Despite being researched for decades, shape-shiftingmolecularcrystals have yet to claim their spot as an actuating materials classamong the primary functional materials. While the process for developingand commercializing materials can be lengthy, it inevitably startswith building an extensive knowledge base, which for molecular crystalactuators remains scattered and disjointed. Using machine learningfor the first time, we identify inherent features and structure–functionrelationships that fundamentally impact the mechanical response ofmolecular crystal actuators. Our model can factor in different crystalproperties in tandem and decipher their intersectional and combinedeffects on each actuation performance. This analysis is an open invitationto utilize interdisciplinary expertise in translating the currentbasic research on molecular crystal actuators into technology-baseddevelopment that promotes large-scale experimentation and prototyping. The short- and long-range intermolecularinteractions are known to define both crystallinity and versatilemechanical properties of molecular crystals, govern their energy transduction,and maintain their long-range lattice order despite large deformations.3 However, the study of mechanical responsive properties of molecularcrystals, for the most part, has remained limited to isolated casestudies, entirely distracted from the holistic class of actuatingmaterials they represent. With the increased reporting, new applicationprospects have emerged and commanded the consideration of molecularsingle crystals as energy-harvesting and work-generating materials.6 Being at a unique intersection between soft and hard materials,7 these crystals appear to be a natural choicefor actuation elements in soft and microrobotics.8 Nonetheless, a clear definition of the capacity and limitationsof molecular crystals as an actuating class is still lacking and currentlyhinders their incorporation in actuator design. Indeed, many reportson responsive molecular crystals are phenomenological and often failto thoroughly evaluate their static and dynamic actuation performance.While characterizing the static response revealshow these crystals perform in either two states (fully loaded or entirelyfree), the dynamic response is the aspect that evaluatesthe efficiency of energy transduction into mechanical work under dynamicloading.9 Understanding the structure–functionrelationships through mapping out the working principles of each crystalexample could explain the behavior of the whole materials class. Itwould facilitate discovering new exceptional dynamic molecular crystalsand enable controlling, optimizing, and possibly customizing the performanceof previously studied crystals. While some solid-state molecular transformationsthat drive the mechanical response of molecular crystals have beenconsidered dramatic, these characteristics do not necessarily translateinto impressive actuation behaviors. Considering the chemical makeupin isolation of mechanical properties and crystal morphologies willoften fall short in explaining the actuation performance. Photodimerizationreactions in molecular crystals, for example, can result in crystalbending, axial expansion/contraction, or even twisting,15 leading to a wide range of actuation performance. Without understandingthe intersectional effects of various chemical and physical featureson the actuation performance, much will likely remain undiscoveredabout this emerging family of engineering materials.Knowledge can be public yet remain fragmentedand undiscoveredif the separately designed information is logically connected butis not retrieved and assembled to disclose patterns unintended andunseen before.16 However, no similarefforts have been employed yet to explore the vast number of reportedmolecular crystals. Collating a complete and extensive dataset remainsthe biggest challenge in inviting exploration of these materials throughmachine learning methods and accurate prediction models. While therehave been attempts to create a dataset of the mechanical propertiesof organic crystals, the analysis remained statistical.7Ensemblelearning methods have been implemented to guide the searchfor hard materials and predict the mechanical properties of thosenot yet characterized.Supporting Information). All possible actuationperformance indices were collected directly, calculated, or extractedfrom the data, images, and videos provided in the reports along withcommon categorical features, X-ray diffraction information, and chemical,physical, and mechanical properties . A statistical analysiswas conducted followed by establishing a machine learning model, forthe first time, that reveals the interconnected patterns and relationshipsbetween different crystal features and their collective impact oneach actuation performance index. Here, we aim to initiate a continuingholistic study, highlight critical data gaps needed to prepare thefield for fully utilizing machine learning tools, and invite interdisciplinarycollaborations in order to fast-track the advancement of molecularcrystals to the forefront of practical applications.In this work, the first comprehensive datasetof over 100 mechanicallyresponsive molecular crystals reported and characterized to date wascompiled . All crystal categories determined to have a significant pairwisedifference in performance  are considered features of fundamental relevance to the actuationbehavior of molecular crystals. While crystals responsive to any stimuliwere considered, photo- and thermo-activated molecular crystals werefound to be the primary contributors to the reported examples of thismaterials class. Photoisomerization reactions in azobenzenes and hydrazides,21 [2 + 2] and [4 + 4] photodimerization in anthracenes and organicacids,24 and cyclization of diaryelethenes27 are some of the most commonly reported photoinduced molecular transformationsin organic single crystals. Thermoresponsive crystals can undergoa variety of molecular transformations that can be categorized underconformational changes, molecular gliding, molecular rotation, ora combination thereof.28In order to highlight importantassociations between crystal featuresand actuation performance indices, a Spearman correlation matrix thatmeasures any monotonic pairwise relationship between all variablesconsidered in this study was constructed 1A. The S30 Diffusion-free strains induced homogenouslythroughout the crystal structure produce anisotropic expansions andcontractions.32 Depending on the kinetics and intensity of the chemical reactionand the mode of dissipation of the resulting elastic energy, the responsemight be in the form of motility, such as jumping, or even disintegration,costing the crystal its structural integrity and causing it to shatter.35 Given the different mechanics involved, the type of deformationinevitably has a direct effect on the amount of force that molecularcrystals can generate .The most critical predictions are shown in R2 was calculatedto determine how much of the variation in the dependent features (actuationperformance metrics) can be explained by the independent crystal featuresused as descriptors . Due to the lack of measurement errorsin the literature, all data points were treated as true values withequal weights and the dataset could not be tested for outliers. Missingdata, particularly for neglected performance metrics or ones thatare experimentally complicated to determine, such as work, power,and efficiency, also contributed to lower prediction accuracies. Nonetheless,the model can successfully determine the crystal features of primaryinfluence on each actuation performance metric. Here, the model’sexplanatory power of the associations made was prioritized over predictionaccuracy, which could be drastically improved by exploring higher-orderparameters and resorting to a black-box approach. However, the latterapproach renders the crystals’ structure–function associationspractically uninterpretable, which defeats the purpose of this study.The predictions were also binned into low, moderate, and high actuationperformance ranges determined by the quantiles of the entire dataset.Hence, this model can be used to focus on finding new responsive molecularcrystals with high actuation capacity as a first line of screening.Predictions for the range of free stroke have the highest accuracywith 93%. The prediction accuracy for the remaining actuation performancemetrics can be drastically improved by more extensive reporting onthese properties. The associations between each actuation propertyand its corresponding crystal features on which the machine learningmodel relies on heavily are dissected next.Given the inherent trade-off between the interpretabilityand accuracyof any prediction model and since our focus lies in understandingthe relationship between crystal features and the actuation performance,a parametric method was used to estimate the latter. Such method entailssimplifying the prediction of the actuation performance through afirst-order parametric form of crystal features and ranking them accordingto feature importance scores that reflect their importance in predictingany actuation performance metric  and their competitive edge forspecific applications. As expected, soft materials such as polymersshow high deformation capacity but generally have low force generation(39 However, unlike rigid actuators, elastic andsoft organic crystals can absorb and dissipate undesired excess forcegenerated at the actuator–load interface. This dampening effectturns these materials into better candidates for minimally invasiveapplications such as cell manipulation and micro-optics.In order to place molecular crystalson the global actuator landscape, neration3A. The oThe global materials property plots also revealedthat molecularcrystals produce volumetric work and power densities as low as thoseof gels or surpass high-dynamics actuators like muscles, bimetallicstrips, and fluidic devices. The balance between large actuation strainand high output stress—typically mutually exclusive properties—positionsmolecular crystals as high-work-density actuators. Their volumetricpower densities are higher than other soft single-material actuatorsand comparable to pneumatic devices. As new examples of responsive molecularcrystals are unearthed,it is essential to follow standardized performance evaluation methodsto avoid undervaluing or overestimating the actuation potential ofthese unique materials. We strongly recommend that future reportson new crystals include a thorough actuation performance analysis.Physical and mechanical properties such as the Young’s modulusand density are essential to draw better structure–functioncorrelations. Highlighting crystal features of particular importancecan guide and accelerate the quest for high-performing molecular crystalactuators, a search that is otherwise short-sighted. Our model canserve as the first level of screening to identify molecular crystalswith high actuation capacities prior to any experimental analysis.It is important to reiterate that while some correlations will inevitablyappear intuitive given the viable classical mechanics and chemistrylogic that explains them, this model serves to determine their importancein dictating the final actuation performance over other features.As we continue to improve this dataset and add new crystal featuressuch as mechanical property measurements, we expect this model tofurther highlight the interplay between different chemical, physical,and mechanical crystal properties. Insights unlocked in this studysubstantiate the correlations between the structure and function ofthese materials. These findings are invaluable in directing any futuresearch for molecular crystal actuators of exceptional performance.The results also call for large-scale collaborations that expand onour collected dataset of dynamic crystals to improve its statisticalsignificance and enhance the accuracy of the prediction model.


EGFR and ALK) are associated with poor response to immunotherapy, and failing to identify such patients results in poor outcomes [KEAP1 or STK11, as well as other molecules involved in tumor microenvironment, are becoming a subject of interest in immunotherapy research, and might eventually reach relevance for introduction in clinical practice [Non-small-cell lung cancer (NSCLC) is the major cause of cancer-related deaths worldwide, due to its high incidence and mortality . The chaoutcomes ,6; on thpractice ,8. Previpractice ,10. The The first consideration based on the current context is that the technology for the detection of molecular alterations is rapidly and constantly improving, with increasing sensitivity in terms of gene detection, including both acknowledged and novel, uncommon mutations; the second consideration takes into account the increasing availability of targeted therapies, with a non-negligible degree of variation among the different regulatory agencies. These improvements pose further challenges: on the one hand, pathologists and molecular biologists must continuously make efforts in terms of training and upgrades of laboratory tools; on the other hand, medical oncologists are required to make clinical decisions for patients with uncommon molecular alterations (including uncommon mutations in both acknowledged targets and uncommon novel targets), for which limited research is available so far, and targeted agents may exist while not being readily available through national healthcare services. An emerging approach to address these potential issues is represented by the institution of molecular tumor boards, which are expected to include personnel with the skills and resources needed for the optimal management of patients whose tumor harbors a complex molecular profile .MET alterations during treatment with EGFR inhibitors, the former approach appears more suitable when various, singularly uncommon, acquired mutations occur. One major limit to this approach is the necessity to re-characterize the tumor at progression, with potential discomfort for the patient and perception of time loss, especially when new actionable drivers are not identified. One possible answer to this issue is represented by the employment of liquid biopsy to detect novel mutations from peripheral blood. This emerging approach is rapidly evolving in terms of accuracy, and its potential applications are currently being explored in the translational and clinical setting. In particular, by making the molecular characterization more accessible compared with conventional biopsy, blood-based liquid biopsy allows for repeated sample collection from each patient, thus providing an unprecedented opportunity for longitudinal monitoring. Furthermore, the nature of liquid biopsy should make its molecular profile representative of the whole neoplasm, hence overcoming the limits of conventional biopsy due to tumor heterogeneity. Notably, while liquid biopsy is extremely promising, histology-based assessments, such as histotype diagnosis and the identification of morphologic shift during targeted therapy  are still beyond the possibilities of liquid biopsy [Another concept, strictly linked with the development of molecular biology and targeted therapy, is represented by the study of resistance mechanisms developed during treatment with targeted agents, which result in clinical disease progression. Notably, the identification of said mechanisms is expected to result in the development of novel therapeutic strategies designed to either manage and counteract resistance-based progression, or to prevent the occurrence of acquired resistance in first place . While td biopsy ,15,16.EGFR [Similar to other fields of medicine, molecular oncology is expected to benefit from the increasing applications of artificial intelligence (AI). In this context, predictive algorithms can provide a large amount of information able to aid in histomolecular diagnosis; two major examples of these applications are represented by digital pathology and radiomics. In digital pathology, AI-based algorithms are applied to scanned tumor slides in order to detect features invisible to the human eye and predictive of specific molecular profiles . In radiEGFR . The devIn conclusion, molecular oncology and precision medicine have made a huge leap in the last few years, resulting in significant survival advantages in different malignancies, and particularly in NSCLC. However, in spite of the impressive achievements, there is still huge room for improvement. The continuous study of emerging molecular alterations and the development of novel treatments capable of exploiting oncogenic drivers remain major objective in thoracic oncology.


Thermal annealing has been proven to be an efficient method to optimize the device performance of organic and polymeric opto-electronic materials. However, no detailed information of aggregate structures was obtained for a deeper understanding of what happens during thermal annealing. Herein, through modulation of molecular configurations by tunable linkage positions, and the amplified amplitudes of molecular motions by incorporation of additional methylene units, accurate changes of aggregated structures upon thermal annealing have been achieved, accompanying with the ‘turn-on’ room temperature phosphorescence (RTP) response by about 4800- and 177-fold increase of lifetimes. The stretching and swing motion models have been proposed, which afforded an efficient way to investigate the science of dynamic aggregation in depth. Accurate changes of aggregated structures and motion models of organic luminogens during thermal annealing have been revealed by crystal engineering, accompanying with `turn-on' RTP response. Since t(∼1.1 Å) ,38, a re(∼1.1 Å) . The repout Fig. . Also, tout Fig. , respecto-CH2-DAc at aggregated states. Moreover, the promoted RTP property with the facilitated ISC process can be confirmed by theoretical calculation. Generally, the possible ISC channels are mainly determined by the small energy gaps (<0.3 eV), and the large spin-orbit coupling constants (SOC) between Tm and S1. The number of ISC processes increased from 6  to 16 (solidified state), and the spin-orbit coupling (SOC) constant of the major ISC channel ζ  enhanced from 0.15 cm−1  to 1.04 cm−1 (solidified state)  between S1 and T18 as the lowest one slightly increased from 0.23 eV  to 0.27 eV (solidified state), the positive effect from the increased channels and improved SOC values played the dominant role in facilitating the ISC process  Fig. . Althoug process .m-CH2-DAc crystals by thermal annealing can also be explained by XRD patterns and crystal structures under different conditions. As shown in Fig. m-CH2-DAc at the crystal state, the two acridine moieties were nearly perpendicular to the phenyl core, and parallel to each other with a large overlap (87.12%). Combined with their close distance (4.010 Å), the van der Waals forces between two acridine moieties can be formed  to 20.65° and 22.72° (solidified state), respectively. Also, the overlap of acridine moieties increased from 87.12% to 88.14%, accompanying with the decreased distance between the centroid of two acridine moieties from 4.130 Å to 4.104 Å . Accordixis Fig. . It was 1 to T18 with the lowest energy gaps, the corresponding SOC constant ζ  increased from 0.02 cm−1 to 0.76 cm−1 with slightly decreased energy gaps  moieties with phenothiazine 5,5-dioxide (OCs) units. Accordingly, the molecules 2-OCs, p-CH2-DOCs, m-CH2-DOCsB-CH and o-CH2-DOCs have been synthesized  and well characterized by 1H NMR spectra and HPLC  and 98.61° (solidified state), respectively. This indicated much larger changes of m-CH2-DAc in aggregated structures during thermal annealing  to 117.81° (solidified state) for ing Fig.  40,41],,41,m-CH2m-CH2-DAc with ‘U’ shape, the molecular packing is loose for the twisted conformation, and the corresponding intermolecular interactions were relatively weak , or the increased lengths of alkyl chains (m-3CH2-DAc)  Special intramolecular interactions should be constructed into the molecular design of organic luminogens, in order to make the directional molecular motions with ordered changes in aggregated structures. Apart from the construction of repulsive or attractive force by the adjustment of molecular configurations, some self-assemble process may be employed as the driving force. Thus, the crystalline states can be maintained in most cases, facilitating to the formation of optimized molecular packing for the RTP property. (2) The loose molecular packing can afford more space for the thermal motions of organic luminogens with large amplitudes to proceed, which can promote the variations of RTP property for the large changes in aggregated structures. Through the formation of preferred packing modes, the improved RTP property can be achieved by thermal-annealing processes.m-CH2-DAc demonstrated good repeatability. The RTP property can still be maintained after five cycles of thermal annealing processes , and coated on the surface of a light-emitting diode (LED) , which would form a uniform film after cooling. When voltage (3 V) was applied, the coated LED displayed blue-violet fluorescence. Once the voltage was removed, the bright green afterglow would appear, which can last for up to 3 s. It not only realized the flexible packaging of LEDs, but also the multi-color emission under different conditions.Finally, the thermal annealing promoted RTP property of rocesses . Thus, cing Fig. . Accordio-CH2-DAc and m-CH2-DAc crystals, respectively. The stretching mode is mainly due to the repulsive force of methylene moieties, and the swing is dominated by acridine-acridine interactions. These molecular motions can be beneficial in forming the compact molecular packing, and strengthen the intermolecular interactions, that result in the promoted ISC process and stabilization of excited triplet states. Thus, RTP lifetimes can be largely increased by about 4800- and 177-fold for o-CH2-DAc and m-CH2-DAc, respectively. The ‘turn-on’ response upon thermal annealing can be incorporated into the coating technology to achieve multicolor displaying. The visualization of molecular thermal motions with accurate aggregated structures afforded an efficient way to investigate, in depth, the science of dynamic molecular aggregation under external force.In summary, the detailed motion models of organic luminogens upon thermal annealing have been captured by crystal engineering, contributing to the understanding of the internal mechanism for thermal modulation. Moreover, it can be well-controlled by the initial molecular conformations, resulting in the stretching and swing modes in n) and n-th triplet (Tn) monomer states were obtained using the PBE1PBE/def2svp based on the structure extracted from a single crystal. The trajectory of molecules were simulated in Gaussian View 6.0 [2λ)ρ was conducted with gnuplot software.The time-dependent density functional theory (TD-DFT) calculations were performed on Gaussian 09 program (Revision D.01) . The excView 6.0 . Spin-orView 6.0 . Non-covView 6.0  to facilnwad239_Supplemental_FileClick here for additional data file.additional_CIF-DATA_and_CIF-dataClick here for additional data file.nwad239_Video_S1-optimized_thermal_annealing_processClick here for additional data file.nwad239_Video_S2-Trajectory_of_molecule_o-CH2-DAcClick here for additional data file.nwad239_Video_S3-Trajectory_of_molecule_m-CH2-DAcClick here for additional data file.nwad239_Video_S4-Repeatability_experimentsClick here for additional data file.


PLoS Medicine dedicated to AMR. These research studies affirm the complexity and multi-faceted dynamics of AMR and the enormous challenge faced in understanding the problem and in designing tractable, equitable and cost-effective interventions to control its spread.Antimicrobial resistance (AMR) has been prioritized by the World Health Organization (WHO) as one of the top 10 global public health threats facing humanity . DespiteThe drivers of AMR are multifactorial but there is no debate that antibiotic overuse has been paramount. Between 2000 and 2015 antibiotic use increased by 65% globally, primarily driven by a substantial increase across LMICs [Klebsiella pneumoniae as the most common causative pathogen for neonatal sepsis, associated with mortality rates of 10–12% and higher when blood cultures were positive [K. pneumoniae (CRKP) has spread to all parts of the world and is a leading cause of drug-resistant infections in neonates and children in LMICs [The Special Issue attracted several studies focused on neonatal and pediatric infections. Neonates and infants are particularly vulnerable to antibiotic resistant infections. In a global prospective study of neonatal sepsis (NeoOBS), which included 11 countries spanning 4 continents, Neal Russell and colleagues identified positive . In the positive . These dpositive . Carbapein LMICs . In a syin LMICs . Among tin LMICs . The pooin LMICs .Of course, inappropriate prescribing of antibiotics is not restricted to hospital settings, nor to LMICs. Using data from a prospective, community-based mother-and-child cohort study (the BIRDY cohort) conducted across urban and rural sites in Cambodia, Madagascar, and Senegal between 2012 and 2018, Antoine Ardillon et al. report extensive, inappropriate antibiotic prescribing among pediatric outpatients . The autIn a systematic review of 109 studies reporting bloodstream infections in hospitalized patients from LMICs, several WHO critical and high priority pathogens were associated with increased mortality, length of hospital stay and admission to intensive care units (ICU), and cost . Wide heStaphylococcus aureus (MRSA). Shortening treatment duration is a common strategy applied by antibiotic stewardship programs in the expectation of reducing the prevalence of antimicrobial resistant bacteria over time. To gain a better understanding of the relationship between treatment duration and prevalence of colonization with antimicrobial resistant bacteria in hospitalized patients, Yin Mo and co-workers applied a model to assess how changing duration of antibiotic treatment would affect the risk of resistance colonization at both individual and population levels [In high-income settings, prolonged antibiotic overuse and misuse has driven the development of ‘super-bugs’ that are recognizable to many, such as methicillin-resistant n levels . The autn levels . Healthcn levels . Conversn levels , suggestK. pneumoniae, have been called for by WHO [K. pneumoniae maternal vaccine on neonatal sepsis infections and mortality, and estimated that maternal vaccination could avert 80,258 neonatal deaths and 399,015 cases of neonatal sepsis annually worldwide, accounting for more than 3.40% of all neonatal deaths [Whilst AMR cannot be neutralized by a single vaccination program, immunization has been well documented to be effective at preventing the spread of infectious diseases, and vaccines targeting resistant microbial species, especially r by WHO . A modell deaths . The larl deaths . Of critIn September 2024, a high-level meeting of the United Nations will be held to discuss AMR and to propose an enhanced framework to that outlined in 2016. Recognition of the magnitude of this problem is urgently required by world leaders and policy makers to ensure adequate global investment in the development of innovative affordable vaccines, antimicrobial agents, diagnostics, and reporting systems. The COVID-19 pandemic has taught us, as a global community, that the planet is small and we are all inter-connected economically, culturally, and socially with the ultimate consequence of what happens in one country soon appearing in another. It is estimated that the attributable deaths due to COVID-19 since December 2019 numbered 3.2 million and its cost to the global economy is approximately $17 trillion. On the current trajectory, by 2050, not only will AMR perhaps be responsible for 10 million deaths annually it will also cost the global economy over $100 trillion—figures that dwarf the impact of COVID-19 and emphasize the urgent threat of AMR.


Due to the excellent biocompatible physicochemical performance, luminogens with aggregation-induced emission (AIEgens) characteristics have played a significant role in biomedical fluorescence imaging recently. However, screening AIEgens for special applications takes a lot of time and efforts by using conventional chemical synthesis route. Fortunately, artificial intelligence techniques that could predict the properties of AIEgen molecules would be helpful and valuable for novel AIEgens design and synthesis. In this work, we applied machine learning (ML) techniques to screen AIEgens with expected excitation and emission wavelength for biomedical deep fluorescence imaging. First, a database of various AIEgens collected from the literature was established. Then, by extracting key features using molecular descriptors and training various state-of-the-art ML models, a multi-modal molecular descriptors strategy has been proposed to extract the structure-property relationships of AIEgens and predict molecular absorption and emission wavelength peaks. Compared to the first principles calculations, the proposed strategy provided greater accuracy at a lower computational cost. Finally, three newly predicted AIEgens with desired absorption and emission wavelength peaks were synthesized successfully and applied for cellular fluorescence imaging and deep penetration imaging. All the results were consistent successfully with our expectations, which demonstrated the above ML has a great potential for screening AIEgens with suitable wavelengths, which could boost the design and development of novel organic fluorescent materials.The online version contains supplementary material available at 10.1186/s12951-023-01864-9. Fluorescent probes, especially organic luminogens, were indispensable agents that were widely used in biological research owing to their lower safety risks and biodegradability–3. Howevabs, λem). Thus, it is important to have a profound understanding of structure-property relationships between molecular structures and optical properties before chemical synthesis. The challenge is arose from the complex AIE mechanisms based on various dimensions of photophysics, such as restriction of intramolecular rotation or vibrationindole, 2-(4-nitrophenyl)acetonitrile, iodoethane and solvents were all purchased from Sigma Aldrich and used as received without further purification. Chloroform and ethanol was obtained from Macklin reagent. 2-Distearoyl-sn-glycero-3-phosphoethanolamine-N-indol-3-ium iodide was synthesized according to the literature method+; Retention time = 0.881 min.In a 50 mL round-bottomed flask, added ammonium acetate , 2(dppf)  and K2CO3  for 24 h. The combined organic phase was filtered and dried to obtain the crude product, which was further purified by silica-gel chromatography (PE/DCM = 2:1) to obain the yellow solid . 1 H NMR  δ 9.88 , 7.73 , 7.57–7.52 , 7.35–7.29 , 7.19–7.14 , 7.14–7.06 .A solution of 4-bromo-N,N-diphenylaniline  and (5-formylthiophen-2-yl)boronic acid  was refluxed under nitrogen in the mixed toluene/MeOH (20 mL: 20 mL) in the presences of PdCl1 H NMR  δ 8.32–8.26 , 7.85–7.75 , 7.65 , 7.57–7.52 , 7.34–7.26 , 7.17–7.11 , 7.11–7.03 . 13 C NMR  δ 151.92, 149.07, 147.42, 147.12, 140.66, 137.34, 136.64, 135.48, 129.62, 127.28, 126.28, 126.10, 125.27, 124.55, 123.99, 122.99, 122.61, 117.84, 103.97. MALDI-TOF (ESI): m/z calcd for C31H21N3O2S [M]+,499.1354; found, 499.1354.A solution of 5-(4-(diphenylamino)phenyl)thiophene-2-carbaldehyde  and 2-(4-nitrophenyl)acetonitrile  were added to ethanol (20 mL) with a drop of piperidine and refluxed for 5 h. It was then cooled down to room temperature and produced a black product, which was then filtered, washed three times with cold ethanol, and dried in a vacuum . TTBI+; Retention time = 0.979 min.The synthetic procedure for the preparation of TTBI. A solut2000 (5 mg) into 5ml of ultrapure water and stirring vigorously for 2 min. The prepared NPs were purified for a day using ultrapure water dialysis (molecular weight cutoff of 100 kDa). After that, NPs were ultrafiltered for 20 min at 4400 rpm through ultrafiltration tubes with a molecular weight cutoff of 100 kDa. After ultrafiltration, the NPs were dispersed in 1°x PBS buffer (pH 7.4) and kept out of the light at 4 °C.Fabrication of NPs was carried out by injecting THF solution (0.5ml) of AIEgens (1 mg) and DSPE-PEG2 atmosphere. After incubating HeLa cells with NPs (20 µg/mL) in glass bottom dishes for 4 h, 200 nM Lyso-Tracker was added, incubated for 30 min. After that, the dishes were washed with PBS 3 times and visualized by Confocal laser scanning microscopy (CLSM) immediately.HeLa cells were cultured in a DMEM medium that contained 10% FPS at 37 °C in a 5% COhttp://www.rdkit.org).Molecule descriptors were a crucial step in molecular machine learning to encode molecules and extract structural information. Quantitative structure-activity relationship (QSAR) was a crucial tool in chemometrics. It used mathematical-statistical methods to explain the relationship between a compound’s activity or physicochemical characteristics and its molecular structure. The foundation of QSAR studies was the calculation of molecular descriptors, and the precise definition and logical application of these descriptors were crucial to QSAR studies. The ability to obtain QSAR models with high confidence and validity depended mainly on the correct choice of descriptors. A molecular descriptor measured a molecule’s characteristics in a specific area, such as a physicochemical property or a numerical index derived from the molecule’s structure by different algorithms. More than 5000 molecular descriptors were currently accessible in a variety of software. RDKit was used to produce molecular descriptors as numerical descriptors for prediction experiments. There were two types of molecular descriptors: quantitative and qualitative. Quantitative descriptions were based on molecular graph theory, various theoretical or experimental spectral data , molecular composition , physicochemical properties  descriptors, molecular field descriptors, and molecular shape descriptors. Qualitative descriptors were generally referred to as molecular fingerprints. That is, some code represents a molecule’s structure, properties, fragments, or substructures. All molecular descriptors were generated by RDKit it into many bit strings  that were then easily compared between molecules. A typical procedure extracted a molecule’s structural characteristics before hashing them to create the bit vector. Comparing molecules was hard, comparing bit vectors was easy, and comparisons between molecules must be quantifiable. Each bit on a molecular fingerprint corresponded to a molecule fragment. Molecular fingerprints were classified into several types based on the method used to convert the molecular representation into bit vectors. Common molecular fingerprinting methods include the morgan circular fingerprint, daylight fingerprint, topological torsion fingerprint, and atom-pair fingerprint.Extended connectivity fingerprint (ECFP) was a circular topological fingerprints designed for molecular characterization, similarity search, and structure-activity modeling. Morgan connectivity fingerprint (MCP) were part of ECFP, derived from Morgan’s algorithm, and have became the industry standard method for circular molecular fingerprints, designed explicitly for constructive relationship studies. They were often used in ML as a benchmark for comparing the performance of new strategies. When used, MCP first sets a defined diameter – different diameters produced different fingerprints – then employed the Morgan search algorithm to look for all substructures in the molecule with that diameter. Finally, it hashed to obtain each substructure’s hash value, forming the corresponding fingerprint. ECFPs with small diameters were typically appropriate for similarity searches and molecular clustering. Contrarily, ECFPs with large diameters gained from having more molecular structure information and were thus perfect for ML to make activity predictions.Topological or path-based fingerprint started from an atom and took each substructure along the path until it reached a specified length, then hashed each substructure to obtain a molecular fingerprint. This fingerprint could be adjusted for quick substructure searching and molecular filtering and applied to any molecule. The most well-known examples of this type of fingerprint were daylight fingerprint, which had bits that could be up to 2048 bits long and encode every possible linkage pathway that a molecule could take to reach a specific length. Atom-pair fingerprint identified each molecule atom as the shortest path based on its environment. Topological torsion fingerprints were generated by constructing a topological double-angle descriptor using four non-hydrogen atom-pair bonding paths. Both fingerprints could be expressed in sparse form.RF was a general-purpose ensemble learning algorithm that used the Classification and Regression Tree (CART) algorithm to reach the final conclusion after “aggregating” the results of a single fully grown regression tree constructed on a randomly chosen subset of data. Each regression tree selected a variable to reduce the Gini impurity as it grows to lessen the chance that a new random variable would be incorrectly classified. In this case, J was the total number of classes, and pi was the likelihood that a given item belongs to class i. For the overall algorithm to be more predictive than a single regression tree and more resilient on a noisy database, RF uses bootstrap sampling and random selection of input samples to ensure that each regression tree in the forest was distinct and uncorrelated to one another. The algorithm’s accuracy would increase with a large number of regression trees.The GBRT was a well-liked model that performed exceptionally well in ML applications. It was a boosting family representative algorithm. Boosting was a progressive model combination strategy. Each new regressor enhanced the predictions of the previous regressor. Thus, boosting was a technique for combining models that reduced bias. GBRT was an iterative regression tree algorithm that consisted of multiple trees. The integration technique used was gradient boosting, and the final result was the sum of the conclusions from each tree. The intuitive understanding was that each round of prediction has residuals with the actual values, the next round of prediction was made based on the residuals, and the result was obtained by summing all predictions. The GBRT process involved several iterations, with each iteration producing a weak regressor that was trained using the residuals of the previous regressor. Since the training process was made to reduce residuals, the accuracy of the final regressor was continually improved. Generally, the requirements for weak regressors were straightforward, with low variance and high bias. Classification and Regression Tree (CART) was usually chosen with weak regressors. The depth of each CART was limited due to the high bias and simplicity requirements. The final total regressor was a weighted average of the weak regressors from each training round. GBRT could be expressed as follows when a regression tree represents the basic model:where where the loss function L was used, the mean square error and the absolute value error were typically the loss functions chosen by the regression algorithm.KNN was one of the most basic regression algorithms. When the k-nearest samples of a data point were considered, the value of that data point was the average of those k values. The number of neighbors k and the calculation of distance were two crucial factors influencing KNN. K was usually an integer no larger than 20, and distance was calculated using the Euclidean distance. Euclidean distance was defined asWhere n was the number of samples.The Vapnik-Chervonenkis theory was the basis for the development of SVM, also known as “support vector network,“ which was a kernel-based supervised learning algorithm. For regression issues, the SVM calculated a hyperplane and fit training data to the hyperplane using a kernel function to project input data onto a higher dimensional space. The kernel function for this work was linear.The XGBoost algorithm was an upgraded library of the GBRT algorithm, which significantly increased data processing effectiveness and lowered the risk of overfitting. Because it employed a sparse-aware algorithm for sparse data and trained the weighting function using first- and second-order derivatives, it was more scalable than GBRT. Similar to GBRT, XGBoost also employed a forward stepwise algorithm, and XGBoost chose the parameters for the following decision tree by minimizing structural risk.where MLP was a forward-structured artificial neural network that mapped a set of input vectors to a set of output vectors. The backpropagation algorithm, a supervised learning technique, was frequently used to train MLPs, which mimicked the human nervous system’s learning and data prediction processes. It first learned, then stored the data with weights and employed algorithms to modify the weights and lessen bias in the training process or the difference between the actual and predicted values. The input, hidden, and output layers were the three types of network layers that made up an MLP. Each layer was made up of a specific number of nodes, which were neurons with non-linear activation functions. Each layer was fully connected to the one before it. The input layer was used to receive data, the hidden layer was used to process the data, and the output layer offered the final prediction. A single network layer’s output was depicted aswhere x represented the input to the node, w represented the node’s weight, b represented the bias, and f(x) represented the activation function. If each neuron’s activation function was linear, an MLP with multiple layers could be compared to a single-layer neural network. Rectified linear unit (ReLU) was a non-linear activation function used in this work.The convolutional neural network was a feed-forward neural network with artificial neurons that responded to a portion of the surrounding units in the coverage area. CNN comprised three layers: the input layer, the hidden layer, and the output layer, with the hidden layer containing various types of networks such as convolutional, pooling, fully connected , and normalization layers. The convolutional layer was the core of the CNN and performed the dot product of the convolutional kernel and the layer input matrix, this product was usually the Frobenius inner product, and the activation function was ReLU. The convolution operation produced a feature map as the convolutional kernel moved along the layer’s input matrix. This feature map then became part of the input for the subsequent layer. CNN was a desirable deep learning structure because it required fewer parameters to be considered than other deep neural networks.MAE (mean absolute error) of these n samples was given byRMSE (root mean squared error) of these n samples was given byCoefficient of determination (R2) of these n samples was given byWe employed Bayesian optimization to identify each model’s ideal hyperparameters during model training. This stThe data were randomly divided into ten equally sized mutually exclusive subsets, each keeping the data distribution as consistent as possible. Nine subsets were taken at a time for the training set and one for the test set. This yielded ten training and test sets, and the final result was the mean of the outcomes of the ten tests.Below is the link to the electronic supplementary material.Scheme S1. The synthetic route to prepare PTMM, TTNA, and TTBI.1 H NMR spectrum of PM.Figure S1 1 H NMR spectrum of PTMM.Figure S2 13 C NMR spectrum of PTMM.Figure S3 Figure S4. LC-MS spectrum of PTMM.1 H NMR spectrum of TTA.Figure S5 1 H NMR spectrum of TTNA.Figure S6 13 C NMR spectrum of TTNA.Figure S7 Figure S8. MALDI-TOF-MS spectrum of TTNA.1 H NMR spectrum of TTBI.Figure S9 13 C NMR spectrum of TTBI.Figure S10. Figure S11. LC-MS spectrum of TTBI.Figure S12. The absorption spectrum of AIEgens in different solvents.Figure S13. PL spectra of AIEgens of AIEgens with different water fractions.Table S1. Comparison of absorption and emission peak between experimental and ML predicted.Table S2. Particle size of AIEgens NPs.Table S3. Zeta potentials of AIEgens NPs.Figure S14. Calculated LUMO and HOMO of PTMM, TTNA, and TTBI.Figure S15. Z-stack images of phantom of PTMM NPs.Figure S16. Z-stack images of phantom of TTNA NPs.Figure S17. Z-stack images of phantom of TTBI NPs.Figure S18. Experimental and predicted data are compared using 10-fold cross-validation.Figure S19. ML prediction error distribution.Figure S20. Model scalability.Figure S21. Comparison of ML accuracy and TD-DFT.Figure S22. Illustration of 10-fold cross-validation.


Nature serves as a rich source of molecules with immense chemical diversity. Aptly named, these ‘natural products’ boast a wide variety of environmental, medicinal and industrial applications. Type II polyketides, in particular, confer substantial medicinal benefits, including antibacterial, antifungal, anticancer and anti-inflammatory properties. These molecules are produced by enzyme assemblies known as type II polyketide synthases (PKSs), which use domains such as the ketosynthase chain-length factor and acyl carrier protein to produce polyketides with varying lengths, cyclization patterns and oxidation states. In this work, we use a novel bioinformatic workflow to identify biosynthetic gene clusters (BGCs) that code for the core type II PKS enzymes. This method does not rely on annotation and thus was able to unearth previously ‘hidden’ type II PKS BGCs. This work led us to identify over 6000 putative type II PKS BGCs spanning a diverse set of microbial phyla, nearly double those found in most recent studies. Notably, many of these newly identified BGCs were found in non-actinobacteria, which are relatively underexplored as sources of type II polyketides. Results from this work lay an important foundation for future bioprospecting and engineering efforts that will enable sustainable access to diverse and structurally complex molecules with medicinally relevant properties. All sequence data were obtained from the precompiled National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST) databases. The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.in vitro.Nature – plants, bacteria, fungi and even animals – has the unique ability to produce molecules with a diverse range of structures and functions. Since many of these molecules have been successfully repurposed by humans in medical, environmental and industrial settings, developing strategies to identify the organisms and biosynthetic systems that manufacture natural products could help to find novel molecules of interest. Type II polyketides have unique antimicrobial and anticancer properties, so identifying new sources of these molecules may offer renewed access to promising pharmaceuticals. By conducting a global phylogenetic analysis of the chain-length factor (CLF) protein involved in type II polyketide biosynthesis, our work provides access to previously unexplored gene clusters that may harbour unique biodiversity. Our curated CLF set nearly doubled the number of sequences available to study, increasing both the volume and the diversity of potential polyketide synthases we can access Microbes have evolved the ability to manufacture a diverse profile of secondary metabolites that confer the host with a selective advantage over other organisms in the nearby environment . Humans Ktenobacter racemifer, Photorhabdus luminescens TT01, Streptoccocus sp. GMD2S and Pseudoalteromonas luteoviolacea, revealing the possibility of innovation in this biosynthetic space [Microbial enzyme assemblies like these are encoded by biosynthetic gene clusters (BGCs), which are physically grouped genes that programme the production of a metabolite . Previouic space . While aic space , a 2022 ic space . Analysiic space , furtheric space . Ancestric space .With the ongoing growth of available genetic data , routineblast databases [We built our nucleotide databases from the following precompiled NCBI atabases  and locaenv_nt ,nt ,patnt ,tsa_nt ,ref_prok_rep_genomes Therefore, our nucleotide databases consisted of complete genomes, contigs from draft genomes, contigs from environmental sequencing, transcriptome sequences and miscellaneous short nucleotide sequences.blast (tblastn) from the NCBI BLAST+ Suite v.2.11.0 for sequence homology to a set of known KS and CLF protein query sequences [These nucleotide databases were searched using translated nucleotide equences . We seleequences . Signifiblast hit for the longest ORF that contains the blast hit. We considered a set of six possible start codons . An ORF was defined as the first of these start codons after a stop codon (or the edge of a given DNA sequence) and continuing until reaching an in-frame stop codon (or the edge of a given DNA sequence). By considering alternative start codons that are not ATG, our ORFs were perhaps longer on the 5′ end of the gene compared to the true start codon; however, our method makes the fewest assumptions when calling ORFs. We required that ORFs were at least 300 nt long and cover at least 50 % of the blast hit with an identical translated sequence, although the vast majority of hits matched 100 % of the blast hit. All custom Python scripts can be found at https://github.com/EricLMiller/KS_CLF_Search.We designed a custom Python script to search between 500 nt before and after a et al. to best distinguish a given type II PKS protein from other protein families (e.g. fatty acid synthases or type I PKSs) or proteins within the same cluster (i.e. a type II KS vs. CLF) [Profile hidden Markov models (pHMMs) run on HMMER v. 3.3.2 were used to differentiate which KS and CLF ORFs belonged to type II PKS BGCs . Predictvs. CLF) . Sequencvs. CLF) . Translaet al. [Using the information from the ORF-Finder on sequences that scored high in our pHMM, we wrote a custom Python script to find KS/CLF ORF pairs from the same nucleotide accession number. This script also removed pairs with over 2 kb distance between the genes to ensure that the KS and CLF function as a heterodimer and can be coexpressed, as noted by Hillenmeyer et al. . KS/CLF Escherichia coli FabF sequence WP_000044679.1 as an outgroup to root the tree.All multiple sequence alignments were produced using MAFFT Galaxy Version 7.475+galaxy0 . Alignmeblastp e-value cutoff of 1×10−8 and minimum alignment length of 200 aa. We examined genomic regions 30 kb before and after each KS–CLF pair; multiple pairs within this range in single genomes were combined together. We ran antiSMASH v6.1.1 [et al. and Chen et al. [We utilized the Natural Product Domain Seeker version 2 (NaPDoS2), a phylogeny-based classification webtool, to predict KS and condensation domains, thus classifying our CLF hits . A FASTAH v6.1.1  using a H v6.1.1  as a genn et al. .Using our pipeline , we idenet al. [blast-based search and retained based on our pHMM score but did not have a corresponding KS within 2000 bp and was thus removed during the proximity pairing stage. Since we found nearly all of the previously reported characterized type II PKS CLFs, and all the CLFs we would expect to find given our workflow, we are confident that our pipeline can accurately identify a broad range of CLF diversity.We validated this pipeline by comparing the set of 167 characterized type II PKS CLFs reported by Chen et al.  with ourAcidithiobacilla, Acidobacteria, Actinobacteria, Proteobacteria , Armatimonadetes, Candidatus Aminicenantes, Candidatus Cryosericota, Candidatus Omnitrophica, Chloroflexi, Cyanobacteria, Euryarchaeota, Firmicutes, Nitrospirae and Planctomycetes . In total, 158 of our CLF sequences were not classified.To assess the significance of our data, we plotted the pHMM score for each CLF ORF onto the phylogeny, observing lower pHMM scores (corresponding to a weaker match to the selected model) for non-actinobacterial PKSs. The pHMM scores for actinobacterial hits had a median of 801.80 , while the pHMM scores for non-actinobacterial hits were much lower with a median of 132.25 . Since the pHMM score of the aurachin CLF was 66, these clusters score better against the model than the most distant type II BGC included in our tree, suggesting that these lower scores do not necessarily indicate that they are not true type II CLFs. As a result, to further verify the soundness of our CLF set, we used NaPDoS2 to detect and classify KS and CLF domains from our dataset. Ultimately, the NaPDoS2 algorithm identified 5497 type II CLF domains, 181 type II KS domains, 464 type II FAS domains, and 22 KS or condensation domains from other synthases , opening up routes for new type II polyketide biosynthetic diversity outside of the traditional actinobacterial space. Notably, we identified a primarily non-actinobacterial clade that has not been previously identified in the literature. Past bioinformatic searches have utilized a variety of criteria  with varying stringency, so it is unsurprising that these different methods produce different sequence sets. Our model may be less stringent than recent searches, leading to a broader selection of CLFs that could represent more distantly evolved, biosynthetically unique BGCs.Our bioinformatic pipeline identified 6322 individual CLF hits, nearly double those found by Chen  in 2015 , confirmMethanobacteria and Methanomicrobia but no type I PKS BGCs were found in archaea, suggesting that these small-molecule-producing clusters are elusive and rare [Euryarchaeota, all members of the Candidatus Methanoperedenaceae archaeon species. While NaPDoS2 classified one of these CLF hits as belonging to a type II FAS cluster, the other two hits were classified as type II PKS KS proteins, posing the question as to whether archaea may actually be capable of producing polyketide-like products.It is important to highlight the archaeal KS–CLF hits identified by our pipeline. Previously, modern archaea and their last common ancestor have been shown to contain FAS pathways, but these archaeal systems lack an ACP . More reand rare . Our pipMelittangeum boletus DSM 14713 was the only non-actinobacterial CLF found within a large, otherwise actinobacterial clade. Our results are consistent with a single large horizontal gene transfer (HGT) event, as suggested by Chen et al. [Mirroring the results of recent phylogenetic analyses , the deln et al. .As a result of their relative evolutionary separation, there are distinct differences between the various phyla represented in our tree. On average, the actinobacterial CLFs scored substantially higher in our pHMM model than the non-actinobacterial CLFs. To some extent, this discrepancy indicates that the non-actinobacterial CLFs are less similar to known, characterized CLF proteins. However, since all of the CLF proteins used to build the model were from actinobacteria, this lower score may actually reflect the current bias in the field toward actinobacterial type II PKSs.ks gene that was duplicated to form the type II PKS KS and CLF genes originated prior to the most recent common ancestor of the actinobacteria and of E. coli, whose FAS is used as an outgroup for these genes [To further verify our CLF hits, we ran all 6322 CLF sequences through NaPDoS2, a phylogeny-powered webtool that classifies various KS and condensation domains . Approxise genes .E. coli FAS KS were less likely to be classified as type II PKS CLFs by NaPDoS2, this does not mean that these hits are extraneous sequences accidentally retained by our pipeline as a previously unexplored clade. Many of these CLF hits were classified as either type II FAS or type II KS domains by NaPDoS2; since our workflow mandated the presence of a KS and CLF gene within 2000 bp of each other to retain them as a KS–CLF pair, each of these hits must have another KS-like domain within these bounds. Therefore, these seemingly extraneous hits could represent BGCs that evolved directly after the ancient FAS ks gene duplication and thus have two near-identical KS domains that lack the typical motifs seen across most actinobacterial CLFs. Despite their relative infrequency, there were CLF hits within this previously unexplored clade that were classified as type II CLF genes, indicating that our workflow is capturing distant CLF genes that may harbour unique sequence and biosynthetic diversity.While the CLF proteins with closer homology to the Our antiSMASH analysis of the regions surrounding our hits further supports this inference. While 15.9 % of our non-actinobacterial hits had the traditional type II KS – type II CLF pairing, 17.2 % of these examined regions contained type II KS – type II FAS pairs and 58.4 % of these regions contained type II FAS – type II FAS pairs. Differences between the percentage of actinobacteria and non-actinobacteria pairs classified as type II KS/type II CLF are hard to interpret due to the actinobacteria sequenced at a much high phylogenetic density compared to the non-actinobacteria; genomes are often not randomly selected to be sequenced, and so the resulting collection of genomic information in NCBI can be biased accordingly. The type II KS – type II FAS pairing represents a relatively unexplored region of BGC diversity. Hits of this type contain two condensation domains: one is homologous to known type II KSs, while the other is most similar to known type II FAS KS domains. This pairing may indicate that hybrid type II PKS/type II FAS systems exist, and that our definition of what constitutes a ‘CLF’ may need to be broadened, such that type II CLFs may actually look much more similar to type II FAS KSs than we previously understood. We also note several non-canonical clusterings of three condensation domains, such as type II KS/type II FAS/type II CLF or type II KS/type II CLF/type II CLF triads. Further characterizing atypical BGC types may reveal biosynthetic diversity beyond our current understanding of type II PKS and type II FAS systems. While the type II FAS – type II FAS pairs may just represent regions where the FAS KS gene duplicated and thus still belong to a traditional type II FAS system, these clusters still represent an area of biosynthetic diversity that should be explored. Delineating the differences between these pairs of condensation enzymes may provide further insight into what constitutes a type II PKS vs. a type II FAS and how we might manipulate these systems to allow them to combinatorially interact.Our bioinformatic pipeline, developed using the computational resources made available through a primarily undergraduate institution, can be easily understood and manipulated by researchers with limited computational experience. While initially designed to identify type II PKS KS–CLF pairs, our pipeline is not unique to type II PKS systems; rather, each step can be tailored to incorporate the parameters needed to produce a phylogeny of any evolutionarily conserved gene or protein, such as by changing the reference set used for comparison in the pHMM or changing the conditions for gene length or proximity. Since our pipeline does not rely on previous annotation, users can systematically identify homologues of their sequence of interest from sequence data of varying completeness or accuracy.E. coli KS prior to the formation of the actinobacterial clade.Unveiling new routes to type II polyketide-like molecules could offer swift access to promising bioactivity. Using the bioinformatic pipeline described herein, we report an updated profile of CLF diversity – a critical and unique protein to type II PKSs – across 14 distinct microbial phyla. Along with unveiling a previously undescribed, primarily non-actinobacterial clade, we share potential evidence of type II polyketide biosynthetic potential in archaea. We further provide additional support for the inference that the type II KS and CLF genes diverged from a common ancestor of the The curated CLF set itself serves as a ‘biosynthetic catalogue’, offering insight into potential leads for type II PKS bioprospecting efforts. Exploring the previously undescribed non-actinobacterial clade may unveil new type II PKS enzymatic and molecular diversity, guiding future efforts in the biosynthesis of never-before-seen secondary metabolites. Further understanding the existence of this clade may allow us to dissect the differences between type II FAS and PKS KS-like domains, gaining insight into the divergent evolution of these systems. We share these results with the community with the hope that they will spark efforts to characterize these diverse BGCs and encoded enzymes. Uncovering the biosynthetic prowess of these systems represents a critical step in gaining sustainable access to important molecules.Click here for additional data file.Click here for additional data file.


Antimicrobial resistance is an increasing challenge in low and middle-income countries as it is widespread in these countries and is linked to an increased mortality. Apart from human and environmental factors, animal-related drivers of antimicrobial resistance in low- and middle-income countries have special features that differ from high-income countries. The aim of this narrative review is to address the zoonotic sources and the spread of antimicrobial resistance from the perspective of low- and middle-income countries.Escherichiacoli is highest in poultry  and there is a risk to import ESBL-producing E.coli through poultry meat in Africa. In aquacultures, the proportion of ESBL-producers among E.coli can be high (27%) but the overall low quality of published studies limit the general conclusion on the impact of aquacultures on human health. ESBL-producing E.coli colonization of wildlife is 1–9% in bats or 2.5–63% birds. Since most of them are migratory animals, they can disperse antimicrobial resistant bacteria over large distances. So-called ‘filth flies’ are a relevant vector not only of enteric pathogens but also of antimicrobial resistant bacteria in settings where sanitary systems are poor. In Africa, up to 72.5% of ‘filth flies’ are colonized with ESBL-producing E.coli, mostly conferred by CTX-M (24.4–100%). While methicillin-resistant Staphylococcus aureus plays a minor role in livestock in Africa, it is frequently found in South America in poultry (27%) or pork (37.5–56.5%) but less common in Asia .Contamination with extended-spectrum beta-lactamase (ESBL)-producing Interventions to contain the spread of AMR should be tailored to the needs of low- and middle-income countries. These comprise capacity building of diagnostic facilities, surveillance, infection prevention and control in small-scale farming. The increase in antimicrobial resistance (AMR) poses a considerable threat to health and livelihoods. An estimated 4.95 million deaths associated with AMR occurred in 2019 . AMR is,Escherichiacoli and methicillin-resistant Staphylococcusaureus (MRSA) in LMIC (excluding China) and the most important pathogens associated with aquaculture as these are of critical importance for understanding AMR particularly in the community setting in LMIC. China was largely excluded as this topic has recently been reviewed elsewhere . In . In 7]. According to the World Organization for Animal Health (WOAH) report, 69,455 tonnes of antimicrobial agents were used in animals in 2018 . The higmcr-1 . Co. Co19]. mcr-1 . Plasmid animals . In the he world . Furtherhe world , 22 and he world  have alsA source for transmission to humans can be antimicrobial resistant bacteria in livestock such as livestock-associated MRSA (LA-MRSA), or ESBL-producing Enterobacterales , 25. TheE.coli depends on the animal species and is highest in poultry (8.9–60%) , 9998, 9 monkeys  or chimp monkeys , 102. Th monkeys . Notewor monkeys . For insn island .Muscidae, Calliphoridae) belong to the order Diptera (true flies) and are coprophagous insects. By consuming faeces from larger animals and humans, and in this way also bacteria, ‘filth flies’ can be both a reservoir and a vector of antimicrobial resistant bacteria. Thus, ‘filth flies’ could be a link between humans, livestock, wildlife, and bushmeat, particularly in LMIC where adequate sanitation systems are often lacking. The capacity to be a reservoir is, however, limited as the alimentary tract of the flies is a hostile environment to the majority of bacterial species  [3 of viable bacterial cells (colony forming units) can be transmitted from the exoskeleton per landing [E.coli is the most relevant in ‘filth flies’ in LMIC  with colonization rates between 0.8 and 72.5% (Table E.coli from flies (24.4–100%) [E.coli are much higher in the hospital environment than in rural areas as shown in Nigeria and Ethiopia [blaCTX-M, blaCMY-2) can be horizontally transferred between different bacterial strains within flies [mcr-1 and blaTEM-1 [So called ‘filth flies’  . Althouguginosa) . The sam landing . Among a.4–100%) –110. It Ethiopia , 111. Thin flies . Not onlblaTEM-1 .Table 3CMRSA colonization in flies is poorly investigated and varies markedly between geographic regions 0.2–25.3%) in LMIC  put forward the Global Action Plan for AMR (GAP-AMR) which sets five strategic objectives that aim to reduce the burden of AMR and preserve our ability to treat infections effectively . In thesThe Tripartite Integrated Surveillance System on AMR/AMU (TISSA) is a platform that integrates surveillance data across different organisations and areas. Specifically TISSA is meant to integrate four monitoring and surveillance systems across the three organizations , WOAH surveillance data on antimicrobial use in animals, ATLASS, and TrACSS) thus encompassing human and animal health, plants, and the environment .E.coli. By employing standard methodologies for surveillance and the project will enable participating countries to develop further surveillance systems involving other pathogens and resistance mechanisms [To further emphasize the interconnectivity across sectors in the efforts to combat AMR, the WHO is planning the Tricycle project which will integrate surveillance in humans, animals and the environment Fig. . The prochanisms .In addition, the Tripartite organizations have developed a One Health priority research agenda to promote scientific interest, increase investment and inform policies related to AMR . One HeaSeveral measures can be taken to mitigate the emergence and transmission of AMR. Strengthening AMR surveillance and research within but also across sectors can lead to a better understanding of the burden of resistance and enable the implementation of setting-specific measures to prevent further spread. This can only be achieved by increasing diagnostic capacity, by developing reliable integrated systems for reporting AMR data across countries, laboratories and sectors , and by ensuring access to funding for undertaking these activities particularly in LMIC. Of critical importance is also ensuring that data are representative and thus correctly reflect the local/regional AMR landscape. Similarly, reliable data on AMU in animals are needed to inform policy and plan educational interventions for effecting behaviour change and reducing AMU.Developing new antimicrobial classes and systems , that are used only in food production, would make the emergence of resistance to these antimicrobials less problematic to human health . FurtherLawsoniaintracellularis led to an important reduction in AMU and improved productivity [Vaccines are a promising tool for combating AMR. These act directly by reducing the incidence of infections overall, and thus of resistant infections, and indirectly by reducing AMU. For instance, vaccination of pigs against uctivity  Vaccinesuctivity .Policies and regulations controlling and restricting the use of antimicrobials critical for human health, the uncontrolled purchase of antimicrobials and their use for growth-promotion in animals would lead to safeguarding the future of antimicrobials . PromotiThis review set out to provide an overview on the zoonotic sources of AMR, associated challenges and relevance to LMIC. Livestock farming accounts for substantial AMU in both high- and low-income settings. While regulations to control and restrict excessive use of antimicrobials have been implemented in high-resource settings, efforts should be made to support LMIC in developing strategies to better monitor and optimise AMU. Furthermore, bushmeat and aquaculture are relevant sources of animal meat in LMIC and should be targeted for AMR surveillance and research. Therefore, measures tailored to the specific features of LMIC need to implemented to contain the spread of AMR. Addressing AMR across sectors and settings, will prevent the development and transmission of resistance as well as preserve our ability to effectively treat infections in humans and animals.


Since the discovery, antimicrobials have been used to treat variety of infections both in humans and animals caused by microbes. However, with the increasing use, microbes developed resistance to the antimicrobials and many of the antimicrobials became ineffective against certain microbes. Many factors are reported to contribute to the resistance of microbes to antimicrobials. One contributing factor is the misuse and overuse of antibiotics which mainly occur due to the lack of knowledge, careless attitudes, and incorrect practices about use of antibiotics.This cross-sectional survey study was conducted among the competent persons (CP) in the community pharmacies in Bhutan, with the aim to assess their knowledge, attitude and practice (KAP) on antimicrobial use (AMU) and antimicrobial resistance (AMR).Results from the survey revealed that the competent persons had good level of knowledge about antimicrobial use and antimicrobial resistance. They also had favourable attitude towards antimicrobial resistance and rational use of antimicrobials. Their knowledge and attitude had led to good practices while dispensing antimicrobials from their pharmacies. However, almost all of them had never had any opportunity to take part in activities related to antimicrobial use and antimicrobial resistance that were organized by the public sector. Many of them did not even hear or know about the existence of the policies on use of antimicrobials or on curbing antimicrobial resistance in the country.Involvement of the community pharmacies through trainings and participations in policy making processes is seen as a vital mechanism that can eventually help achieve the goals in the national drive towards reducing antimicrobial resistance. Since the first discovery of penicillin by Sir Alexander Fleming in 1928 . The devA systematic review and meta-analysis has shown the inappropriate use of antibiotics by the general population, as seen in behaviors such as purchasing antibiotics without a prescription from pharmacies and not completing the entire course of antibiotics as prescribed by the physicians which causes the microbes to become resistant leading to AMR . AnotherNeisseria gonorrhoea against ciprofloxacin (85.1%), penicillin (99.2%), tetracycline (84.8%) and nalidixic acid 99.7% (E. coli was resistant to ampicillin (73.5%) and 3rd gen cephalosporins (73.2%), K. pneumoniae was resistant to 3rd gen cephalosporins (78.2%) and aminoglycosides (63.9%), and S. aureus was resistant to penicillin (98.3%)  . What isTaking into account the possible contributing factors toward misuse of antimicrobials and AMR, this cross-sectional study is aimed at assessing the knowledge, attitude and practice of the competent persons (CPs) in the community pharmacies on antimicrobial use (AMU) and AMR. As per Bhutan Medicines Rules and Regulation 2019 “CP refers to any person who possesses the requisite qualifications and practical experience prescribed by the Bhutan Medicines Board and is approved to undertake retail sale and dispensing of Medicinal Products.”2.2.1.A descriptive cross-sectional survey was carried out from October to November 2021, in 55 operational community pharmacies across the country, 2.2.Data was collected using Epicollect 5 . Data validation and analysis were performed using SPSS software  and MS excel. Results are presented in frequencies and percentages. The geospatial information of community pharmacies was established using QGIS LTR 3.16. Descriptive statistics were performed by calculating the proportions of frequencies to describe the demographic characteristics and KAP score. For the knowledge and the practice section, a score of “1” was allotted for the correct answer and “0” for the wrong answer, based on the regulatory requirements and international practices. The total score was then added and those who scored above the mean was categorized as “good” and those who scored equal to and below the mean were defined as “poor” in terms of knowledge and practice on AMU and AMR.The attitude section had parameters whereby the responses can be easily differentiated into having a “favorable” or “unfavorable” attitude toward AMU and AMR.2.3.Since the survey was carried out as part of a routine regulatory activity of the DRA of Bhutan, ethics approval was not required by the local ethics board. Administrative permission was granted by the DRA to use the data for publication. No identifiable variables were collected and all participants provided informed consent after reading and agreeing to the information and consent form on the first page of the online survey.3.3.1.n = 36) were male and 37.93% (n = 22) were female. Most of the survey participants fell under the age range of 26–35 . Almost half of the CPs  had less than 5 years of experience and the majority of them had certificate level  and bachelor’s degree qualifications   .3.2.n = 56) CPs had scored >60, 62.07% (n = 36) hxad scored >70, 32.76% (n = 19) had scored >80 and 8.62% (n = 5) had scored >90%, n = 17) chose the wrong option, while many  selected only 1 option. Only a small number of CPs  selected all the 5 antimicrobials correctly from the list, n = 41) were aware that antibiotics are not effective against the common cold or flu. Most of them  were also aware that inappropriate use of antimicrobials would lead to AMR. Almost all the CPs  knew that antibiotics should not be stopped soon after the disease symptoms were resolved. All of them were aware that they cannot dispense antibiotics for similar previous infections without prescription and also that SOPs were required for storage and dispensing of medicines. Most of them  knew that they had to retain a copy of prescription for every antibiotic sold. However, quite a huge number of them  did not know that they were not allowed to sell tropical antibiotics without a prescription, while a few  were not at all aware of such legislation, The overall knowledge scores of the CPs were found to be above 50%. Out of that, 89.66% , Internet (36), and Bhutan National Formulary (35) based on the frequency of sources selected, In terms of possible interventions by the CPs for patients with minor side effects, referral to hospital was the most frequently chosen option (36), followed by reassurance (15) and investigation of the severity, and advising accordingly (11), 3.3.n = 40) of the 58 CPs interviewed accepted that AMR is a global issue, and 62.07% (n = 36) recognized AMR as an issue of concern in Bhutan. Half of the CPs (n = 29) felt that the patients coming to their pharmacy had very little understanding on both antimicrobials and AMR, while 18.97% (n = 11) felt that the patients do not have any knowledge on antimicrobials and 34.48% (n = 20) of them are of the opinion that the patients visiting their pharmacies have no understanding on AMR at all. Majority of the CPs  felt that it is crucial to advise the patients on complying with treatment when antimicrobials are dispensed and likewise, 77.59% (n = 45) of the CPs felt that patients value their counseling on rational use of antimicrobials.More than half  stated that they did not have opportunities to attend Continued Medical education (CME) on AMR and all of them were willing to attend CMEs, conference and workshops on antimicrobials and AMR for better understanding and practice, as majority of them  felt that CPs played an important role in tackling AMR, Close to half of the CPs  had scored above the mean in the overall practice scores, while 89.66% (n = 52), 63.79% (n = 37), 63.79% (n = 37) and 22.41% (n = 13) of them had scored more than 60, 70, 80 and 90%, respectively, n = 53) of CPs out of 58 maintained records whereas 8.62% (n = 5) did not maintain records of antimicrobials sold. Majority of the CPs  checked the appropriateness of prescription, specifically rationality of prescription, while 5.17% (n = 3) did not. From 58 CPs who cross-checked the prescriptions, 52.73% (n = 29) of them reported receiving inappropriate prescriptions with antimicrobials, and out of that, 79.31% (n = 23) of them communicated to the prescriber regarding the inappropriate prescriptions. While 22.41% (n = 13) of CPs had participated in antimicrobial-awareness activities, majority of them 77.59% (n = 45) did not get any opportunities to take part in such activities. The community pharmacies in the country authorized by the DRA are also allowed to sell veterinary medicines in addition to human allopathic medicines. Out of 55 community pharmacies involved in the survey, 14.55% (n = 8) of community pharmacies dealt with both human and veterinary antimicrobials while the remaining pharmacies dealt only with human antimicrobials, Almost all of the CPs  were aware of AMR. However, the knowledgeable rating on the overall scores may not imply that all the CPs were well aware of the AMU and AMR. When we analysed the responses to the survey questions individually, we found out that quite a huge number of CPs have given the wrong responses to some of the critical questions. With regard to the law of selling antibiotics without prescriptions, many of them  were not aware that they were not allowed to sell antibiotics without prescriptions, while a few  were not at all aware of that law. This is comparable to a study conducted in Northeast China where nearly half of the participants  sell antimicrobials without a prescription to patients occasionally (n = 41) were aware that antibiotics are not indicated for common cold or flu, indicating a higher level of knowledge compared to a study conducted in Indonesia where more than half of respondents  assumed that antibiotics can be used to treat virus infection (n = 53) also knew that antibiotics should not be stopped soon after disease symptoms were resolved. In line with earlier studies (n = 56) agreed that inappropriate use of antimicrobials would lead to AMR.Our results showed that the CPs at the community pharmacies had a good overall knowledge on AMU and AMR with 100% of them securing more than the mean score. Almost all of them  strongly agreed that it is an issue in our country as well. In this context, 50% of the CPs (n = 29) agreed that one of the leading factors could be the lack of knowledge or little understanding on AMU and AMR by the general public as evidenced by the findings from this study. In addition, the majority of CPs also agreed that the community pharmacies played a vital role in tackling AMR in the community. In agreement to the responses from the CPs , ensuring antimicrobials are dispensed only on prescription, educating the patients on rational use of antimicrobials, and also educating the general public on AMR could be core components while dispensing. And this looks possibly successful since most of the patients  coming to the pharmacies were found to value the counseling and instructions given by the CPs.Reports suggest that AMR is mainly driven by misuse of antibiotics due to lack of knowledge on antimicrobials , 17. Whin = 45) of them did not take part in any antimicrobial-awareness activities given the limited opportunity and platform. Hence it is evident that to improve the public-private partnership toward curving the issues of AMR, community pharmacies should be given priority while making policies with regard to AMU and AMR.Considering the overall good knowledge and attitude toward AMU and AMR of the CPs in the community pharmacies as revealed by this study, the practice toward rational AMU and AMR awareness were found comparatively adequate with compliance above the mean value. However, as revealed by this study, there are a number of CPs who do not really understand the concept of AMU and AMR, although the majority had satisfyingly adequate overall knowledge and practice on AMU and AMR. Hence, it is impossible to rule out that the sale of antimicrobials by these CPs might be directly or indirectly contributing to the issue of AMR in the country. Providing specific trainings and orientations on the related topics would help build their knowledge and confidence in antimicrobial fields. Moreover, the majority (77.59%, 4.1.Besides our best of efforts, this study does have some limitations. The survey was carried out by the officials of the DRA, which could have caused the respondents to give favorable answers in topics related to regulations. However, the respondents were thoroughly oriented on the objective of the survey and assured of no implications to whatever response they provide during the survey. Other potential limitations include the small sample size and the unequal distribution of the community pharmacies throughout the country.5.This study is the first of its kind in Bhutan, assessing the knowledge, attitude and practices of the CPs in the community pharmacies on antimicrobial use and antimicrobial resistance. Results showed that the CPs had good level of knowledge on AMU and AMR. They had favorable attitude toward AMR and rational use of antimicrobials. Even in practice, they are shown to be following the good practices while dispensing antimicrobials to the patients. However, most of them did not get any opportunities to participate in the awareness activities organized by the public sector. Many of them were not aware of the existence of the policies on reducing AMR. Since antimicrobials are readily available from the community pharmacies, the CPs may be recognized as key players in the national drive toward curbing AMR in the country.The original contributions presented in the study are included in the article/Ethical review and approval was not required for the study of human participants in accordance with the local legislation and institutional requirements. Written informed consent from the patients/participants was not required to participate in this study in accordance with the national legislation and the institutional requirements.WG, SW, JT, and GT planned the overall survey methodology with WG as the approving official. JT, KPT, and GT carried out the survey along with other officials. JT, KPT, and GT drafted the manuscript. SW and WG reviewed the manuscript. SW sought funding for the survey. All authors contributed to the article and approved the submitted version.This study was funded by the Fleming Fund Project, under the Ministry of Health, Bhutan.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Molecular evolution—including the neutral theory of molecular evolution—is a major sub‐discipline of evolution and is widely taught in undergraduate evolution courses. However, despite its ubiquity, there have not been any previous attempts to compile and review the molecular evolution education literature. Here, we draw upon the framework proposed in a past literature review examining the broader evolution education landscape to conduct a literature review of papers related to molecular evolution education, classifying the contributions of such papers to evolution pedagogy as well as evolution education research. We find that there remains very limited coverage of molecular evolution in the education literature, with existing papers focusing primarily on providing new instructional modules and strategies for teaching molecular evolution. Our work suggests several areas of critical need as well as opportunities to advance evolution education and evolution education research, including compiling instructional goals for the sub‐discipline, developing validated assessments, and investigating student thinking related to molecular evolution. We conclude by providing general strategies, advice, and a novel curricular activity for teaching molecular evolution and the neutral theory of molecular evolution. Molecular evolution is a major sub‐discipline of evolutionary biology and is commonly taught in undergraduate evolution courses. However, despite its ubiquity, there have not been any prior attempts to compile, synthesize, and review the education literature relating to molecular evolution. Here, we provide a literature review on this important field, applying a framework to categorize the available papers in molecular evolution education by their aims and scope, and provide a novel activity and advice for teaching molecular evolution. We then compiled these results to form a database of papers relating to molecular evolution education from 1990 to 2023. For our search, we followed the same procedures outlined in Ziadie and Andrews . We usedType of PCK: First, we identified if each paper presented instructional strategies, examined student thinking, developed new validated assessments, or set educational goals, following the framework used by Ziadie and Andrews , empirical , a literature review, or a paper that presented an author's perspective, following the definitions presented by Ziadie and Andrews  and then examined the learning objectives and materials provided to reach a consensus for which student level the paper would be most appropriate for. We noted any of these student contexts that were inferred from the activity and were not explicitly described in the manuscript with an asterisk in our table.Length and setting of curricular module: For papers that presented instructional strategies, we noted the length of the module, classifying if the activity requires one class period or multiple classes. Given the variation in length for multi‐class modules, we also provided additional details for the suggested number of classes required. For those papers describing general advice and strategies rather than a specific module, we denoted this as “general”. Some papers did not provide estimated lengths for their curricular module, and we again drew inferences based on the materials to estimate the amount of instructional time required. Finally, we also noted if the intervention or curricular module was designed for a course that has a lab setting, which typically requires several hours of time in a row and access to either computational or experimental equipment.Coverage of molecular evolution sub‐discipline: We further classified which sub‐disciplines of molecular evolution that the paper covered. We started by utilizing the list of topics generated by Ziadie and Andrews  were descriptive, with fewer than one third providing any empirical data designed to answer a research question. The descriptive papers provide general descriptions and information for implementing a curricular module and may include anecdotal data from students and instructors , but do not include systematic collection of data to assess the efficacy of the module. However, we note that the relative number of instructional papers with empirical data may be increasing: only two papers that Ziadie and Andrews  identifiWe also identify that the published instructional materials are designed for a range of student levels. Half of the papers were designed for undergraduate students in upper‐division biology classes (including a paper that described a curricular module designed for both introductory and upper‐level students), followed by approximately a third (34.6%) of approaches designed for high school students. In contrast, fewer than one fifth (19.2%) of instructional approaches were geared for introductory biology students, and only three papers described applying the module for undergraduate non‐majors biology courses. Similarly, we find that the published approaches are designed for a diversity of lengths and formats. For instance, a little over half of published approaches (54%) require multiple class sessions, while approximately 40% are designed for a single class . In addition, while the majority of papers describe modules that can be implemented in traditional classrooms, several require computational or molecular labs to support the activity.Finally, we identify uneven coverage of topics in molecular evolution. For instance, we find that some topics, such as protein evolution, mutations and sequence changes, and the molecular clock, were each covered by multiple papers' curricular modules. In contrast, other topics, such as chromatin evolution, RNA evolution, and molecular systematics, only had one paper each providing curriculum in those areas. In addition, we note the major challenge of classifying these instructional papers by their molecular evolution topic. There is no clear, consensus list of learning objectives or competencies related to molecular evolution, nor is there a widely agreed upon list of sub‐disciplines within molecular evolution. In addition, many of the papers included in our review did not list their learning objectives, making it at times challenging to infer the primary goals of the curriculum, and multiple papers described activities that focused upon concepts outside molecular evolution but included some coverage of molecular evolution concepts, again presenting challenges in classifying the molecular evolution topics. Given these challenges, we acknowledge that different evolutionary biologists may bin the coverage areas of each paper differently. We note that our goal of classifying these papers is not to provide a comprehensive list of topics that each paper covers, but instead to determine if there is even coverage of molecular evolution topics across the literature, and to provide a general framework that instructors can use as a starting place for identifying and choosing papers with relevant activities for their courses.Interestingly, we find that none of the papers focused on teaching the neutral theory, indicating that there are currently no published, peer‐reviewed resources for teaching neutral theory or studying how students think about and conceptualize such principles. Only two articles explicitly mention the neutral theory. The first, a lab activity where students build a phylogenetic tree after extracting and sequencing their own DNA, primarily focuses on other evolutionary principles, such as phylogenetics and population genetics , Vision & Change advocates for establishing core concepts for each discipline to guide instructors on what concepts to teach and promotes instructors introducing concepts through a broader conceptual framework rather than as isolated facts (American Association for the Advancement of Science (AAAS), In addition, there is a need to identify “big ideas” and core concepts of molecular evolution for the undergraduate classroom. The literature review identified that the published instructional strategies designed for both high school and undergraduate courses covered a diverse set of molecular evolution principles. However, it remains unclear (1) which concepts and competencies in molecular evolution are most frequently taught in undergraduate biology and evolution courses (and to what extent these topics are covered or previewed in high school biology courses) and (2) which concepts in molecular evolution most instructors, faculty, and evolutionary biologists consider as the most important. There has been a recent effort in other subfields of evolution, such as evolutionary medicine, to establish a list of “big ideas” or “core concepts”  or limited coverage  can be particularly impactful for instructors looking to incorporate additional coverage of molecular evolution in their courses. Similarly, given that the majority of published approaches are designed for upper‐division undergraduate courses or high school courses, there is a major need to develop additional modules specifically geared towards introductory biology and non‐majors courses. In addition, we note that there is an opportunity to assess the effectiveness of currently published modules, most of which were published as descriptive papers and do not provide any formal assessment data. We encourage instructors who implement such curricular modules or strategies to consider systematically gathering and sharing assessment data and other information that can inform how students are thinking about and conceptualizing molecular evolution concepts. Such instructors may wish to consult some of the published resources that are designed to guide instructors who are new to assessment and discipline‐based education research . We examine the context to better situate how neutral theory is presented and what other concepts are presented alongside the neutral theory.How the textbook connected the molecular clock to the neutral theory . We examine the placement of teaching about the molecular clock to the neutral theory given that we identified several published resources for teaching about the molecular clock but none on the neutral theory, and that the neutral theory is often used to explain the constant rates of change in molecular clocks . This approach may not be the best for supporting student learning, given that past studies have demonstrated that students may have more challenges comprehending and interpreting symbolic representations of numbers .Mathematically calculate the rate of neutral evolution in different populationsExplain why the rate of neutral evolution is equal to the rate of neutral mutation under the neutral theoryDraw inferences about how a constant rate of neutral evolution can inform the molecular clockThis activity is primarily geared for mid‐ to upper‐level undergraduate evolution courses and is designed to be completed in one class session. There are several learning objectives; by the end of the module, students should be able to:Prior to this lesson, students should be familiar with the evolutionary mechanisms, including mutations, migration, drift, and selection, and should recognize that the probability of fixation for a given allele is equal to its frequency in the population if drift is the only force at play. In addition, instructors should introduce the key ideas of the neutral theory prior to this activity and provide context for why it is important to mathematically calculate the rate of neutral evolution in various populations if the main principles of the neutral theory hold true. Casillas and Barbadilla  provide Vision & Change (American Association for the Advancement of Science (AAAS), The activity is set up around students working with two sample populations with the same neutral mutation rate, but different population sizes. Students are challenged to think critically and calculate the number of new neutral mutations, the probability of each new mutation reaching fixation under neutrality, and the expected number of neutral mutations reaching fixation. Students are guided to reach the conclusions that population size has no impact on the rate of neutral evolution, and to discover that the rate of neutral evolution is always equal to the rate of neutral mutation. This activity is thus organized as an inquiry‐based activity where students are asking and addressing key questions pertaining to the neutral theory and also developing quantitative reasoning skills, a core competency identified as important in many national calls, such as 5We recognize several limitations of our work. First, while we made every effort to be comprehensive in our literature review, we acknowledge that there is the possibility that additional literature exists that is relevant to molecular evolution but not found through our keyword search. In addition, our search followed the approach of the systematic review reported by Ziadie and Andrews  and usedDesiree Forsythe: Conceptualization ; data curation ; writing – original draft ; writing – review and editing . Jeremy L. Hsu: Conceptualization ; data curation ; writing – original draft ; writing – review and editing .The authors declare no conflicts of interest.Table S1.Click here for additional data file.Appendix S1.Click here for additional data file.