Neisseria gonorrhoeae antimicrobial resistance (NG AMR) has become an urgent concern globally. The World Health Organization, the United States of America Centers for Disease Control, and other regulators have called to improve resistance-testing methods to enhance NG AMR surveillance. NG AMR surveillance remains critical in informing treatment; unfortunately, this is often lacking in settings with limited resources, such as Papua New Guinea (PNG). We conducted a systematic review and a prevalence meta-analysis, and provided an overview of NG AMR in PNG. We showed the lack of NG AMR data in the last decade, and emphasized the need for NG AMR surveillance in PNG. Since NG AMR testing by the NG culture method is unreliable in PNG, we suggested using molecular tests to complement and enhance NG AMR surveillance. Neisseria gonorrhoeae antimicrobial resistance (NG AMR) [Neisseria species [One of the most urgent threats to sexual health globally is the progressive development and spread of (NG AMR) ,2. NG ca species . Some pu species ,2,4. In  species . Promine species ,6.The “gold standard” for NG AMR testing is the culture method . HoweverThe WHO recommended that national NG AMR surveillance be done at regular intervals to inform treatment. If observed resistance prevalence is above 5% for any antibiotics, a change in treatment is required ,5. DespiPapua New Guinea (PNG) has some of the highest prevalence of sexually transmitted infection (STI) in the WPR . The recThe standard treatment for gonorrhea in PNG is a single-dose cocktail of the following antibiotics: amoxicillin (penicillin), probenecid (uricosurics), augmentin (penicillinase/beta-lactamase inhibitor), and azithromycin (macrolide) . OccasioNeisseria gonorrhoeae” or “Neisseria” or “gonorrhoea” or “gonococcus” or “gonococcal” or “sexually transmitted infection” or “sexually transmitted disease” or “venereal disease” and “resistance” or “antibiotic resistance” or “antimicrobial resistance” and “Papua New Guinea”. The articles generated from the search were then screened following the set eligibility criteria outlined below for inclusion in the meta-analysis.The systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method . MEDLINE-Original study that investigated NG AMR in humans from PNG;-Peer-reviewed articles published between January 1980 and October 2020. The cut-off year was set at 1980 and after was to ensure that the reported prevalence in the primary studies were generated using the Australia Gonococcal Surveillance Program (AGSP) and/or the WHO Gonococcal Antimicrobial Surveillance Program (GASP) methodology. These two programs use similar standardized methods for NG AMR testing and result interpretation;-The total number of samples or isolates analyzed and the resistance prevalence described and stated. This was to ensure that we have the exact numerator (number of sample or isolates that were resistant to the antibiotic tested against) and denominator  to enable accurate proportion estimations in the meta-analysis; and-Abstract and full text available in English.Inclusion criteria:Two independent reviewers  screened the full articles. The data extracted from the papers were: article reference (following the Vancouver referencing style); country of study; year or period in which the study was conducted (year of sampling); year of publication; number of samples/isolates; and number of isolates that were successfully profiled for NG AMR for the following antibiotics of interest—penicillin (amoxicillin), tetracycline, macrolide (azithromycin), quinolone (ciprofloxacin), aminoglycoside (spectinomycin), and cephalosporins (ceftriaxone and or cefixime).2 > 25%) [The data were collated and managed by removing duplicate articles in Microsoft Excel 365 , and the Endnote referencing software  . Prevale2 > 25%) .A total of 1574 articles was generated following the literature search strategies mentioned above. All these papers were in English, and none in other languages. After removing duplicates, 377 articles remained. On further screening of the title and abstract of these 377 papers, 62 articles showed to report NG AMR in humans in PNG. Full-text articles of these 62 papers were accessed and screened following the inclusion criteria mentioned above. Out of the 62 articles, only 15 papers met the eligibility criteria and were included in the prevalence meta-analysis, see n = 17), chromosomally mediated penicillin resistance (n = 13), tetracycline resistance (n = 13), quinolone (ciprofloxacin) resistance (n = 17), aminoglycoside (spectinomycin) resistance (n = 7), macrolide (azithromycin) resistance (n = 2) and cephalosporin (ceftriaxone and or cefixime) resistance (n = 8), and, additionally, the small sample size used in the primary studies, these resulted in wide ninety-five percentage confidence intervals (95% CI) in this meta-analysis, see Because of the small data points (based on year of sample collection) included in the meta-analysis, 17 data points for plasmid-mediated penicillin resistance (2 = 95% (p ≤ 0.05), see The pooled PPNG resistance prevalence is estimated to be 37.9% (95% CI: 29.3–47.2) in this meta-analysis, see 2 = 94%), see The prevalence of chromosomally-mediated resistance to penicillin (CMR-penicillin) was significantly heterogeneous (I2 = 93%) of the reported prevalence, with the mention of a high reported resistance prevalence in a recent study in 2016, 37.9% (95% CI: 26.2–49.6).Generally, there was an increase in the reported tetracycline resistance prevalence over time. The pooled tetracycline resistance prevalence estimate is 10.3% (95% CI: 6.2–16.5%), just above the 5% threshold, see 2 = 60%), see Overall, the reported quinolone resistance prevalence in the primary studies was heterogeneous (I2 = 0.0%). The estimated pooled prevalence is below the threshold, 1.3% (95% CI: 0.6–2.6), see The reported aminoglycoside (spectinomycin) resistance prevalence is homogeneous (I2 = 0.0%), with an estimated prevalence of 0.5% (95% CI: 0.2–1.2), see The reported resistance prevalence from the papers analyzed for cephalosporin resistance was homogenous  and tetracycline (10.3%). Yet, interpretations of these pooled estimates must be made with caution because resistance prevalence above the threshold has been reported. Most of the PNGs’ NG AMR data were from the WHO WPR GASP. During PNGs participation in the WPR GASP, PNG consistently submitted samples to the NG AMR surveillance program between 1993 and 2009. One-hundred and ninety-three (193) samples were submitted on average per year by PNG to the program, similar to Brunei, Japan, Korea, the Philippines, Vanuatu, and Vietnam. However, this was lower than Australia, Hong Kong, and Fiji, who were submitting 600–3000 samples per year in that same period. The main limitation of PNG NG AMR data was that the samples were collected from a few sites, and restricted to STI clinics.Our prevalence meta-analysis showed an increase in PPNG prevalence from 1989 to 2009. PNG has reported some of the highest prevalence of PPNG in the WHO WPR and SEAR. The pooled PPNG prevalence estimate  in this meta-analysis is similar to that observed in other countries in the WHO WPR and SEAR, such as Hong Kong (32.4%), Malaysia (30%), and Vietnam (32.5%) . DespiteJapan has reported the highest prevalence of CMR to penicillin (39%), whereas other countries in the WPR and SEAR reported CMR to penicillin in the range of 10–20% . The pooTetracycline is not the recommended antibiotic for treating gonorrhea, but is sporadically used. Our analysis showed an increase in tetracycline resistance prevalence between 1989 and 2000, followed by a decline between 2001 and 2004 in PNG. Surprisingly, a spike in prevalence was reported in 2016 in PNG, estimated at 37.6% (95% CI: 26.2–49.6), see Several studies in PNG have reported a high prevalence of ciprofloxacin resistance in the mid to late 1990s, followed by a decline. A similar trend was seen for spectinomycin resistance. The declining resistance prevalence may be due to the strict use of amoxicillin and azithromycin. With the rise of ciprofloxacin resistance in the WPR , PNG needs research and surveillance to ascertain the observed decline .The only three countries in the WHO WPR that are still using penicillin and azithromycin for treating gonorrhea are PNG, Fiji, and the Solomon Islands. The rest of the countries in the region use cephalosporins (ceftriaxone or cefixime) and azithromycin ,44. HoweOur analysis showed that the estimated pooled resistance prevalence for most antibiotics is below the 5% threshold. This suggested the possibility to use other drug combinations, then to quickly use the last line of treatment. At the same time, it must be noted that most of the studies included in this meta-analysis were conducted a decade ago. Thus, this could mean that the estimates reported here may be outdated due to the lack of recent NG AMR surveillance in PNG.The lack of representative and updated NG AMR data in PNG emphasizes the need to explore methods other than the culture method, such as molecular methods, to complement and support the culture method for NG AMR surveillance. Molecular testing has increasingly been used for NG and NG AMR testing in many countries, and is proving to be an invaluable tool for NG AMR surveillance . Given iN. gonorrhea AMR prevalence results presented here are as reported in the primary studies, where multiple drug resistance by individual samples were not reported. Therefore, it is not possible to determine the presence of multi-drug resistant N. gonorrhea strains from these articles. Third, the data points analyzed in this study are small . The small data points and the small sample size analyzed in the primary studies have resulted in large 95% CI values in this analysis. Therefore, caution is required in the interpretation of these estimates until additional, more robust data is available.We acknowledge that there are limitations to this study. First, the article search was done in the MEDLINE, EMBASE, Google Scholar, and Papua New Guinea Institute of Medical Research Library databases; therefore, articles not indexed in these databases may have been missed. Second, the In Papua New Guinea (PNG), penicillin and azithromycin remain the standard treatment for gonorrhea. That may soon change as per the newly drafted National STI Treatment Guidelines. Cephalosporins (cefixime and ceftriaxone) and azithromycin are now the recommended treatment for NG in PNG. However, PNG does not have sufficient NG AMR data to inform this change, which was acknowledged in the new treatment guidelines. This highlights the need for evidence-based research and surveillance of NG AMR in PNG.In support of the latter, we showed that PNG has no national representative and updated NG AMR data in the last decade. Moreover, our meta-analysis showed inconsistencies in the reported NG AMR prevalence.Though the culture method remains the “gold standard” for NG AMR testing, it requires viable NG bacteria. Maintaining viable bacteria for culture is often challenging in PNG because of the logistical difficulties and costs associated with the storage and transportation of viable NG bacteria, which severely affects NG AMR testing. Thus, it is appropriate to consider molecular testing methods for NG AMR testing and surveillance in PNG. Considering the advantages discussed earlier, molecular methods could be established easily, and used to enhance NG AMR surveillance quickly and efficiently in PNG.


The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm for Dialogue Management that selects the most appropriate conversation topic depending on the user input. Moreover, it discusses strategies to ensure a conversation flow that captures, as more coherently as possible, the user intention to drive the conversation in specific directions while avoiding purely reactive responses to what the user says. To measure the quality of the conversation, the article reports the tests performed with 100 recruited participants, comparing five conversational agents: (i) an agent addressing dialogue flow management based only on the detection of keywords in the speech, (ii) an agent based both on the detection of keywords and the Content Classification feature of Google Cloud Natural Language, (iii) an agent that picks conversation topics randomly, (iv) a human pretending to be a chatbot, and (v) one of the most famous chatbots worldwide: Replika. The subjective perception of the participants is measured both with the SASSI (Subjective Assessment of Speech System Interfaces) tool, as well as with a custom survey for measuring the subjective perception of coherence. Social Robotics is a research field aimed at providing robots with a brand new set of skills, specifically related to social behaviour and natural interaction with humans.Social robots can be used in many contexts such as education , welcomiIn particular, robots may help to cope with caregiver burden, i.e., the stress perceived by formal and informal caregivers, a relevant problem both in care homes and domestic environments. This subjective burden is one of the most important predictors for adverse outcomes of the care situation for the caregivers themselves, as well as for the one who requires care. Clinicians frequently overlook the caregiver burden problem .Recently, social robots have been recognized as a very important resource by one of the most recent editorials of Science Robotics , which atask-oriented: it is used to give commands to perform a task or retrieve information. Examples of task-oriented conversations can be found both during the interaction with a robot, i.e., “Go to the kitchen”, and during the interaction with a smart assistant, i.e., “Turn off the light”. In this case, the problem is to understand the semantics of what the user is saying, to provide the required service.chit-chatting: it has the purpose of gratifying the user in the medium to long term, keeping him/her engaged and interested. For this kind of conversation, the most relevant problem, rather than perfectly grasping the semantics of what the person says, is managing the conversation, showing the knowledge and competence on a huge number of different topics coherently and entertainingly 14] usingIn the Literature, tools exist that can be used to evaluate the User Experience (UX) and the overall quality of the conversation. The work carried on in  reviews As a measure of the quality of the flow of conversation, we aim to evaluate how “coherent” the system is: this shall be done not only taking into account the last user utterance but also the current conversation topic . ToSystem Response Accuracy scale of the SASSI questionnaire: such a questionnaire, described more in detail in Sect. System Response Accuracy is defined as the system’s ability to correctly recognise the speech input, correctly interpret the meaning of the utterance, and then act appropriately. However, according to the aforementioned definition, what the System Response Accuracy scale aims to measure is not equivalent to the broader concept of coherence that has been given: it measures the quality of the system’s reply to the user input in a purely reactive fashion, without relying on the concept of “current topic of conversation”.Unfortunately, the aforementioned UX tools are not meant to evaluate topic coherence in a mixed-initiative dialogue, as in our case. The most similar measure to what we want to evaluate is the For this reason, a coherence measure in the spirit of  and 32]32] has bQuestion answering bots: knowledge-based conversational systems that answer to users queries by analysing the underlying information collected from various sources like Wikipedia, DailyMail, Allen AI science and Quiz Bowl [uiz Bowl ;Task-oriented bots: conversational systems that assist in achieving a particular task or attempt to solve a specific problem such as a flight booking or hotel reservation [ervation ;Social bots: conversational systems that communicate with users as companions, and possibly entertain or give recommendations to them [ to them : recent  to them  and ReplIn the following, we discuss more in detail the agents belonging to the third class pointing out differences and similarities with our solution, without making a distinction between robots and chatbots, unless strictly required.Depending on the emphasis they put on a task-oriented conversation or chit-chatting, a typical classification for artificial conversational agents is based on their scope:For many decades, the development of social bots, or intelligent dialogue systems that can engage in empathetic conversations with humans, has been one of the main goals of Artificial Intelligence. As stated in , early cXiaoIce (“Little Ice” in Chinese) is one of the most popular chatbots in the world. It is available in 5 countries  under different names  on more than 40 platforms, including WeChat, QQ, Weibo, and Meipai in China, Facebook Messenger in the United States and India, and LINE in Japan and Indonesia. Its primary goal is to be an AI companion with which users form long-term emotional connections: this distinguishes XiaoIce not only from early chatbots but also from other recently developed conversational AI personal assistants such as Apple Siri, Amazon Alexa, Google Assistant, and Microsoft Cortana.As stated in , the topReplika is presented as a messaging app where users answer questions to build a digital library of information about themselves. Its creator, a San Francisco-based startup called Luka, sees a whole bunch of possible uses for it: a digital twin to serve as a companion for the lonely, a living memorial of the dead, created for those left behind, or even, one day, a version of ourselves that can carry out all the mundane tasks that we humans have to do, but never want to.To the best of the authors’ knowledge, there is no detailed explanation of the implementation of Replika, hence we can only make assumptions on how issues related to Dialogue Management are faced. After having intensively tried Replika, it seems that the conversation is partitioned into “sessions” in which it has specific competencies, somehow playing a similar role as topics in XiaoIce and our system. Concerning issue 7 in Sect. MitsukuThe Pandorabots chatbot framework is based on the Artificial Intelligence Markup Language (AIML) scripting language, which developers can use to create conversational bots. The downside is that Pandorabots do not include machine learning tools that are common on other chatbot building platforms. A specific AIML file allows users to teach Mitsuku new facts: the user should say “Learn” followed by the fact . The taught information is emailed to its creator Steve Worswick, which will personally supervise the learning process. To address issue 7 in Sect. Insomnobot-3000In addition to the aforementioned chatbot available to the large public, recent research on data-driven knowledge-grounded conversation based on sophisticated generative models is worth being mentioned.Meena [ pairs is used to train and evaluate the network. Experiments show significant improvements in SSA with respect to competitors, providing replies that are coherent with what the user said and, at the same time, more specific to the context. Authors also report that issues related to inappropriate and biased language still need to be addressed: to the best of our knowledge, a publicly available version of this chatbot has not been released yet.Meena  is a genBlenderBot [enderBot  is a verenderBot , which rDialoGPT  is a neuAll generative models based on human-human data offer many advantages in producing human-like utterances fitting the context but have the major drawback that they can learn undesirable features leading to toxic or biased language. Classifiers to filter out inappropriate language exist , but theEven if the focus of this article is on knowledge-based chit-chatting and dialogue flow management, and not on cultural adaptation, it is necessary to briefly introduce the structure of the cultural knowledge base used by the CARESSES conversational system since it strongly influences the algorithms we implemented.In CARESSES, the ability of the companion robot to naturally converse with the user has been achieved by creating a framework for cultural knowledge representation that relies on an Ontology  implemenTo deal with representations of the world that may vary across different cultures , the OntTo implement this mechanism, the Culture-Specific ABox layer comprises instances of concepts  Fig. , used byFrom here on, we define a topic as a node of the DT. The relation between topics is borrowed from the structure of the Ontology: specifically, the Object Property hasTopic, its sub-properties, and the hierarchical relationships among concepts and instances are analyzed to define the nodes and the branches of the DT. In the example of Figure As mentioned, each conversation topic has chunks of culturally appropriate sentences associated with it that are automatically composed and used during the conversation. Such sentences can be of different types . They are selected in subsequent iterations, depending on internal rules and the input received from the user . Then, in the higher-level topics of the DT, the sentence would sound like “I love movies with great actors”. In the lower-level topics, the variables $hasName and $hasTopic*hasName will be instantiated with more specific types of movies and actors, producing sentences such as “You know... I love Bollywood movies with Amitabh Bachchan”. In the current version used for testing, exploiting variables and the taxonomy of the Ontology allowed us to easily produce a DT with 2,470 conversation topics and 24,033 sentences, with random variations made in run-time.H from DT leaves produces a number of sentences equal to Since this concept is key for automatic sentence generation through variable instantiation and composition, a few additional words are worth spending. Currently, as in the aforementioned example, one sentence may contain variables whose value depends on (i) the specific concept that inherited the sentence from superconcepts in the Ontology, and (ii) related concepts through an Object Property. Then, when manually adding a sentence as a Data Property of a given concept, a number of sentences will be inherited and added automatically depending on the number of (i) its subconcepts and (ii) related concepts through an Object Property. By considering a DT generated from the Ontology and having a maximum branching factor chit-chatting state. In this case, the Dialogue Management algorithm operates to keep the conversation as engaging and natural as possible by implementing two different, intertwined mechanisms to navigate the DT based on what the user says: Navigating the DT according to the topic hierarchy: the first mechanism implemented by the Dialogue Management algorithm simply chooses the topic based on the DT, following the branches from more general conversation topics close to the root  to more specific  or related ones . This is achieved by selecting the DT branches to maximise the probability that the user will be interested in the next topic . When in a topic, the system asks questions, replies with positive or negative assertions, proposes activities or simply encourages the user to freely express his/her view, until the topic has been sufficiently explored. Probabilities associated with topics . After doing so, the system reverts to the first mechanism but starting from the new topic: it asks questions, makes positive and negative comments, proposes activities, or allows the person to freely express their view about the new topic, and then re-start following branches as previously.When the user pronounces a sentence that triggers the start of a conversation, the system switches to the With reference to Figure R. (1): Do you usually drink something with your meals?Mrs S.: Always! At least I try...R. (1): Drinking water is very important for health! Please, tell me more about your drinking preferences.Mrs S.: Well, I mostly drink water during lunch.R. (1): I know that many English persons love tea. Do you?Mrs S.: Yes, of course! But mostly in the afternoon.R. (1): You can never get a cup of tea large enough or a book long enough to suit me. Do you usually have milk with your tea?Mrs S.: Yes, and scones, too! But they are not very healthy.R. (2): I love scones with jam and whipped cream!Figure The diagram shows that, as soon as the person says something that is not a request to stop the execution (box Wait For user input), the Dialogue Management algorithm checks if the user sentence contains some command. We define a command as a sentence pronounced by the user aimed to trigger an activity that is not exclusively related to the conversation. Following the same rationale, we define an activity as any task that the robot might be requested to perform, not only related to the conversation, possibly using third-party services. For instance, the user might issue the command “Show me the weather” to start the corresponding activity that acquires information about the weather (box Perform the required activity). Even if described for completeness, this part of the interaction is not the focus of this work. It has been implemented in our experiments with caring robots during the CARESSES project, but not in the tests described in this article, and it may rely on a third-party system for NLPIf a request to start an activity is not found, the user input is processed (box Process the user sentence by navigating the DT...) by using the two mechanisms described so far: as a first step the user utterance is analysed to check if something relevant is detected, and possibly used to jump to another topic using mechanism 2; if no information is found to jump to another topic, mechanism 1 checks if the current topic shall be further explored or it is time to follow the branches of the DT from a parent node to a child node that is semantically related in the Ontology. Eventually, it should be mentioned that activities  may even be proposed by the Dialogue Management System itself when related to the current topic of discussion . The interaction continues in this way until the user explicitly asks to stop it.This approach to Dialogue Management, despite its simplicity, reveals to be very effective for chit-chatting. It should be reminded that here Dialogue Management is not meant to understand all the nuances of human language when giving a specific command to be executed , but rather it aims at engaging the user in rewarding conversations: an objective that we try to achieve by enabling the system to coherently talk about a huge number of different topics while properly managing the conversation flow. Please notice that the approach has been already tested in the CARESSES project with more than 20 older people of different nationalities, for about 18 hours of conversation split into 6 sessions. Both the quantitative and qualitative analysis performed revealed very positive feedback from the participants . HoweverPlease notice that, when navigating in the knowledge base following the branches of the DT (aforementioned mechanism 1), coherence in the flow of conversation is straightforwardly preserved by the fact that two nodes of the DT are semantically close to each other by construction. However, to preserve coherence when deciding if it is needed to jump from one node to another (mechanism 2), proper strategies should be implemented to avoid the feeling that the system is “going off-topic” with respect to what the person says: on the one side, the system needs to be enough responsive to promptly move to another topic if the person wants to; on the other side, the system needs to avoid jumping from one topic to another, overestimating the desire of the person to talk about something else when they would be happier to further explore the current topic of conversation.When using mechanism 2, described in the previous section, to navigate the DT, to preserve coherence in the conversation flow the system uses one of the two following jumping methods: keyword-based topic matching and keyword- and category-based topic matching. These methods differ in terms of complexity and in terms of the need to rely on third-party services to analyze the semantic content of sentences.To avoid confusion, please notice that we use the word “mechanism” to refer to the two ways to navigate the DT , whereas we use the term “jumping methods” to refer to the two different ways to jump between topics when using mechanism 2.The first, and the simpler, jumping method is exclusively based on the detection of keywords in the user sentence . To match a topic, at least two keywords associated with that topic should be detected in the sentence pronounced by the user, using wildcards to enable more versatility in keyword matching. The use of multiple keywords allows the system to differentiate between semantically close topics .Figure If the user sentence contains the two keywords corresponding to a topic in the Ontology (left part of the diagram), the algorithm returns a topic of the DT that matches those keywords. In case more topic matches are found, the algorithm randomly chooses one of the matching topics.If there are still relevant questions to be asked or assertions to be made about that topic, the system stays on the same topic.If not at the bottom of the DT, the Dialogue Management System keeps on exploring the DT along its branches;Otherwise the algorithm returns a random topic immediately below the root.Otherwise:Otherwise:This basic approach, despite its simplicity, has been successfully exploited during the experimental trial in care homes, and its capability to provide  coherent, knowledge-grounded replies, was confirmed in public exhibitions. However, when focusing on coherence, the approach has obvious limitations. Let’s suppose that the user is having a conversation with the system and at some point, for some reason, the user says “My bank account has a high interest”. This sentence, like any other sentence, is provided as input to the keyword-based jumping method, to find the most appropriate topic to continue the conversation. The algorithm finds the word “interest” matching with the keyword_1 of the topic HOBBY. Then, it checks if the sentence contains a word matching with keyword_2 associated with the same topic: however, in this case, a wildcard is used in the topic HOBBY for keyword_2 to guarantee that the first keyword alone is sufficient to determine the next topic. As a result, the algorithm will return the only matching node of the DT: the system will start asking the user about their hobbies . The second limitation related to the behaviour of this algorithm arises when no keywords are found and we are at the bottom of the DT: in this case, as already mentioned, the algorithm has no information to continue the conversation and jumps to a random topic close to the root.The second jumping method is meant to solve the issues of the previous method, or at least reduce their frequency, by enabling a more complex understanding of the semantic content of the sentence. For this purpose, this jumping method not only exploits the keywords, but it also takes into account the “category” of the user sentence: in the current implementation, it uses the third-party services provided by Cloud Natural Language (CNL) APIand CNL returns at least a category associated with the sentence (left part of the diagram), the jumping method selects the topic(s) in the Ontology with the greatest number of categories in common: if there is more than one topic, it picks the closest to the DT root or, if there are multiple topics at the same level, it chooses randomly;If the user sentence contains the two keywords corresponding to a topic in the Ontology or the sentence does not have any category:If there are still relevant questions to be asked or assertions to be made about that topic, the system stays on the same topic.If not at the bottom of the DT, the Dialogue Management System keeps on exploring the DT along its branches;or CNL categories associated with the sentence , the jumping method selects the topic(s) with matching keywords or the greatest number of categories in common: if multiple, it picks the one closer to the root in the DT or randomly if they are at the same level.If there are keywords Otherwise, the jumping method returns a random topic immediately below the root.Otherwise:Otherwise:Otherwise, if keywords do not match  This second jumping method is more complex and computationally expensive than the previous one , but it provides more stability and consistency when selecting the next conversation topic. Also, it diminishes the chance of performing random changes of conversation topic when at the bottom of the DT and no keywords are found: if the sentence has at least one category associated, recognized by CNL, there is still a chance of finding a coherent topic to jump to in order to continue the conversation.To exploit the information related to the category of the sentence, the Content Classification of the topics contained in the Ontology is a fundamental operation and needs to be performed in a setup phase to create a mapping between the topics contained in the Ontology and the CNL category hierarchy. Off-line, before the system starts, the classification procedure is performed for all the topics. An algorithm puts together all the sentences associated with each topic , sends Evaluate the impact of the different solutions for Dialogue Management we developed, either keyword-based or both keyword- and category-based, to improve the subjective perception of the system in terms of coherence and user satisfaction;Compare our solutions with Replika  as well as with baselines consisting of a system choosing replies randomly, and with a human pretending to be a chatbot.Among the most famous chatbots mentioned in Sect. Experimental tests with recruited participants have been performed for multiple purposes:The system exploiting the keyword-based Dialogue Management algorithm;The system exploiting the keyword and category-based Dialogue Management algorithm;A system that chooses the next topic randomly ;A human pretending to be a chatbot ;Replika.It shall be reminded that the purpose of the experiments is to test the impact of the Dialogue Management solutions we proposed, which emphasize the problem of switching between different topics and not sentence generation. Since Replika uses GPT-2, a language generation model, it is expected to perform better in generating individual sentences than systems 1, 2, and 3, and a human pretending to be a chatbot is expected to perform even better.The participants for this test have been recruited through posts on Social Networks (Facebook and Twitter) as well as in Robotics and Computer Science classes at the University of Genoa, for a total of 100 volunteer participants aged between 25 and 65. The only inclusion criteria are that participants shall be able to read and write in English and to use a PC with a network connection from home. Since the test is anonymous and no personal data is collected, the whole procedure is fully compliant with the EU General Data Protection Regulation. Each time a new participant is recruited, they are randomly assigned to a group from 1 to 5 (where each group corresponds to a different conversation system), and given the instructions to perform the test. Based on the group they were assigned, participants had to interact with: Our system is general purpose in the sense that, whatever the user says, it always tries to find the most suitable topic that matches the user expectations. However, in its current version, it composes pre-existing phrases to produce answers and does not exploit generative models. In principle, we conjecture that a language generation model could be included in the future to generate new sentences starting from the pre-stored phrases in the Ontology and then in the DT. However, this is out of the scope of this work: the purpose of the comparison is to show that, even in presence of a more advanced approach for producing individual sentences, our solution for Dialogue Management may still have a significantly positive impact on user experience.For reasons due to the Covid-19 pandemic, participants could not take the tests with a robot, but they had to interact with their assigned conversational system  using their computer, by establishing a connection to a remote server in our laboratory. It is crucial to mention that the text-based user interface was identical for all the systems: therefore, participants assigned group 4 were not aware that they were interacting with a human, writing at a terminal, and participants assigned to group 5 were not aware that they were interacting with Replika .In total, each session included 20 exchanges  between the participant and the system.Immediately after the conversation session, participants were asked to fill in a questionnaire, divided into two parts.not Coherent and 7 means Coherent. The second part consisted of the SASSI questionnaire  is computed over all participants that interacted with it.We decided to use this widely known tool to measure the user experience during the conversation, after performing some research and comparing it with other tools commonly used for this purpose .Figure System Response Accuracy (9 items): it refers to the user perceptions of the system as accurate and therefore doing what they expect. This will relate to the system’s ability to correctly recognise the speech input, correctly interpret the meaning of the utterance, and then act appropriately;Likeability (9 items): it refers to the user ratings of the system as useful, pleasant, and friendly;Cognitive Demand (5 items): it refers to the perceived amount of effort needed to interact with the system and the feelings resulting from this effort;Annoyance (5 items): it refers to the extent to which users rate the system as repetitive, boring, irritating, and frustrating;Habitability (4 items): it refers to the extent to which the user knows what to do and knows what the system is doing;Speed (2 items): it refers to how quickly the system responds to user inputs.Controversial opinions about the usage of the SASSI can be found in [The published version has 34 items distributed across six scales, each item being scored with a 7-point Likert scale from Strongly Disagree to Strongly Agree: found in . It has found in  to more The first sheet contains all the answers to the first part of the questionnaire, concerning the Coherence of the replies, divided per group ;The second sheet contains all the answers to the second part of the questionnaire, divided per group  and per SASSI scale. For the Accuracy, Habitability and Speed scales, the scores assigned to negative statements  have been inverted; while for the Cognitive Demand, as a higher score has a negative meaning, we inverted the scores assigned to positive statements ;The third sheet contains a statistical analysis of all data. All datasets have been tested for normality both with the Shapiro-Wilk Test and with criteria based on the descriptive statistics  and computing the Pearson’s correlation index by pairing Coherence measures with the corresponding scores of each SASSI scale. The value of the correlation found when comparing Coherence with Accuracy turns out to be r=0.78; with Likeability r=0.69; with Cognitive Demand r=-0.45; with Annoyance r=-0.51; with Habitability r=0.56; with Speed r=-0.24. As expected, a high positive correlation is reported between Coherence and Accuracy and, to a minor extent, with Likeability and Habitability. A weaker, negative correlation is found with Cognitive Demand and Annoyance. An easily explainable small negative correlation with Speed is reported: system 4  obtains the highest Coherence scores but needs a longer time to reply, whereas system 3  obtains the lowest Coherence scores but has no delays when answering since no reasoning algorithms are involved.This section highlights and examines the major findings.Figure From Figure Results confirm that the additional cost for category extraction and matching (2) positively impacts the perceived Coherence with respect to using keywords only (1), and it is sufficient for beating Replika (5).Figure As for Coherence, the random system (3) is the worst one. An interesting result is that the system exploiting the keyword and category-based Dialogue Management algorithm (2) is the only one as accurate as a human (4) , other than being remarkably more accurate than all the other systems.The standard deviations shown in Fig. As it could be expected, from the histograms it is immediate to notice that group 3 has the lowest Likeability. As regards the other groups, the average Likeability scores present less prominent differences.Considering both the table in Fig. The standard deviations in Fig. As regards the averages, group 3 deviates from the others. This means that a higher cognitive effort is needed to interact with the system: this is since the replies of the system are random, hence the participants found it more difficult to easily interact with it.By looking at the p-values in Fig. As shown in Fig. Examining the table in Fig. From the histograms in Fig. Regarding the averages, the smallest one is that corresponding to group 3, which presents also the lowest average Habitability. This result was expected, as the random system had also the lowest Accuracy, Likeability, and Annoyance, and the highest Cognitive Demand, whose scores are likely not completely independent of one another.Considering the p-values in Fig. As it can be seen in Fig. Groups 4 and 5 report a higher standard deviation and a lower average. However, these results cannot be compared with those of the other tests. Since group 4 involves the unaware interaction with a human, the final score depends on the typing speed of the human. The same reasoning applies to group 5, which involved the unaware interaction with Replika: a human acted as an intermediary between the participant and Replika, by manually typing Replika’s replies which required some additional time.Considering both the table in Fig. The article proposes a novel system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. We compare two algorithms, based on the Ontology, for Dialogue Management that select the most appropriate conversation topics depending on the user input: the two versions differ in their computational cost and/or the need for third-party NLP services. Moreover, they implement slightly different strategies to ensure a conversation flow that captures the user intention to drive the conversation in specific directions, while avoiding purely reactive responses.Experiments performed with 100 volunteer participants, interacting with five different conversational systems (one of which is a human pretending to be a chatbot in a Turing-test fashion), support our intuitions about the importance of dialogue flow management, the improvements brought by the proposed solution based on the semantic category of the user sentence, as well as the positive correlations between Coherence in flow management and some scales of the SASSI (Subjective Assessment of Speech System Interfaces) questionnaire. Specifically, system (2), exploiting both keywords and categories for Dialogue Management, is statistically superior in Coherence and most SASSI scales  to Replika, one of the most popular chatbots worldwide. Since the SASSI is a widely known tool to measure the user experience during the conversation (and it positively correlates with our Coherence measure), we conclude that our approach may be a step forward towards properly managing the conversation flow to improve the user experience, thus supporting the aim of the paper. System (1), the one that exploits keywords only, is less computationally demanding as it does not require third-party services for category extraction and matching, and less performing than system (2): however, it can be a good “cheaper” alternative to produce an engaging conversation with the user. Indeed, it exhibits results not statistically discernible from those of Replika in Coherence, Accuracy, Likeability, Cognitive Demand, superior in Habitability and inferior in Annoyance.The approach presented in this article has obvious limitations since it relies on an Ontology of concepts and the related sentences to talk about such concepts, which needs to be manually encoded by experts. This issue has been addressed in subsequent work, which explored strategies for expanding the knowledge base at run-time during the interaction with the user .


Molecular testing can refine the risk of malignancy in cytologically indeterminate thyroid nodules and can reduce the need for diagnostic thyroidectomy. However, quality of life (QOL) in patients mananged with molecular testing is not well studied.We aimed to assess the QOL of patients undergoing surveillance after a benign molecular test result, or thyroidectomy after a suspicious molecular test result.This prospective longitudinal follow-up of the Effectiveness of Molecular Testing Techniques for Diagnosis of Indeterminate Thyroid Nodules randomized trial utilized the Thyroid-Related Patient-Reported Outcome, 39-item version (ThyPro-39) to assess the QOL of patients with indeterminate cytology on thyroid fine needle aspiration (FNA) biopsy. All patients underwent molecular testing at the time of initial FNA. A mixed-effect model was used to determine changes in QOL over time.n = 124) benign and 28% (n = 50) suspicious. ThyPro-39 scores of benign molecular test patients were unchanged from baseline  to 18 months of ultrasound surveillance. Baseline symptoms of goiter, anxiety, and depression were more severe for patients with suspicious compared with benign molecular test results. At a median of 8 months after thyroidectomy, suspicious molecular test patients reported improved symptoms of goiter, anxiety, and depression.Of 252 eligible patients, 174 completed the assessment (69% response rate). Molecular test results included 72% (A benign molecular test provides sustained QOL throughout ultrasound surveillance, without worsening anxiety or depression relating to the risk of malignancy. Definitive surgery results in improvement of QOL in patients with suspicious molecular tests. The use of medical imaging has made thyroid nodules increasingly prevalent in clinical settings.5Historically, indeterminate nodules were managed with repeat FNA or thyroid lobectomy for definitive diagnosis; however, the advent of molecular testing has allowed for greater diagnostic insights and de-escalation of surgical care.Thyroid cancer has a disproportionately negative effect on quality of life (QOL) compared with malignancies with a worse prognosis.In this longitudinal study, we aimed to measure the QOL of patients with indeterminate thyroid nodules who had benign molecular test results through the course of ultrasound surveillance. We hypothesized that the initial reassurance provided by a benign molecular test diagnosis would be sustained over time. We also compared the pre- and postoperative QOL of patients with indeterminate thyroid nodules and suspicious molecular test results who underwent thyroidectomy.All patients aged 18 years and older who underwent FNA biopsy with indeterminate cytology results throughout the University of California, Los Angeles (UCLA) Health System from August 2017 to January 2020 were eligible for enrollment. Those excluded were patients under the age of 18 years, those with concurrent thyroid malignancy, those who received nondiagnostic molecular test results, and non-English-speaking patients, due to the inability to provide our electronic QOL assessment in a language other than English. This study was approved by the UCLA Institutional Review Board.Biopsies were performed within UCLA Health by the patient’s endocrinologist, endocrine surgeon, or radiologist. At the time of the FNA, an additional sample was routinely collected for potential molecular testing and reflexively sent for all patients with indeterminate cytopathology .Variables extracted from the medical record included patient age, sex, thyroid-stimulating hormone (TSH) level, coexisting hypothyroidism (defined as TSH >4.7 mU/L), largest nodule diameter reported by cervical ultrasonography, Bethesda diagnostic category, molecular test performed and result, operation details , and observation duration (time zero was defined as day of FNA). No data were collected on subject’s race or ethnicity.Molecular test results typically took 2–3 weeks to return after FNA and were communicated to the patient by the treating physician within 1 week . The primary treating physician for most patients was their endocrinologist . The endocrinologist was generally the initial physician who notified the patient of their cytology and molecular test results, for both suspicious and benign cases. Following communication of the molecular test result and plan of treatment, patients were contacted by designated research personnel, either by email or telephone, to enroll in the study and complete electronic QOL assessments administered every 6 months from the time of molecular test diagnosis. Reminder emails and phone calls for incomplete QOL surveys were conducted up to five times at each time point. Survey responses were categorized into three groups based on survey completion time from FNA: baseline (0–4 months after FNA), early (4–12 months after FNA), and late (12–24 months after FNA). Survey responses were grouped into two molecular test result categories—benign or suspicious. As no significant differences in QOL were found between the two molecular tests, the QOL scale scores for GSC and Thyroseq v3 were combined for analysis.QOL assessment was continued after surgical intervention, when applicable. Patients with suspicious molecular test results who completed QOL surveys at baseline and at least 1 month after thyroidectomy were included, while those who underwent thyroidectomy prior to completing a baseline survey or underwent thyroidectomy with benign molecular tests were excluded from analysis.This study utilized the Thyroid-Related Patient-Reported Outcome, 39-item version (Thy-Pro-39) to capture a patient’s QOL. Thy-Pro-39 is a validated disease-specific questionnaire with 11 scales  and one single QoL composite score.17p-values were two-sided, and a p-value <0.05 was considered statistically significant.Descriptive data were generated from demographic and clinical information to characterize the study populations based on age, sex, nodule size, TSH level, Bethesda category, molecular test and result, and time to survey completion. An unstructured mixed-effect model was used for repeated measurement data to determine significant differences in QOL scores while accounting for the correlation between repeated measurement of each patient. This was performed for benign molecular test result patients at baseline, and early and late follow-up, and in suspicious molecular test patients at baseline, early follow-up, and postoperatively following thyroidectomy. Our model used all longitudinal data and adjusted for a fixed effect of time to survey completion  and molecular test result and a random component to account for correlations between repeated measurements within subjects. By using all available data and accommodating unbalanced or incomplete data, this analysis was more efficient than direct comparisons. Univariate logistic regression analyses were used to assess ThyPro-39 scores of benign molecular test patients from time of baseline survey completion to 18 months of follow-up to create a model of QOL development over time. All n = 67), were non-English speaking (n = 12), and had nondiagnostic molecular tests results (n = 31) or concurrent thyroid malignancy in another nodule (n = 8).Of 370 patients with indeterminate thyroid nodules who underwent molecular testing from August 2017 to January 2020, 118 patients were excluded and 252 patients were eligible for the study; 174/252 patients completed the ThyPro-39 questionnaire (69% response rate)—124 (71%) with benign molecular tests and 50 (29%) with suspicious molecular tests  Bethesda 3 nodules and 13.8% (n = 24) Bethesda 4 nodules. Afirma GSC was performed in 54% of patients and Thyroseq v3 in 46%. Benign molecular test patients were less likely to have Bethesda 4 cytology than suspicious molecular test patients . No differences were observed in age, sex, nodule size, molecular test performed or TSH level between groups (Table . The diagnostic performance of GSC and Thyroseq v3 has been published elsewhere.14The median (interquartile range [IQR]) age of all participants was 56 years (44–66) and 77% were female Table . The cytAmong the 124 patients with benign molecular test results, a baseline survey was completed in 102 patients at a median (IQR) of 2.0 months (1.3–3.8) after FNA, an early survey was completed in 71 patients at a median of 8.0 months (7.3–9.6) after FNA, and a late survey was completed in 52 patients at a median of 15.0 months (13.8–18.9) after FNA. Among the 50 patients with suspicious molecular test results, 45 completed a baseline survey at a median (IQR) of 1.7 months (1.3–2.8) after FNA. Most patients with suspicious molecular test results proceeded to thyroidectomy, thus follow-up surveys were included in the postoperative QOL analysis.At baseline, patients with suspicious versus benign molecular tests reported worse symptoms of goiter, anxiety, and depression Table . No QOL p = 0.048) but was this was not significant at late follow-up. As shown in Fig. On longitudinal assessment, no significant changes in symptoms of goiter, anxiety, depression, susceptibility, impact on social life, impact on daily life or appearance were observed in patients with benign molecular test results at early (relative to baseline) and late follow-up Table . Appearan = 45] vs. 11.1 ± 15.5 [n = 9], p = 0.04) , anxiety , depression , impaired social life , and impaired daily life , relative to baseline  reported improved postoperative symptoms of goiter  and impaired social life   reported improvement in postoperative symptoms of depression  and anxiety .Among the 45 suspicious molecular test patients who completed baseline QOL assessment, 36 (80%) underwent thyroidectomy at a median (IQR) of 3.2 months (2.1–4.3) after FNA. Postoperative surveys were completed in 35 patients (97.2%) comprising a total of 54 observations. At a median (IQR) of 7.6 months (5.4–12.4) after thyroidectomy, suspicious molecular test patients reported improved symptoms of goiter  and appearance  were worse in suspicious molecular test patients with benign pathology versus benign molecular test patients at early assessment. Depression  and appearance  remained more severe when compared with benign molecular test patients at late follow-up.Finally, we compared the postoperative QOL of patients with suspicious molecular tests and benign surgical pathology with those with benign molecular test results managed nonoperatively. We observed no significant differences in QOL when compared with benign molecular test patients at baseline. However, depression , which may be attributable to the overlap between a patient’s perception of appearance and their level of anxiety related to malignancy risk. For example, after initial diagnosis of an indeterminate nodule, a patient may potentially be more aware and concerned of the risk of malignancy, and with stable symptomatology and ultrasound findings over time, worry may diminish and reassurance gained. Although repeat FNA for Bethesda 3 indeterminate cytology may yield benign cytology in up to 42% of cases,Patients with suspicious versus benign molecular testing reported increased symptoms of goiter, anxiety, and depression following molecular test diagnosis. These findings confirm the results of a previous cross-sectional study assessing QOL in patients with indeterminate thyroid nodules, in which baseline ThyPro-39 scores for symptoms of goiter and depression were significantly worse in suspicious versus benign molecular test patients.23n = 9) and self-selection bias, as these patients had deferred recommended surgical management and instead preferred observation. Interestingly, suspicious molecular test patients pursuing nonoperative management reported improved symptoms of goiter and a trend suggested improved anxiety and depression at 7 months of follow-up. Such patients who favor observation are likely more worried about the possibility of having surgery for their indeterminate thyroid nodule than the risk of malignancy it harbors. This improvement in QOL may therefore reflect satisfaction with their treatment decision. Physician interpretation of suspicious molecular test results and subsequent patient counseling and communication likely impacts QOL and represents one area that can be targeted to improve intial patient worry surrounding a possible cancer diagnosis.Although the differences between benign and suspicious molecular test patients were no longer evident on early follow-up, this assessment is limited by the small sample size of suspicious molecular patients (Thyroid cancer patients experience symptom distress at the time of cytological diagnosis at a level comparable with general oncology patients, despite a generally good prognosis, and report disproportionately adverse physical, psychological, and social symptoms compared with patients with other malignancies.Attention to QOL outcomes in thyroid cancer patients has been increasingly relevant given the indolent nature of most thyroid cancers. The negative QOL outcomes experienced by patients with indeterminate nodules at the time of suspicious molecular test diagnosis suggest that interventions should be considered to address this distress, given the favorable prognosis of most indeterminate thyroid nodules and thyroid cancers. Such measures could include improved patient counseling and education, social work consultation, and other forms of interdisciplinary care. Moreover, recent studies on molecular marker testing show improvements in diagnostic performance over prior versions.Our study has several potential limitations. First, we were unable to evaluate the QOL effect of an indeterminate cytology result itself, as all indeterminate samples were reflexively sent for molecular testing. We felt that the inclusion of nondiagnostic molecular test patients was not valid as most of these patients underwent repeat molecular testing. Second, we were unable to assess QOL prior to FNA biopsy, which would evaluate the initial QOL of patients with a thyroid nodule and determine the subsequent impact of molecular test results on QOL. Third, we did not have specific data on patient’s race, ethnicity, socioeconomic status, or pre-existing conditions, including anxiety and depression, which may have been associated with baseline QOL. Third, we do not have surveillance data for benign molecular test patients who may have experienced nodule progression that could have impacted QOL. However, based on our previous results from ultrasound surveillance over a median follow-up of 27 months, 84% of nodules remained stable in size and appearance,We observed that benign molecular test patients reported similar QOL from the time of molecular test diagnosis through 18 months of follow-up. This finding suggests that a benign molecular test provides patients with sustained reassurance that the risk of malignancy is low. Definitive surgery resulted in improvement of QOL in patients with suspicious molecular test results.


A larger dihedral angle of anisotropy is an important point limiting the charge mobility in the herringbone arrangement. It is hoped that the correlation results between the crystal structure and mobility can assist the experimental study and provide an effective way to improve the photoelectric conversion efficiency of the organic semiconductor devices and multiple basis for multiscale material system characterization and material information.Charge mobility is an essential factor of organic crystalline materials. Although many investigators have made important progress, the exact relationship between the crystal structure and carrier mobility remains to be clarified. Fortunately, a series of bis-1,3,4-oxadiazole derivatives have been successfully prepared and reported. They have similar main molecular fragments but different crystal packing modes, which provide an ideal research objective for studying the effect of molecular packing on charge mobility in organic photoelectric conversion systems. In this work, the charge mobilities of these molecules are systematically evaluated from the perspective of first-principles calculation, and the effect of a molecular overlap on orbital overlap integral and final charge carrier mobility is fully discussed. It can be seen that the small intermolecular distance (less than 6 Å) is the decisive factor to achieve high electron mobility in  Compared with inorganic materials, organic materials in our daily life have unique advantages in terms of price, ease of property, fine-tuning, and flexibility, etc. The structure of organic materials is complicated, and there are two types of organic materials in general: crystalline organic materials and amorphous organic materials. However, even for the simplest single crystalline materials, it is difficult to find a precise connection between the crystal structures and their micromechanisms such as anisotropic practical transport, structural deformation, and mechanical properties of anisotropy . There aπ–π stacking, CH–π, and anion–π+/cation–π− interactions play significant roles in many aspects  can improve the transport performance of organic semiconductors   has been chosen, which has been synthesized by Wang et al. . The molibration . BecauseTheoretical calculation of the electronic structure of organic semiconductor system is an effective means to analyze the micro-carrier mobility. In this article, we establish a causal relationship between charge mobilities and stacking modes by using theoretical simulation to parameterize the intrinsic properties of organic materials to have a full-dimensional and multi-faceted understanding. And based on these research studies, we find what kind of crystal structure is most conducive to charge transfer and explain the reason. We anticipate that after this study about more comprehensive material informatics, the interpretation of structure–activity relationships in organic crystal materials will be advanced and the design of new materials will be greatly promoted.Theoretical research on charge mobility is often based on the Marcus theory, but the high-frequency modes which may also play considerable role in charge mobility are neglected in this approach. In this study, the tunneling-enabled hopping models are employed to describe the charge transport, which has showed great advantages in the high-frequency regime. In this model, each hopping event is viewed as a non-adiabatic electron transfer reaction; the charge transfer (for electron) between two adjacent molecules follows the reaction M + M-→M- + M, where M is the molecule undergoing the electron transfer. The quantum mechanical charge transfer rate from one molecule to another under the perturbation theory and the displaced harmonic oscillator approximation can be derived from Fermi’s golden rule. The rule states thatUnder the displaced harmonic oscillator approximation , Eq. 1 cHere, From Here,  program  with sui program  and 6–31 program . The orb program . General neutral  to the cHere, The diffusion coefficient π stacking and herringbone arrangement and then discussed them separately. Firstly, to describe the π stacking of this series of BOXD complexes, slip distance between the nearest adjacent molecules along the direction of x, y, and z is needed. The molecular long axis (y) is defined as a line through the two para-C in terminal benzene rings; in the meanwhile, another line in the molecular plane that is also perpendicular to the molecular long axis can be defined as the molecular short axis (x); besides, the π stacking direction (z) is perpendicular to the x-y plane. Although the BOXD-D crystal is full of π stacking arrangements, herringbone arrangement also exist in the structure of other BOXD derivatives which cannot be simply defined by the slip distance. In this case, the angle between two molecular long axes Many unique physical properties of organic crystalline materials are resulted from their long ranged order—periodic structure. Because of its well-defined molecular structure, molecular packing, and intermolecular interaction, single crystal is considered as an ideal model to investigate the relationship between the properties and structures. To conveniently and intuitively describe the spatial relationship between the reference molecule and its neighbors in single crystal, we have divided the neighbors into π–π interactions in between. As present in π–π interactions is similar at 3.43 Å (Δz). Molecule 2 and molecule 4 stack with similar displacement along the molecular long and short axes are shown in There are four kinds of molecular structures with distinct torsion angles in a BOXD-m crystal. BOXD-m also exhibits layered assembly structure features, and each molecular layer has two kinds of molecules. Molecule 1 (green) and molecule 2 (blue) are in the same molecular layer (a), while molecule 3 (red) and molecule 4 (yellow) are in another layer (b). The layers are arranged in the a-b-b manner with intermolecular π stacking slip distance between BOXD-o-1 along the long axis (Δy) is 0.40 Å, distance along the short axis is 1.72 Å (Δx), and the distance from π–π interactions is 3.52 Å (Δz). In this crystal structure, herringbone arrangement also can be found in different layers. The distance from the nearest adjacent molecules is 10.64 Å, the long axis of these two molecules is nearly perpendicular to each other which is 89.5°, and the dihedral angle of two molecular planes is 27.6° (π stacking with a contact distance of 3.37 Å (Δz), and displacement of the nearest molecules in π stacking along the molecular long axis is much longer than it is in BOXD-o-1, which is 5.75 Å (Δy), and the slip distance along the molecular short axis is about 0.81 Å (Δx). The long axis angle of primary herringbone arrangement is 57.2°, and the dihedral angle of two molecule planes is about 61.7°, with a distance of two molecules being 9.32 Å  and 1.11 Å (Δx), respectively, and the contact distance is at 3.38 Å (Δz). In the herringbone arrangement, the long axis angle is about 35.6°, which is much smaller than other packing modes, but the dihedral angle is as large as 67.8° than other molecules  and short axis (Δx), and π–π contact distances (Δz) are measured as 5.45 Å, 0.67 Å, and 3.32 Å (Δz), respectively. BOXD-D features a layered assembly structure . As for the primary herringbone arrangement, the long axis angle is 75.0° and the dihedral angle is 22.5° with a 5.7 Å intermolecular distance  allows the molecular orbitals to couple strongly to each other. Under this circumstance, greater overlap and stronger coupling will result in larger transfer integral. On the other hand, if the bonding orbitals overlap with the antibonding orbitals because of the intermolecular slippage like path 2 of BOXD-D and path 2 of BOXD-T, the transfer integrals will be greatly reduced, even smaller than path 1 of BOXD-p and path 1 of BOXD-D with much less overlap. The other distribution mode is that the LUMOs are located on one of the two molecules because the Coulomb coupling value is negative. With this distribution, the electron transport between the two molecules becomes more difficult. In path 7 of BOXD-m and path 3 of BOXD-o-2, the transfer integral is going to be small without the overlap between the molecular orbitals.Here, one should notice that the difference in the transfer integral of electron transfer can be explained through the intermolecular direction and the molecular orbitals, and it needs to be discussed separately for π stacking (It can also be noticed that the transfer integrals of herringbone arrangement are lower than those in stacking . Taking π–π interactions are most obvious interaction, and n–π interactions can also be considered. In addition, the location of interactions, that is, the orbital overlap direction is shown in π stacking and herringbone arrangement. Attention to the orbital overlap integral, the similar tendency can also be found, except p–p1, o2–p3, and o2–p1. These three pathways have lower transfer integral, although they can achieve higher orbital overlap integral than others. A larger molecular overlap can be found in these pathways than the paths of D–p2 and T–p2. In this case, large orbital overlap integral is essential for electron transfer. As orbital overlap integral is reduced to orders of 10−3, the molecular overlap begins to show its negative effects to limit electron transfer.In order to obtain more information about the transfer integral, a deeper insight of interaction of the LUMO should also be evaluated. The 2V−1s−1, which is contributed by BOXD-m with the largest average mobility of 1.43 cm2V−1s−1. After that, BOXD-D and BOXD-o2 also have good performance, and their average mobilities are 0.28 cm2V−1s−1 and 0.34 cm2V−1s−1, respectively. The average mobility of BOXD-o1 and BOXD-p are relatively small—3.55 -2 cm2V−1s−1 and 2.39 -2 cm2V−1s−1. The calculated mobility of BOXD-T is 0 cm2V−1s−1, it seems like this structure cannot be used as a hole transfer material. But as shown in A dramatic difference can be found in the calculation of hole transfer in contrast to electron transfer. The largest mobility in hole transport can even achieve 2.15 cmJust like the analysis on the electron mobility, reorganization energy and the transfer integral should be considered in hole transport. In order to make clear the relationship between reorganization energies and normal-mode frequencies, their correspondences are plotted in To achieve a better understanding of the difference in reorganization energy, it should be a good choice to examine the difference of electron density. π stacking, there are two general kinds of intermolecular stacking, the one is that the HOMO orbital of each monomer is still evenly distributed within the monomer, which may usually be associated with a small long-axis slip distance. In this case, the overlap of the HOMOs is proportional to the transfer integral between the molecules; the greater the overlap the molecular orbital overlap makes, electrons are more likely to be transferred between molecules, which can explain the change in transfer integrals. The path 1 of BOXD-m has the largest overlap and also the largest transfer integral, and as the overlaps decrease in the path 5 of BOXD-m and path 1 of BOXD-o-1, the transfer integral decreases accordingly. The transfer integral of BOXD-p will be smaller because of the larger molecular slip distance along with the smaller orbital overlap. In BOXD-T, there is no overlap in molecules; thus, the transfer integral is almost 0. The other stacking way is usually accompanied by large long-axis distance, which will concentrate the molecular orbitals on the overlapping part of the two molecules. It would be advantageous to separate the electron and the hole as it would also be difficult for the hole to recombine with the electron in the transfer process and eventually increase the transfer integral. But if the long-axis slip distance became too large, the promotion effect of the charge transfer which is obtained by the excellent electron and hole separation cannot overcome the disadvantages from the small overlap and eventually decrease the transfer integral. Therefore, appropriate molecular long-axis slip is favourable for hole transport, but the transfer integral will be greatly reduced if the slip is too large in π stacking.Another crucial factor—transfer integral also have drastic difference compared to that in electron mobility. The transfer integral and the intermolecular distance of the primary hole transport path is also shown in π stacking, the transfer integral will be reduced due to the more concentrated orbital distribution and orbital overlap. While in BOXD-o-1, BOXD-p, and BOXD-T, the HOMOs are located in one of these pair of two molecules at the effect of Coulomb coupling. Due to the lack of the molecular orbital overlap, the transfer integral decreases obviously. At the same time, the increase in the dihedral angle has a negative effect on the transfer integral. Increasing the dihedral angle can also be seemed as another way to reduce the molecular overlap, making it difficult for hole transfer. Thus, dihedral angles can fundamentally affect the overlap of molecules and their orbitals to change the herringbone transfer integral. The difference of transfer integral between path 1 and path 2 in BOXD-o-2 can be found in hole mobility with the exactly opposite result. That is because of the distribution of HOMOs which is also quite opposite to that of LUMOs.Hole transfer integrals onto herringbone arrangement also show great difference from those in electron transport . Compariπ stacking and T–p1 of herringbone arrangement, larger orbital overlap integrals and smaller transfer integrals than o1–p1 and o2–p1 appear due to the disadvantage of molecular overlap.Orbital overlap integral of every primary hole transfer pathways is also evaluated . The samπ-packing and herringbone arrangement for anisotropic electron and hole mobility. Intermolecular distances are the determining effect of transfer integral in π stacking. For the electron transfer process, the shorter intermolecular distance is better because the molecular orbital overlap is beneficial to the increase in transfer integral. While the overlap between the bonding and antibonding orbital greatly limits the integral when intermolecular distances become larger. Uneven distribution of molecular orbitals between molecules would also have a negative effect on this integral. However, the situation has difference in the hole transfer process. If the molecular orbitals are symmetrically distributed over each molecule, larger intermolecular distance will be detrimental to the transfer integral, which is same as electron transfer. But with the increase in the long axis critical slip distance, the transfer integral increases first and then decreases due to the separation of the electron and hole. The transfer integrals in herringbone arrangement which are usually smaller than those of π stacking are mainly controlled by the dihedral angle, except that the unique structure of BOXD-o-2 leads to its different transfer integrals. The transfer integral will decrease with the increase in the dihedral angle. According to π stacking, but it is also possible to achieve better mobility by appropriately increasing the distance in the hole transfer process. With regard to herringbone arrangement, the mobilities of parallel herringbone arrangement can even be comparable to that of π stacking; dihedral angles of more than 25° usually have extremely adverse effects on charge transfer. On the other hand, excessive structural relaxation also negatively impacted to attaining larger mobility. The almost nonexistent mobility of BOXD-T in hole transfer is ascribed to the combined influence of huge reorganization and small transfer integral. Actually, the different orientations of electron and hole mobilities in three dimensions can effectively inhibit or avoid carrier recombination. According to the results in Based on multiple model and high-precision first-principles computational analysis of dense packing of organic molecules, we finally reveal the effects of crystal structures with


The history of antimicrobial resistance (AMR) evolution and the diversity of the environmental resistome indicate that AMR is an ancient natural phenomenon. Acquired resistance is a public health concern influenced by the anthropogenic use of antibiotics, leading to the selection of resistant genes. Data show that AMR is spreading globally at different rates, outpacing all efforts to mitigate this crisis. The search for new antibiotic classes is one of the key strategies in the fight against AMR. Since the 1980s, newly marketed antibiotics were either modifications or improvements of known molecules. The World Health Organization (WHO) describes the current pipeline as bleak, and warns about the scarcity of new leads. A quantitative and qualitative analysis of the pre-clinical and clinical pipeline indicates that few antibiotics may reach the market in a few years, predominantly not those that fit the innovative requirements to tackle the challenging spread of AMR. Diversity and innovation are the mainstays to cope with the rapid evolution of AMR. The discovery and development of antibiotics must address resistance to old and novel antibiotics. Here, we review the history and challenges of antibiotics discovery and describe different innovative new leads mechanisms expected to replenish the pipeline, while maintaining a promising possibility to shift the chase and the race between the spread of AMR, preserving antibiotic effectiveness, and meeting innovative leads requirements. A sharp decline in the introduction of newer antibiotics and the worldwide emergence of antimicrobial resistance (AMR), combined with the current COVID-19 pandemic, point to the urgency for action plans for the better treatment of infectious microorganisms . MaintaiAMR is an ancient natural widespread phenomenon that precedes humanity ,21. DiffResistance is the inherited ability of a bacterium to grow when exposed to high concentrations of antibiotics . AntibioTolerance by slow growth that is either inherited or not, occurring at a steady state.Tolerance by lag that is a transient state induced by starvation or stress.Tolerance is the ability of a bacterium to survive exposure to increased antibiotic concentrations without modifications of the MIC, as a result of slowing down essential bacterial processes ,39. Tole99) is a technique used to measure tolerance, and is defined as the time needed to kill 99% of the culture -N-hydroxy-2-(tetrahydro-2H-pyran-4-yl)acetamide), which is a sulfonamide derivative . The LF,E. coli, Salmonella, Yersinia, Haemophilus, Pseudomonas, and Klebsiella. Agents targeting bacterial adherence through the inhibition of pili not only deny access to host tissues, but they also promote rapid bacterial clearance and circumvent the release and translocation of tissue-damaging factors [E. coli. Hemagglutination mediated by either type 1 or type P pili, adherence to bladder cells, and biofilm formation mediated by type 1 pili were all reduced by approximately 90% in laboratory and clinical isolates. This represented promising evidence for developing drugs that function by targeting pili [Bacterial adhesion is an important step in pathogenesis, and is required for tissue colonization, where the next step of tissue destruction by enzymes and toxins takes place . In fact factors . A grouping pili .Two-component systems (TCS) for signal transduction are primary pathways by which bacteria adapt to the external environment, and they serve an important role in regulating virulent gene expression, cell wall synthesis, biofilm formation, and bacterial activity . TCS allSalmonella, and restores sensitivity to the last-resort antibiotic, colistin. Cellular-based and mouse models of infection demonstrate that dephostatin attenuates Salmonella virulence both in vitro and in vivo, through the perturbation of its regulatory networks [S. aureus, the small-molecule chemical savirin was capable of blocking the transcriptional function of the TCS Agr-CA, affecting virulence through the reduction of the quorum sensing ability, but not survival, while savarin had no impact on the commensal Staphylococcus epidermidis [P. aeruginosa, benzothiazole-based HK inhibitors that perturb multiple virulence pathways were found to significantly reduce the level of toxic metabolites of this organism that are involved in quorum-sensing and redox-balancing mechanisms. The inhibitors also decrease the ability of P. aeruginosa to undergo swarming and attachment to surfaces, probably by influencing motility appendages [E. coli (AIEC) [Most small-molecule inhibitors of TCSs target the HK. Several HK inhibitors have broad-spectrum activity and inhibit both essential and nonessential TCS. A small number of recently reported compounds are targeted to the RR, allowing for greater direct control over gene expression . As suchnetworks . In S. adermidis . Anotherdermidis . In P. apendages . Anotherpendages . Recentli (AIEC) . Such inAntivirulence therapies represent a strong, non-traditional trend towards the discovery and development of new antimicrobial agents; however, challenges remain to be addressed. Virulence factors are often species or even strain-specific, and variably conserved among a bacterial species. This makes their development specific for targeting particular pathogens. Furthermore, the expression of virulence factors may depend on environmental conditions, the site of infection, or the time course of a pathophysiologic process. Such complex biological variability and narrow spectrum constitute major challenges to translating the early discovery of virulence factors for clinical use .Genome mining refers to the bioinformatics investigation used to detect the biosynthetic pathway of bioactive natural products, as well as their possible functional and chemical interactions . It is aStreptomyces sp. YIM 130001 from a tropical rainforest in China displayed antibacterial activity against Bacillus subtilis. The draft genome sequence of this isolate strain revealed 18 putative biosynthetic gene clusters (BGCs) for secondary metabolites. An analysis of these gene clusters led to the identification of new thiopeptide antibiotic, geninthiocin B, with bioactivity against B. subtilis. A combined analysis of the genome sequencing data and metabolite profiling led to the identification of the geninthiocin B gene cluster, confirming the power of the genome mining approach in the discovery of natural products with antibacterial activity [P. aeruginosa and colistin-resistant E. coli, and an apparently low risk of resistance. The two peptides showed efficacy against E. coli in a mouse thigh infection model, contributing to a novel pathway in the discovery and development of antibiotics against Gram-negative pathogens.For example, a new lichen-associating activity . Li and activity  analyzedHumans host trillions of micro-organisms in the skin, gut, and airways. These micro-organisms exert regulatory functions, are in a continuous dialogue with intestinal epithelia, influence energy production, break down nutrients, digest vitamins, and may interfere with the pathophysiology of diabetes and obesity . Short-tS. aureus [K. pneumoniae clinical strains. These antibodies promoted bacterial killing through several extracellular and intracellular processes, and prevented the spread of infection in mice from the lungs to distal organs. It is promising that such antibodies can ultimately treat or protect patients infected or at risk of infection by this multidrug-resistant bacterium [Despite the explosion in monoclonal antibody therapies developed for oncologic and rheumatic indications, the therapeutic potential of this drug class for treating multidrug-resistant infections is yet to be examined . Given t. aureus , and a m. aureus . Likewisacterium . It is eacterium .It is worth mentioning that, in addition to the above, the preclinical antibiotic pipeline holds 135 projects on direct-acting small molecules that represent new classes, new targets, or new mechanisms of action, with a vast number of pathogen-specific and adjunctive approaches not witnessed before in antibiotic discovery, as reported recently in 2020 . The discovery and development of new antibiotics take at least ten years and cost more than USD 1 billion . In paraThe challenges for antibiotic discovery are primarily financial, complicated by the scientific and regulatory hurdles ,248. TheThe other huddle is related to strict regulations for clinical trials. Some drugs with improved activity against resistant pathogens such as oritavancin were pushed back due to the inadequacy in trials. The pharmacological and toxicological criteria are also challenging in repurposing original drugs and their starting material .A lot remains to be investigated to tackle the future of AMR, augment antibiotic discovery, and enlarge the armamentarium of agents used to combat MDR pathogens. The different lessons learned from the golden age of antibiotic discovery, changes in AMR thereafter, and consideration of the current recent advances in genome editing, gene regulation, and systems biology, can all inspire a wide variety of innovative antibiotic discovery projects. Approaches including nanoparticles, immunotherapy, antisense RNA, resistance modulation, and removal of drug-resistance plasmids are on the rise. Moreover, antibiotic resistance breakers that may or may not have direct antibacterial action and can either be co-administered with or conjugated to other failing antibiotics, are being studied. In this regard, compounds that are used to reverse AMR like modifying-enzyme inhibitors, membrane permeabilisers and efflux pump inhibitors are under investigation. Other possible future avenues to combat AMR include antibiotic hybridization, harvesting, and modifying natural antimicrobial peptides from eukaryote and prokaryote organisms . AlthougA throwback on the history of antibiotics and the evolution of resistance shows that, in a matter of about one century, antibiotics have drastically changed modern medicine and increased human lifespan, however, have been also substantially hit by the current AMR crisis. This is a multifactorial issue of microbial evolution to escape antibiotics, gradual decline in discovery and development of antibiotics, and many economic and societal challenges. The race between AMR and antibiotic discovery shall continue, and research needs to chase, at higher speeds, and with more prominence an intensity, augmented solutions to combat AMR. While the global efforts to mobilize attention towards AMR have been huge, the call today is to further invest in basic, translational, and clinical research targeting AMR, and to optimize the application of advanced knowledge and expertise to target this public health concern in humans and the environment.