and migrate in the amorphous regions and irregular domains. Thus the 3D conduction channels together with appropriate crystalline phase of polymer PO12 can synchronously deliver fast charge transport and high n‐doping efficiency, thus leading to the large electrical conductivity and PF.After thermal annealing, higher order lamellar diffraction (200) emerged in the OOP direction and a stronger (010) π–π stacking diffraction peak in the IP direction can be found for annealed PO8, indicative of the improved film crystallinity in comparison to as‐cast film. For annealed PO12 film, it was found that the lamellar diffractions also progress up to (200) in the OOP direction and obvious (010) diffraction peaks appear in both OOP and IP directions, suggesting bimodal orientation with both face‐on and edge‐on fractions. Unexpectedly, the orientation of annealed PO16 changes to face‐on orientation with a broadened (010) diffraction peak along the OOP direction at FigureTo better illustrate the topographic differences of doping process between three polymers and dopant, 3−2 V−1s−1 with gradual increase of side‐chain size. For polymer PO8, the achieved highest mobility is attributed to its close molecular packing and favorable edge‐on orientation as evidenced by 2D‐GIWAXS characterizations. Interestingly, PO12 with the medium side‐chains has moderate crystallinity and bimodal orientation, benefiting to penetration of the dopant into polymer, which leads to formation of well interconnected matrix with efficient charge transport network and 3D conduction channels. Therefore, PO12 exhibited a highest n‐doping efficiency when n‐doped with N‐DMBI. As a consequence, PO12 delivered excellent electrical conductivity of 92.0 S cm−1 and power factor of up to 94.3 µW m−1 K−1, both of which are among the highest value for n‐type polymers. Overall, our systematic study demonstrates that tuning the oligo(ethylene glycol)‐type side‐chain size is a very straightforward and powerful approach to equilibrating the doping level and charge mobility, leading to improved conductivity and thus promoting the OTE performance. We believe that these findings provide important guidelines to develop efficient n‐type polymers to advance of the OTE field.In conclusion, we designed and synthesized three fused bithiophene imide dimer‐based n‐type polymers PO8, PO12, and PO16 decorated with distinct OEG side‐chain. Varying the length of side chains enables us to tune the film crystallinity and packing orientation of polymer chains. It was found that PO12 and PO16 with larger side‐chains show relatively redshifted absorption compared with PO8 and the FMOs slightly become lower‐lying with the increase of side‐chain size. When applied in OTFTs, PO8, PO12, and PO16 exhibited a monotonic mobility decrease from 0.015 to 0.013 and to 0.008 cmThe authors declare no conflict of interest.Supporting InformationClick here for additional data file.


During space missions that travel beyond the cocoon of the Earth’s magnetosphere, astronauts are subjected to the microgravity and radiation stressors of outer space. Understanding and mitigating the adverse effects of microgravity and space radiation impose profound challenges for future missions to Mars and back and future Lunar missions. In recent years, cellular and molecular signaling in space biology has become a vital research topic. Therefore, we are pleased to present this Special Issue entitled “Cellular and Molecular Signaling Meet the Space Environment,” which delves into the significant advances and challenges that face research in space biology and the life sciences community.Microgravity and space radiation experienced during spaceflight, especially beyond low Earth orbit (LEO), clearly affect cellular and molecular signaling pathways, leading to alterations in cell signaling , remodelIn this Special Issue, the molecular mechanisms of gravitational alterations using rodents and cell culture models have been covered. One of the articles in this issue focuses on the impact of hypergravity exposure on post-translational histone modifications in the thymus of mice . CalcagnFurthermore, Blottner et al.  conducteFrom clinical aspects, Guilhot et al.  reportedIn addition to research articles, this Special Issue includes review articles and perspectives that provide a broader perspective on cellular and molecular contributions to health hazards from deep space missions. One such article discusses the hazards of outer space, particularly the impact of ionizing radiation and microgravity on the health of astronauts, with a focus on the increased risk of gynecological cancer in women. Women historically have been permitted to spend less time in space due to their higher incidence of radiation-induced cancers. The aim of the article is to provide a summary of existing research and identify further studies that are needed to ensure safer space exploration and better post-flight screening and management for women astronauts .Overall, this Special Issue presents a comprehensive overview of the current state of research that explores the cellular and molecular mechanisms that underlie space biology . The art


Accurate prediction of molecular property holds significance in contemporary drug discovery and medical research. Recent advances in AI-driven molecular property prediction have shown promising results. Due to the costly annotation of in vitro and in vivo experiments, transfer learning paradigm has been gaining momentum in extracting general self-supervised information to facilitate neural network learning. However, prior pretraining strategies have overlooked the necessity of explicitly incorporating domain knowledge, especially the molecular fragments, into model design, resulting in the under-exploration of the molecular semantic space.We propose an effective model with FRagment-based dual-channEL pretraining (FREL). Equipped with molecular fragments, FREL comprehensively employs masked autoencoder and contrastive learning to learn intra- and inter-molecule agreement, respectively. We further conduct extensive experiments on ten public datasets to demonstrate its superiority over state-of-the-art models. Further investigations and interpretations manifest the underlying relationship between molecular representations and molecular properties.Our proposed model FREL achieves state-of-the-art performance on the benchmark datasets, emphasizing the importance of incorporating molecular fragments into model design. The expressiveness of learned molecular representations is also investigated by visualization and correlation analysis. Case studies indicate that the learned molecular representations better capture the drug property variation and fragment semantics.The online version contains supplementary material available at 10.1186/s12859-023-05413-x. One of the most foundational and crucial tasks in the domain of drug discovery pertains to the accurate prediction of molecular properties. Compared with conventional in vitro and in vivo experiments, computational methods have the potential to expedite the overall process of identifying better drug candidates with specific characteristics , 2. In gDue to the inherent benefits of graphs in representing molecules, graph-based models, ranging from convolutional  to spatiDespite of some encouraging headway, most of the prior studies tend to overlooked the potential benefits of incorporating domain knowledge into model architecture, which can explicitly integrate biochemical information into model training. In the domain of pharmaceuticals, molecular fragments are of vital importance in determining molecular properties. For example, adrenergic receptor agonists with catechol structure (catechol hydroxyl group) are easily decomposed by COMT (catechol O-methyltransferase) in vivo, with poor stability and short action time, which affects the effectiveness of the drug. In comparison, adrenergic receptor agonists with non-catechol structure have much stronger stability . MoreoveMotivated by intuitive inspiration and exploratory experiment, we propose a novel and effective framework with FRagment-based dual-channEL pretraining (FREL), that comprehensively employs generative learning and contrastive learning to achieve intra- and inter-molecular agreement, respectively. The overall framework is demonstrated in Fig. With intuitive biochemical inspiration and convincing exploratory experiment, we rethink the necessity to incorporate molecular fragment into model design in molecular property prediction tasks.We propose a novel dual-channel self-supervised pretraining strategy to learn intra- and inter-molecule agreement, enabling effective molecular representation learning.We evaluate our method on extensive molecular property prediction tasks. Experimental results demonstrate that FREL achieve superior performance compared with competitive baselines. Further experiments investigate the expressiveness of learned molecular representation.We evaluate the performance of our FREL model on 10 widely-used benchmark datasets from MoleculeNet  that covMolecular pre-training, achieved through self-supervised training on massive amounts of unlabeled upstream data, enables models to capture rich semantic information about molecules. This research paradigm has demonstrated its effectiveness in enhancing predictive performance on downstream tasks. In the context of graph-based molecular pre-training, early works focused on adapting classical graph self-supervised methods to molecular graph training. Methods such as AttrMask, ContextPred , GPT-GNNHowever, traditional graph self-supervised learning often overlook the incorporation of domain-specific knowledge in the molecular domain, which can impact the positive transfer brought by pre-training. In recent years, tailored pre-training strategies specific to molecular graphs have been proposed, broadly categorized into atom-level strategies and fragment-level strategies. GraphMVP , 3D InfoHowever, prior work has not adequately integrated unsupervised training strategies with the introduction of domain-specific knowledge (such as molecular fragments), which hinders exploration of intra- and inter-molecular semantics. Therefore, we aim to explore the possibilities for a more integrated approach in this regard.RQ1 . Does the proposed model bring positive transfer and outperform state-of-the-arts on molecular property prediction tasks?RQ2 (Representation expressiveness). How expressive are pre-trained molecular representations?RQ3 (Ablation studies). How do the different channels contribute to the model performance?RQ4 . How does different hyperparameters affect model performance?We first provide a brief introduction of the experimental configurations, with more detailed settings available in the Methods section. We then demonstrate the performance of our proposed FREL on various property prediction tasks. Additionally, we leverage visualization and case studies to better showcase the superiority of the learned representations. Lastly, we present the results of ablation experiments and sensitivity analysis.In this section, we present empirical evaluation of our proposed FREL model and demonstrate its effectiveness. Specifically, the experiments aim to investigate the following research questions.We choose GEOM-Drugs  as the pGeneric graph SSL models: AttrMask, ContextPred , InfoGraMolecular SSL models: GROVER-Contextual (GROVER-C), GROVER-Motif (GROVER-M) , MGSSL , GraphMVFor comprehensive comparison, we select the following two groups of Self-Supervised Learning (SSL) methods as primary baselines in our experiments.We evaluate the performance of our model differently depending on the task. For classification tasks, we use the Area Under the Receiver Operating Characteristic curve (ROC-AUC) as the performance metric, where higher values indicate better performance. For regression tasks, we use Root Mean Squared Error (RMSE) as the performance metric, where lower values indicate better performance. The TPR, FPR and RMSE are formalized as follow:ous work .The performance of molecular property prediction tasks is summarized in Table We make other observations as follows. Firstly, compared with randomly initialized baseline, FREL obtains more accurate and robust predictions, indicating that our pretraining framework can capture useful knowledge from large, unlabeled datasets and migrate the learned semantics to downstream tasks without negative transfer. Secondly, we can observe that prior work has already achieved promising performance, especially in scaffold split settings. For example, Mole-BERT, as the current SOTA methods, only obtains a 1.2% absolute improvement over its best baseline GraphMAE in terms of average ROC-AUC. Our model expands the limits of performance without extensive hyperparameter tuning, achieving an absolute improvement of up to 0.9% in terms of average ROC-AUC over Mole-BERT. Lastly, it is shown tha second-best models often fail to achieve robust performance gains on most datasets, which can be attributed to the diversity of downstream drug properties. For instance, although GROVER-C achieved second-best performance on the BACE dataset, it exhibits poor performance on the MUV dataset. In contrast, our proposed framework achieve robust performance on diverse drug property prediction tasks, highlighting the robustness of FREL.To further demonstrate the effectiveness of our proposed model FREL, we further conduct experiments on molecular property regression on the ESOL , Lipophi2It is seen from Table Although we have incorporated information on molecular fragments through explicit model design, the black-box nature of deep learning still hinders our understanding of the specific reasons behind performance improvements. Based on the experimental results mentioned above, we will attempt to provide some hypotheses for performance improvements based on the characteristics of the specific dataset.Tox21, Toxcast, and Sider are datasets that provide information on chemical toxicity, toxicological assessment, and side effects and adverse reactions (ADR) of listed drugs. These datasets are relevant to the study of drug toxicity, specifically its side effects. Our research suggests that the success of these datasets can be attributed to the identification of structural alerts and toxicophores, such as aromatics and nitro groups, which are associated with hepatotoxicity. These functional groups are essential components of drugs and cannot be easily replaced. .The blood-brain barrier (BBB) is a highly selective interface between the circulating blood and the brain extracellular fluid, which serves to protect the brain from potentially harmful foreign substances present in the bloodstream. BBBP refers to the permeability of the BBB, which is determined by several factors such as the size of the molecule, the expression of relevant transporters and enzymes, and lipid/water solubility. While the functional groups of a substance may affect its lipid/water solubility, they cannot directly alter the permeability of the BBB. As a result, the impact on the permeability of the BBB is limited, which may explain why the outcomes of our experiment were not as optimal as we had hoped. .Drug molecular fragments play a significant role in the inhibition of HIV-1 replication, where the same functional groups have similar antiviral activity. Take tenofovir for example, and a series of aryl phenoxy-amidate derivatives of it, showed potent activities against the replications of HIV-1 . FurtherThe ESOL and Lipophilicit datasets describe the hydrophilicity and lipophilicity of drug molecules, the ratio of a drug to its lipid/water distribution. Compared with macromolecules, the larger the molecular weight, the more lipophilic. Since most molecules in production and life are smaller, the lipid/water solubility of molecules is mainly affected by functional groups. For example, the presence of -COOH significantly increases the hydrophilicity of a molecule. Therefore, our model achieves better performance .Malaria is a data set on antimalarial drug inhibitors collected by GlaxoSmithKline ( GSK ). This data set discloses the structure of effective, drug-like antimalarial compounds in the hope of finding the key to new malaria treatment. These compounds exhibit higher molecular weight and hydrophobicity index compared to other compounds. We speculate that the success of this experiment may be attributed to these characteristics of the compounds in the dataset.Note that most of the datasets we used for downstream tasks are ADMET property prediction tasks: chemical Absorption (A), Distribution (D), Metabolism (M), Excretion (E), and Toxicity (T), and we thus group the ten end tasks according to their prediction targets in the following analysis. We provide detailed analysis as follows:We use t-SNE (t-distributed Stochastic Neighbor Embedding)  to intuiA and D from Fig. After pre-training, the representations obtained by the model exhibit clustering characteristics, with similar labeled representations being closer to each other, and representations with dissimilar labels being distributed further apart, thereby enhancing the discriminability of molecules belonging to different categories. This is beneficial for improving the performance during downstream classification and regression. In contrast, the non-pre-trained model performs poorly in this regard. As shown in figure To better explore the expressiveness of the learned representation obtained from model after pre-training, we draw the scatter plots of the distance between the molecular representations after t-SNE dimensionality reduction and the absolute value distance between their true labels on three regression datasets, as illustrated in figure G and H from Fig. Based on the aforementioned correlation analysis, we conduct a case study on the HIV dataset to further verify the relationship between the distance learned between representations and the difference in molecular properties. Since the HIV dataset evaluates whether molecular compounds are able to inhibit HIV replication (positive or negative), we randomly selected three sets of molecular instances for observation, namely positive-positive, positive–negative, and negative-negative. The results are shown in Fig. It can be observed that representations of molecules with the same properties are generally closer to each other, with distances ranging from Aromatic Ring Counting and (2) Hydroxyl-Containing Molecules Solubility Regression. The description of experimental settings are as follow:For aromatic ring counting, we randomly draw 10K molecules from GEOM-Drugs dataset to test whether model pretrained with different strategies can recognize the number of aromatic rings of each molecule, which is an informative descriptor determining various drug properties . The perFor the hydroxyl-containing molecules solubility regression, we select all molecules with hydroxyl groups from the ESOL dataset. We then perform a regression task on their water solubility using the same experimental setup as described in the Experimental Configurations. The performance in terms of Rooted Mean Squared Error(RMSE) are shown in Table To support our key motivation and justify that FREL enables better learning of fragment semantics compared to other atom-based pretraining strategies, we further conduct two experiments, including (1) Given the intimate relationship between the experiments we proposed and molecular fragment information, the performance of these experiments can serve as an indicator of the capability to capture molecular fragment semantics. A superior performance signifies a stronger proficiency in capturing the semantic of molecular fragments. Based on the results from Table –FREL –FREL We report the performance of model variants in Additional file To answer RQ3, we conduct ablation studies on the effect of different pretraining channels to verify that different modules of FREL can independently provide beneficial impact. We consider the following model variants for further inspection. Except the modifications in specific modules, other implementations remain the same as previously described.entclass1pt{minimam and temperature coefficient Moreover, we further evaluate the performance of FREL with respect to two model-specific hyper-parameters: the mask ratio Prior works on drug property prediction have two main limitations. Firstly, they tend to overlook the effectiveness of explicitly incorporating molecular fragment information into model design, despite the crucial role that molecular fragments play in determining molecular properties. Secondly, the effective utilization of both intra- and inter-molecular relationships for self-supervised pretraining has not been adequately addressed, resulting in suboptimal molecular representation learning.Our model has demonstrated the ability to partially mitigate the aforementioned issues and yield performance improvements. However, there are still some limitations to address. Currently, most molecular pre-training models are based on the GIN encoder, which tends to have a smaller parameter count due to challenges such as over-smoothing , 56 and Furthermore, the method of fragmenting molecules based on BRICS decomposition is rather crude, while the approach of decomposing molecules into functional groups based on chemical definitions is overly meticulous, thus limiting effective exploration of the chemical semantic space. Consequently, an unresolved issue is how to identify valuable molecular subgraphs for pre-training strategies. In the future, we aim to find effective solutions to these open-ended questions that can drive drug discovery forward.Pretraining methods have emerged as a prominent research focus in the field of drug property prediction. Nevertheless, prevalent pretraining methods in the field often lack explicit incorporation of biochemical knowledge and exhibit a limited scope in the design of self-supervised strategies. To this end, we propose a novel framework, coined FREL, which comprehensively employs generative learning and contrastive learning to achieve intra- and inter-molecule agreement, respectively. Our approach explicitly integrates molecular fragment information into the model design. We evaluate the effectiveness of FREL on ten benchmark datasets and achieve the state-of-the-art performance. Further empirical analysis supports our key motivation that molecular fragment has the potential to boost the performance of drug property prediction. Overall, our work highlights the necessity of incorporating molecular fragments into model design and provides a promising solution for drug property prediction task.u and v. The feature of node v and edge  with D dimension are denoted as v, its representation vector k-th layer is formalized byv, K is the number of GNN layers. The graph representation vector K) and denote v and denote We begin by introducing some common notations for Graph Neural Networks (GNNs) and outlying the key concepts used in this work. Each molecule can be represented as an undirected graph, with atoms as nodes and chemical bonds as edges. Let Following generic “pretrain, fine-tune” pipelines, we first pretrain a simple GNN model with self-supervised objective and then fine-tune it on the downstream molecular property prediction tasks. The core idea of the FREL framework lies in the design of self-supervised objective, which facilitates the learning of underlying biomedical semantics by the model. The overall pretraining process involves two perspectives, known as dual-channel pretraining, which includes contrastive learning and generative learning channel. In the subsequent fine-tuning phase, we take the weights of the learned model and tune it on the labeled datasets with supervised information.In the following, We first elaborate on the two pretext tasks specialized for molecular fragment and introduce a integrated objective for pretraining. Then, we justify the effectiveness of our pretraining strategy from the perspective of information theory.Contrary to prior works that generate augmented views from local and global aspects with random perturbation –59, our To be specific, we first leverage the GNN encoder to obtain node embeddings for both views. For the first view, we take the mean of node embeddings belonging to the same fragment as fragment representation. Then, we perform fragment-level self-attention to further capture the correlation between different substructures and make weighted pooling based on attention coefficients. The second view is obtained by simple mean pooling upon node embeddings. Eventually, we employ a contrastive objective to enforce the embedded molecular views agree with each other and can be discriminated from embeddings of other molecules.m and scalar value In our FREL model, we use BRICS algorithm  to decom network  that leaFor any molecule While contrastive learning maximizes the agreement between molecule pairs, generative learning, on the other hand, extracts unsupervised signals from the molecule itself. Prior graph masked auto-encoder (GMAE), which targets reconstructing graph structures and features, are mainly performed on the complete graph for recovery. However, it may undermine the intrinsic information (e.g. acidity and polarity of carboxyl) of molecular fragments when encoded in different molecules, thus impairs the prediction performance.sensitivity and low selectivity problem [To this end, we propose to conduct GMAE at fragment level to preserve intrinsic information where possible. Formally, we randomly select partial nodes to constitute a subset GraphMAE , we leve problem . The genRecalling that the overall optimization objective has the form of the summation of contrastive loss and generative loss. In this section, we further provide a deeper insight into the theoretical support of our optimization objective. We demonstrate that minimizing the total loss The sum of mutual information can be lower bounded bywhere Intuitively, the result of theoretical analysis tells us that with the continuous optimization of model parameters, on the one hand, contrastive learning improves the mutual information among positive samples by comparing them with negative samples, which learns the agreement between molecules; generative learning, on the other hand, improves the mutual information between the original input and the encoded representation by reconstruction loss, which learns the agreement within molecules. Overall, by constructing high-quality contrastive samples and obtaining better masked representations with molecular fragments, we simultaneously learn the intra- and inter-molecule agreement, which is the key to the effectiveness of our proposed model FREL.For fair comparison with the other pre-trained models, we choose GEOM-Drugs  as the pPhysical chemistry.The ESOL dataset [Biophysics.The HIV dataset  [Physiology.The Blood-brain barrier penetration (BBBP) dataset [ dataset  contains dataset  and reco Screen)  was deve Screen)  was sele(BACE-1) . The Mal(BACE-1)  gauges d dataset  models t dataset  and ToxC dataset  are all  dataset  is a datFor those datasets for fine-tuning, we follow OGB  that useGeneric graph SSL models: AttrMask, ContextPred , InfoGraMolecular SSL models: GROVER-Contextual (GROVER-C), GROVER-Motif (GROVER-M) , and GraIn the pretraining stage, all the above SSL approaches are trained on the same dataset based on GEOM-Drugs. We also report performance with a randomly initialized model as the non-pretraining baseline. To ensure the performance is comparable with existing work, we report most of baseline performance from previously published results [For comprehensive comparison, we select the following two groups of Self-Supervised Learning (SSL) methods as primary baselines in our experiments. results . However results  and repoAll of the experiments are deployed on a computer server with 4 NVIDIA GeForce RTX 3090 GPUs (with 24GB memory each) and 256 AMD EPYC 7742 CPUs. We adopt Glorot initialization  for the In the selection of the pre-training backbone model, all of the baseline methods and our model follow the widely-used settings proposed by Hu et al. . On one m for generative learning are two highly relevant parameters for the performance of FREL. We conduct detailed discussions and experimental explorations on these parameters in the sensitivity analysis section. The source code of our experiment is available at https://github.com/Ruowu9944/FREL.For other hyperparameters used in model training, we follow the settings used in GraphMVP  and assuAdditional file 1. Detailed description of exploratory experiment.Additional file 2. Ablation study with different channel.Additional file 3. Performance variation with hyper-parameter m and Additional file 4. Proof of Theorem 1.


The proposed pandemic instrument — with its focus on prevention, preparedness and response — represents an ideal opportunity to develop and adopt a unifying global target that catalyzes global action on AMR. We propose three key characteristics of a unifying global target for AMR that — if embedded within the pandemic preparedness instrument — could rally public support, funding, and political commitment commensurate with the scale of the AMR challenge.Ensuring that life-saving antimicrobials remain available as effective treatment options in the face of rapidly rising levels of antimicrobial resistance will require a massive and coordinated global effort. Setting a collective direction for progress is the first step towards aligning global efforts on AMR. This process would be greatly accelerated by adopting  Antimicrobial resistance (AMR) is a substantial threat to human and animal health, global economies, and the environment. Increasing drug resistance is already manifesting in longer hospitalizations, higher morbidity and mortality, and rising healthcare costs associated with infections that were, until recently, considered treatable.unifying global target — a defined global goal that unites all countries and sectors in their collective efforts to address AMR. Without a global target to rally support, past efforts to address AMR have lacked the necessary level of ambition and coordination to secure a future with sustainable antimicrobial use for all.Box 1Summary of Three Recommended Characteristics of a Unifying Global Target for AMRA unifying global target should act as a barometer of global progress across all countries and sectorsTo ensure global collective action, a unifying global target for AMR should act as a barometer for global success and should provide an overview of collective progress across human, animal, and environmental sectors to meaningfully address AMR in ways that matter to people.A unifying global target should conceptually unite many technical perspectives as a single clearly communicated conceptPoliticians and the public are the primary audience for a unifying global target and as such, the target must prioritize clarity and accessibility. Rather than selecting one or more technical indicators, the unifying global target should conceptually unite many technical perspectives or indicators as a single easily communicated concept that is universally valued and inherently important.A unifying global target should be action-oriented to give identifiable moments of successTo rally support for global action on AMR, a unifying global target must include clear steps to make progress on the goal and offer the opportunity for identifiable moments of success.Setting a collective direction for global progress is the first step towards aligning global efforts on AMR. This process would be greatly accelerated by adopting a A unifying global target is a high-profile goal with a particular emphasis on raising attention and catalyzing action on key global issues. Unlike the indicators, monitoring strategies, and benchmarks that emerge from the goal and allow technical experts to track progress toward it, the intended audience of a unifying global target are politicians and the general public. High-profile examples of unifying global targets are the Millennium Development Goals (MDGs), Sustainable Development Goals (SDGs), and UNAIDS’ 90-90-90 goal.Goals are powerful tools in global governance, catalyzing action on the international stage in much the same way as individual or small group action. At their core, goals act as vehicles for global norms, help to direct attention and effort towards goal-relevant activities, serve an energizing function, and motivate persistence so that efforts are extended over longer periods of time.Since goals embody and exercise various forms of power, the act of goal-setting is an inherently political process. Global goals represent a shared aspiration for the stated objective, suggesting that the goal, and the norm that it embodies, are universally desirable for the future. Translating the global goal into indicators can also pose political challenges, despite being a largely technocratic process. Indicators must be able to meaningfully measure how well a country is performing on a particular aspect of the goal.1.Given the global nature of AMR and our inability to isolate the spread of resistance to particular regions, it is essential that AMR is perceived as a global issue requiring global collective action. Attempts to adopt simple goals that can be measured at the national level in other areas of global health have failed to achieve the intended effects of the unifying global target.In the past, some goals have been designed through the lens of international competition and have been perceived as an opportunity to rebuke or discipline of underperforming countries. Once goals are set and transformed into indicators, country actions can be measured, evaluated, ranked, and compared against the performance of others. In theory, goal setting can help countries ‘self-regulate’ or pressure laggard states toward a norm for fear of reputational consequences, while the use of progress indicators can be used to allocate resources and penalties.This ranking approach to goal setting is out of step with the purpose of a unifying global target. Given the global nature of AMR and our inability to isolate the spread of resistance to particular regions, it is essential that AMR is perceived as a global issue requiring global collective action. Attempts to adopt simple goals that can be measured at the national level in other areas of global health have failed to achieve the intended effects of the unifying global target. The MDGs, for example, characterized as a “report card for global development”Although its indicators may facilitate naming and shaming, a unifying global target should primarily act as a barometer of global progress on the global issue and will ideally not even be measurable at the national level. This is the case for the Paris Agreement’s unifying target: the success or failure to maintain average global temperatures below 2°C above pre-industrial levelsFinally, for multisectoral challenges, a successful unifying global target must be applied cross sectors to show a complete picture of global successes and failures. A target that exclusively relies on data on human health may not accurately represent global progress on AMR in animal and environmental sectors. A unifying global target must aggregate the actions of diverse industries and present a single clear message. Experts may use technical indicators to assess the appropriateness of antimicrobial use in individual sectors; however, a unifying global target should portray whether action across sectors is adding up to an appropriate, significant, sufficient response. This has been done in the case of the Paris target which represents the global progress; technical indicators are used by experts to assess specific challenges around greenhouse gas concentrations, warming, emissions, ice melt, and pollution, but these do not represent the full picture of the global response. In the case of AMR, the contributions — both towards the problem and towards progress — of all One Health sectors  need to be aggregated into a single goal.2.An effective global goal must strike a balance between accurately reflecting progress on the nuanced scientific issue of AMR while also being clear and easily understood by the primary audience: politicians and the general public. As such, a unifying global target should not be a biological indicator or other technical metric typically used by specialists for monitoring the evolution of AMR.While global goals can include multiple indicators, the overall direction should be clear, and the specific actions that will be necessary to make them successful must be directly conveyed.3.Above all, a global AMR goal needs to act as a rallying cry around which the international community can mobilize. Currently, the dominant narrative is that AMR is a looming crisis with an extremely bleak prognosis.Eradication goals, such as efforts to eradicate smallpox, rinderpest, and polio, have been largely successful unifying global targets, rallying substantial support over decades in part through their success stories and clearly identifiable action steps. The 2020 rallying cry to “flatten the curve” during the early COVID-19 pandemic — which referred to slowing the rate of new infections in order to reduce the peak of the epidemic curveBox 2Previously Proposed and Existing AMR Goals, Indicators and TargetsPercent reduction in bloodstream infections (United Nations 2020)The Sustainable Development Goals include a target to reduce blood stream infections.Antibiotic footprint In line with climate change ‘carbon footprint,’ the ‘antibiotic footprint’ has been proposed as a communication tool to illustrate the magnitude of antibiotic use across sectors with the goal of reducing individual and national footprints as much as possible.Target levels of antimicrobial useSeveral antimicrobial use targets or benchmarks have been proposed in Defined Daily Doses, miligrams of antimicrobials per kilogram of animal (mg/kg), milligrams of antimicrobials per Population Correction Unity (mg/PCU).Drug Resistance Index The Drug Resistance Index was developed to communicate changes in the proportion of disease-causing pathogens that are resistant to commonly-used antibiotics over time. The Index combines measurements of antibiotic consumption and resistance across multiple pathogen–organism combinations to create a single metric that represents an aggregate level of drug resistance, allowing for a global assessment of the relative efficacy of countries’ antibiotic therapy.Various metrics for analyzing and communicating AMR priorities or thresholds have been proposed . While eDrug Resistance Index was developed to communicate changes in the proportion of disease-causing pathogens that are resistant to commonly-used antibiotics over time. The Index combines measurements of antibiotic consumption and resistance across multiple pathogen-organism combinations to create a single metricThe proposed antibiotic footprintAnother proposed idea, the Selection of a unifying global target for AMR should be guided by the technical and political criteria considered above. Fortunately, the proposed pandemic instrumentThe creation of a unifying global target also creates opportunities to catalyze action to reduce inequity within global AMR action. The translation of global aspirations into national policies requires more than just setting a goal; it also requires countries to have sufficient resources and capacity to implement the actions needed to achieve the goal. This can be particularly challenging in low- and middle-income countries, where a one-size-fits-all solution may be more burdensome than in high-income countries. Failure to recognize this reality may disincentivize countries from participating in a global effort for which the costs may appear to outweigh the benefits. While some high-income countries have included funding for AMR within their international development programs, their aims are not globally coordinated and insufficient to resource a truly global effort. Articulating a unifying global target creates an opportunity to align funding and capacity building supports in service of the broader global goal.The proposed pandemic preparedness instrument represents an ideal opportunity to harness the power of international law to establish a unifying global target that catalyzes global action on AMR. While the majority of proposed AMR targets and indicators to date have been too technical to succeed as a unifying global target, the creation of a target that could act as a barometer of global progress across sectors, synthesize technical indicators into a single clearly communicated concept, and offer identifiable moments of success would represent a monumental step forward towards catalyzing collective action on AMR.


These stressors can select for AMR – even in the absence of antibiotics – via mechanisms such as cross-resistance, co-resistance and co-regulation. Moreover, anthropogenic stressors can prime bacterial physiology against stress, potentially widening the window of opportunity for the de novo evolution of AMR. However, research to date is typically limited to the study of single isolated bacterial species – we lack data on how intensive agricultural practices drive AMR over evolutionary timescales in more complex microbial communities. Furthermore, a multidisciplinary approach to fighting AMR is urgently needed, as it is clear that the drivers of AMR extend far beyond the clinical environment.Antimicrobial resistance (AMR) is a growing threat to public health, global food security and animal welfare. Despite efforts in antibiotic stewardship, AMR continues to rise worldwide. Anthropogenic activities, particularly intensive agriculture, play an integral role in the dissemination of AMR genes within natural microbial communities – which current antibiotic stewardship typically overlooks. In this review, we examine the impact of anthropogenically induced temperature fluctuations, increased soil salinity, soil fertility loss, and contaminants such as metals and pesticides on the  Antimicrobial resistance (AMR) is a pressing global issue expected to cause more than 10 million deaths annually in 2050 . While rde novo evolution, species sorting toward resistant taxa and enhanced horizontal transfer of AMR genes.Intensive agricultural practices have been highlighted as significant drivers of AMR , with co2 globally is covered by mine waste, a large proportion of which is located in populated areas . A recent scoping review article by Anedda et al.  examinedet al. . DespiteAnthropogenic activity is warming the climate at an unprecedented rate, with an average projected increase of 1.5–2 °C in the coming decades . ExtremeTopt) can cause cellular proteins to misfold, damage DNA and RNA, and increase membrane fluidity [E. coli, the HSR is regulated by the alternative sigma factor σ32 [Since the origin of life, microbes have been faced with temperature stress. In fact, microbial pathogens may have been the driving force behind the evolution of warm-blooded animals, as fever would be more effective at repelling infections in warm-blooded versus cold-blooded animals . Temperafluidity . Bacterifluidity . In E. cctor σ32 , charactctor σ32 . This HSE. coli with aminoglycosides  results in protein expression changes that are ‘virtually indistinguishable from that produced by a shift in temperature’ from 28 °C to 42 °C [et al. [E. coli physiological responses to low or high temperatures are clearly separated, and each is grouped with particular antibiotics that have similar effects to cold or heat respectively. For example, aminoglycosides, as well as nitrofurantoin and trimethoprim, all have similar physiological effects to heat stress (44–46 °C), while macrolides, tetracycline and fluoroquinolones emulate cold stress (22–37 °C). While the exact causes of this interaction similarity are unclear [Acinetobacter baumanii and E. coli [cspB – associated with the cold-shock response – can lead to an enhanced HSR and consequently increased resistance to heat-similar aminoglycosides and trimethoprim [It has been recently suggested that mechanisms of AMR are co-opted from such stress responses to temperature . Differeto 42 °C . More re unclear  it was h. coli . Moreoveethoprim . Togetheethoprim .E. coli, and hence is fitting for short-term rather than long-term temperature extremes. However, activation of the HSR could ‘prime’ bacterial populations for resistance before a heat-similar antibiotic is applied [Despite the potential for temperature stress to influence AMR via activation of the HSR, it is less clear whether temperature-similarity profiles feed into selection over evolutionary time. The HSR is generally transient (in the order of magnitude of minutes) in  applied . In thiset al. [E. coli growing at 37 and 42 °C, revealing differential expression of 1737 genes between the two temperature treatments. Downregulated genes at 42 °C included ribosomal constituents  involved in translation, amino acid biosynthesis, flagellum motility and ribonucleoside biosynthesis. Perhaps most surprisingly, however, is that growth at 42 °C resulted in the downregulation of heat shock proteins involved in the HSR, including subunits of core RNA polymerase (RNAP) rpoA, rpoB and rpoC. Similarly, most HSR encoding chaperones were also downregulated  at 42 °C. This result was explained by the fact that the gene-expression profiles were assayed at the mid-exponential phase, at which point the HSR was already turned off in this particular experimental setup. This suggests that the transient HSR might play a minimal role in priming populations for AMR. However, further experiments are needed to test if a short-term advantage could enhance selection for resistance over longer timescales.A tour de force by Rodríguez-Verdugo and colleagues  provideset al.  comparedE. coli populations under thermal stress (42.2 °C for 2000 generations) [rpoB) instead restored growth and allowed the cell to revert to a gene expression profile similar to the ancestral (pre-stressed) state [rpoB and incidentally conferring rifampicin resistance ranging from ×10 to ×320 higher than susceptible cells. Using constructed rpoB mutants with SNPs in codon 572 they confirmed that this particular rpoB mutation (i) conferred high levels of rifampicin resistance via alterations in RNAP, and (ii) increased growth relative to the wild-type at 42 °C. Their work shows that the interplay between the costs and benefits of bacterial stress responses across multiple timescales can dictate the spread of AMR, at least in E. coli.Rodríguez and colleagues also experimentally evolved 114 rations) . While id) state . In 12 pet al. [in E. coli, Klebsiella pneumoniae, and Staphylococcus aureus. Although the mechanism was not elucidated, it was speculated that increased temperatures accelerate HGT of AMR genes. Similarly, Reverter et al. [While the HSR could allow bacteria to tolerate short-term temperature extremes, more moderate increases in temperature could drive AMR evolution in multiple ways. Higher temperatures can have mutagenic effects by increasing replication errors and causing DNA damage . Increaset al.  found thr et al.  analysedr et al. . They foThe nutrient content of natural soils is declining on a global scale . ConversWhile the impact of soil fertility loss on plants is now evident , we knowσs) stimulates key physiological changes, including (i) genome compaction, (ii) reduced membrane permeability, (iii) increased production of osmoprotectants and (iv) decreased expression of growth-promoting genes [E. coli, rpoS mutations conferring σs overexpression can also have consequences for AMR – for example, a mutation in rpoS (87 D-6) can cause resistance to nalidixic acid [E. coli through prolonged incubation on agar plates also reveal the predictable emergence of rifampicin-resistant mutants, despite incubation taking place in the absence of antibiotics [β-subunit (rpoB) that enhance fitness under starvation while incidentally conferring rifampicin resistance [rpoB are also the cause of high-level β-lactam resistance in methicillin-resistant Staphylococcus aureus [, Salmonella enterica rspL mutants fail to induce the stationary phase sigma factor σs, causing them to outcompete the slow-growing wild-type. These rspL mutations also enhance resistance to streptomycin [rspL mutants. This result is presumably due to poorer translational fidelity of the mutant relative to the wild-type when nutrients are rich [When nutrients are scarce, physiological responses by bacterial cells can permit long-term survival. Activation of the stationary phase sigma factor S (ng genes . In E.xic acid . Studiesibiotics . This fiibiotics . Howeversistance . Mutatio in rpoS  D-6 can ptomycin . Interesare rich .E. coli in laboratory media (in the absence of antibiotics) reported reduced susceptibility to erythromycin (2–4× MIC), fosfomycin (2–6× MIC), rifampicin (2–32× MIC) and streptomycin (2–3× MIC) after 500–1000 generations of evolution [P. aeruginosa in M9 minimal media found that under nutrient-limiting (but not nutrient-rich) conditions, lasR mutations evolved that caused enhanced levels of antibiotic resistance (possibly via increased expression of efflux pumps) [P. aeruginosa lasR mutants are common in clinical settings, and typically display enhanced resistance to tobramycin [While stress response systems may drive AMR under nutrient limitation in the short term, experimental evolution approaches can reveal whether such responses will probably feed into long-term selection dynamics. One experimental evolution study of volution . AMR genx pumps) . Interesbramycin . While sbramycin . Trade-obramycin . HoweverThe loss of soil fertility is a complex problem, but solutions are relatively easy to implement. The EU Green Deal is encouraging the farming sector to adopt more sustainable methods, such as crop rotation, cover cropping, reduced tillage and better irrigation . These aIntensive agricultural practices have led to cultivating densely packed crop monocultures to make the most economical use of space. Unfortunately, these conditions also facilitate the success of ‘pests’ such as fungi, bacteria, viruses, insects, arachnids and rodents, as well as undesirable vegetation (i.e. weeds) . To mitiDespite being designed to target specific pests (i.e. fungicides ‘only’ target fungi), many pesticides have been shown to have harmful effects on humans and the broader ecosystem . PoliciesoxRS in E. coli [soxRS system can upregulate AcrAB efflux pumps which have been attributed to both pesticide and antibiotic resistances, including fluoroquinolones [de novo evolution of mutations in the AcrAB-TolC multi-drug export pump, causing cross-resistance to tetracycline and chloramphenicol [The first line of defence by bacteria against pesticides is the downregulation of membrane porins or upregulation of efflux pumps to remove the chemicals from the cell . For exa. coli . The soxinolones . Copper-phenicol . Mutatiophenicol  (cross-rphenicol .opd) have been identified in a plethora of soil-dwelling bacteria such as Flavobacterium, Pseudomonas, Bacillus and Agrobacterium [et al. [Geobacillus could dock with and hydrolyse streptomycin, ampicillin, chloramphenicol and cefotaxime. Furthermore, a plasmid-bound α–β hydrolase known to degrade organophosphate-degrading α–β hydrolases has been shown to reside on plasmids and provide resistance to a range of antibiotics [Many bacteria can also degrade pesticides into less harmful residuals . This biterium . However [et al.  have sugibiotics .S-transferases (GSTs). These isozymes are widely used by plants and insects as pesticide resistance mechanisms [Another group of enzymes involved in detoxification are glutathione chanisms . GTSs hachanisms . Howeverchanisms . Intereschanisms . Peroxidchanisms , it is let al. demonstrated that soils treated with glyphosate herbicides show an increased abundance of ARGs and MGEs compared to the non-herbicide-treated control [E. coli [E. coli grown in a lab-based medium containing a cocktail of 23 common pesticides revealed selection for mutations conferring streptomycin resistance [E. coli to pesticides and ampicillin selects for cross-resistance to ciprofloxacin, tetracycline and chloramphenicol, possibly due to mutations in transcriptional regulators responsible for oxidative stress defence or biofilm formation [Finally, the co-occurrence of resistance genes to pesticides and antibiotics on MGEs poses a significant risk to public health, enabling the rapid dissemination of antibiotic resistance in bacterial populations. Studies have shown that exposure to certain pesticides can facilitate the transmission of AMR genes on MGEs in natural populations  resistant species. These dynamics are frequently reported in the gut microbiota, where antibiotic treatment leaves the gut microbiota vulnerable to invasion by antibiotic-resistant ficile . Hence, Trichoderma have been used to control fungal plant diseases caused by Fusarium and Rhizoctonia [Given the accumulating evidence of pesticide use on the dissemination of AMR, it is important that policy is implemented to prevent further AMR spread and evolution. To address this issue, several solutions can be implemented. First, promoting integrated pest management practices that combine various eco-friendly methods, such as crop rotation, biological control and mechanical pest control, can help minimize pesticide reliance. Second, research into the development of pesticides targeted to a specific pest could significantly lessen the indirect impact on soil microbiota while still effectively controlling pests. Insect viruses, such as baculoviruses, are highly specific in their host range and could be used to target a single insect pest . Plant pzoctonia . Finally+, Cl−, and K+ influx and efflux; and (ii) increased biosynthesis or uptake of compatible solutes – which are compounds that mimic the osmotic properties of salts [Climate change brings increased levels of evaporation, low rainfall and global sea level rise . The infof salts . Both merffG, rffH and ISYNA1); monobactams ; carbapenem ; and penicillin (pac) [cusS and copS (causing reduced membrane permeability), as well as AbcA and BmrA efflux pumps conferring β-lactam resistance [et al. [tetM, sul1, ermB and intI1, but not tetV, mexk or bacA [High-saline environments have been associated with increased antibiotic production by resident microbes. For example, studies on rhizobia in mangroves show gradients of increasing salinity are associated with increased abundance of antibiotic biosynthesis genes encoding streptomycin (in (pac) . Converssistance . One stu [et al.  found th or bacA . Hence,  or bacA .Listeria monocytogenes, salt stress similarly increases the expression of LiaR – a response regulator involved in cell envelope stress and toxic ion responses [liaR gene increases the sensitivity of L. monoctytogenes to nisin [de novo mutants that have reduced antibiotic susceptibility. An experimental evolution approach could reveal how physiological responses to salt stress feed into selection for AMR over evolutionary time.Cross-resistance or co-regulation of salt resistance and AMR genes can enhance AMR under high salinity. For example, the EnvZ/OmpR membrane-bound histidine kinases are chemoreceptors which can detect changes in external osmolarity . These responses . Deletinto nisin . While stetM, sul1 and ermB, because they resided on MGEs containing salt stress resistance mechanisms [+ transporters [Actinobacteria in highly saline soils [MGEs can co-select for ARG in high-salinity environments. Metagenomic analysis of manure samples treated with increasing salt concentrations revealed that high-salinity environments maintain AMR genes chanisms . Similarsporters , 125, hasporters . Converssporters . This wane soils . Hence, The salinization of arable land is a growing concern, as land use intensifies amid the growing impact of climate change. In order to reduce or maintain soil salinity levels and prevent AMR dissemination, improved irrigation practices are required. This could be achieved by using efficient irrigation methods such as drip irrigation or precision agriculture; farmers can reduce water wastage and prevent the build-up of salts in the soil . HoweverAnthropogenic activities have increasingly led to accelerated climate change, environmental pollution and the disruption of natural ecosystems. These events have been identified as potential contributors to the proliferation of AMR . EmerginE. coli). The question remains about how relevant short-term stress responses are (which often temporarily enhance tolerance or antibiotic resistance) to long-term AMR selection. Moreover, the knowledge we have gained by studying stress responses in a single species  should now be expanded to gauge the role of stress response systems in natural microbial communities, where the cost and benefits of stress responses are likely to change [A myriad of studies linking bacterial stress responses to AMR stem from gene expression studies of knockout mutant strains lacking stress response gene(s) (e.g. sigma factor σ32 in o change . Semi-nao change ) are useet al. [P. aeruginosa comes at a population-level cost by selectively favouring siderophore 'cheats' that do not bear the cost of siderophore production but reap the metal-chelating benefits of siderophores produced by others [While our review focuses on how anthropogenic stress can drive AMR, trade-offs could equally influence resistance evolution. However, few studies have investigated trade-offs between mechanisms other than those targeting different clinical antibiotics . Using et al.  demonstry others . These ry others , whetherOur review highlights the profound role of natural environments in shaping AMR, and follows several excellent reviews in this area . However