The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthetic pathways for both NPs and NP-like compounds. First, a single-step bio-retrosynthesis prediction model is trained using both general organic and biosynthetic reactions through end-to-end transformer neural networks. Based on this model, plausible biosynthetic pathways can be efficiently sampled through an AND-OR tree-based planning algorithm from iterative multi-step bio-retrosynthetic routes. Extensive evaluations reveal that BioNavi-NP can identify biosynthetic pathways for 90.2% of 368 test compounds and recover the reported building blocks as in the test set for 72.8%, 1.7 times more accurate than existing conventional rule-based approaches. The model is further shown to identify biologically plausible pathways for complex NPs collected from the recent literature. The toolkit as well as the curated datasets and learned models are freely available to facilitate the elucidation and reconstruction of the biosynthetic pathways for NPs. The complete biosynthetic pathway from most natural products (NPs) are unknown. Here, the authors report BioNavi-NP, a computational toolkit for bio-retrosynthetic pathway elucidation or reconstruction for both NPs and NP-like compounds. Remarkably, this vast chemical space of NPs is reachable from a few dozen, simple building blocks4. According to the classes of those building blocks, there are correspondingly four well-known biosynthetic pathways for major classes of NPs and their hybrids, including: (1) the AA/MA  pathway that produces fatty acids, phenols, and polyketides; (2) the MVA/MEP  pathway that generates terpenoids and steroids; (3) the CA/SA (cinnamic acid or shikimic acid) pathway that yields flavonoids, phenylpropanoids, lignans, and coumarins; and (4) the AAs (amino acids) pathway that constructs alkaloids and peptides including ribosomally synthesized and posttranslational modified peptides (RiPPs) and non-ribosomal peptide (NRPs). Unfortunately, as shown in Fig. 5, KEGG6 and MetaNetX7). That is, complete biosynthetic pathways including all intermediates are not established for most of the hundreds of thousands of known NPs. Accordingly, there is a strong desire to reveal the biosynthetic pathways from essential building blocks to target NPs (namely the native NPs biogenesis).To date, more than 300,000 natural products (NPs) have been discovered and catalogued in libraries such as Dictionary of Natural Products8. As a result, NPs play a significant role in drug discovery: more than 60% of FDA-proved small molecule drugs are NPs or their derivatives9. NPs are often the best option for seeking novel bioactive templates in human health, as many of them are critical factors for regulating intrinsic biofunctions, especially in plants11. However, obtaining commercially-relevant quantities of NPs can be a major obstacle to their therapeutic translation, since NPs are usually expressed in low abundances in natural sources, and thus conventional extraction approaches are inefficient and environmentally unfriendly in most cases. Meanwhile, many highly valuable NPs have complicated structures, making total synthesis difficult and time-consuming. As famously exemplified by the heterologous biosynthesis of the arteannuinic acid12, biosynthesis and semi-synthesis of complex natural products have become more popular and influential strategies in the past decade because of the theoretical advantages of lower cost and higher yield. Nevertheless, it remains challenging to reconstruct a heterologous biosynthetic pathway from its native pathway. Therefore, computer-aided tools are needed for the retro-biosynthesis analysis of target NPs, especially for the exploration of non-native biosynthetic pathways.NPs have been noted to exhibit larger structural diversity than fully synthetic molecules and exist in a distinct chemical space15, which can be roughly divided into two categories of methods: knowledge-based and rule-based approaches (Supplementary Table 5 and KEGG6) and rank the suggested routes through scoring functions such as chemical similarity17 and chassis18. For complex NPs, these methods are often not applicable when the reactions of their biosynthetic pathways are not included in those databases. The template- or rule-based models  match the query molecule to a collection of generalized reaction rules, i.e., subgraph patterns of molecules that highlight changes during biochemical reactions. The rules are either summarized manually by experts24 or extracted automatically from the reaction databases25. Although rule-based methods have led to promising results in retro-biosynthesis, a few challenges remain. First, their ways to formulate expert-approved rules are complicated and time-consuming25. Second, the degree of generality/specificity of curated rules may lead to invalid or incomplete proposals26. Third, they are fundamentally unable to predict reactions beyond the rule databases27.To date, many efforts have been made in the field of retro-biosynthesis28) as input into sequential models such as recurrent neural networks29 and transformer neural networks30. Such techniques have been utilized to predict the products of both organic32, and enzymatic reactions34 by giving reacting substrates as input, or the reverse for retrosynthesis prediction task36. These rule-free models have shown better performance and greater generalization potential than rule-based models in many cases35. Based on the single-step retrosynthesis prediction, the retrosynthetic pathways can be planned through searching techniques , but MCTS-based methods38 are of limited efficiency due to the required expensive online reward estimation. More recently, Chen et al.39 reported a deep learning-guided AND-OR tree-based searching algorithm called Retro*, and demonstrated improved planning efficiency and solution quality. Nevertheless, multi-step planning algorithms have not yet been applied to NPs retro-biosynthetic planning, mainly due to its much less available data, greater number of steps, and higher branching ratios in the biosynthetic pathways.Recently, the development of deep learning methods has made it possible to predict reactions without rules, where molecules could be represented as strings  through the deep learning-guided AND-OR tree-based searching algorithm, which can solve the combinatorial number of options caused by the branches of the synthetic pathway. As a result, BioNavi-NP successfully identify biosynthetic pathways for 90.2% of 368 test compounds and recover the reported building blocks as in the test set for 72.8%, demonstrating its potential for bio-retrosynthetic pathway elucidation or reconstruction. For each biosynthetic step in the multi-step bio-retrosynthetic routes, we further evaluate the plausible enzymes through enzyme prediction tools, Selenzyme42 and E-zyme 243. All outputs of the BioNavi-NP can be visualized by an interactive website (http://biopathnavi.qmclab.com/), where the predicted reaction pathways are sorted by the computational cost, length, and organism-specific enzyme.Herein, we present BioNavi-NP as a practical tool to propose NP biosynthetic pathways from simple building blocks in an optimal fashion. As depicted in Fig. 44, we evaluated the performance on the test set using top-n accuracies, defined as the percentages of correct instances among top-n predicted precursors. Considering the complexity of biosynthesis, we further expanded the training set by retrieving 62370 organic reactions similar to these biochemical reactions from USPTO45, the largest organic chemical reaction library available. This strategy was inspired by transfer learning40, where a sufficient amount of relevant data helps to improve model robustness by learning general patterns and avoiding over-fitting. The larger data set of 60 K natural product-like reactions is named USPTO_NPL (see Methods for more details).Multi-step retro-biosynthesis planning is based on the backward search performed through iterative single-step retrosynthesis predictions. Therefore, it is critical to achieve a reliable prediction of single-step precursors at each step. Our first task is to compare various architectures and training modes to determine an optimal model. To train our model, we first curated a biosynthesis data set from the public database called BioChem (see Methods), containing 33710 unique pairs of precursors and metabolites. From the dataset, we randomly selected 1000 pairs as the test set, 1000 pairs as the validation set, and the remaining as the training set. Following the previous retrosynthesis works41 can reduce the variance of different models’ random initializations and improve robustness.As summarized in Table 20, with an increase by up to 1.1% and 18.5% in terms of top-1 and 10 accuracies, respectively. This result demonstrated the power of the deep learning-based methods for the prediction of biosynthetic processes, while the higher accuracy of BioChem + USPTO_NPL than BioChem + USPTO_NPL (ses2seq) demonstrated the value of the attention mechanism by transformer. Hereafter, we would use the BioChem + USPTO_NPL (ensemble) as the basic single-step prediction model if not specially mentioned.Table 20 was set to 1000 iterations and 10 expansions following its default settings. Note that the number of expansion represents the top-N metabolites that the model will predict in every single step, i.e., top-N in Table Next, we investigated the performance of different multi-step planning strategies. We integrated the above trained single-step prediction ensemble model to navigate the multi-step bio-retrosynthesis planning and named it BioNavi-NP. To evaluate the searching performance, we randomly selected 368 diverse NPs with complete biosynthetic pathways from the BioChem dataset, and compared different methods in terms of their abilities to: (i) predict biosynthesis routes that terminate in allowable building blocks (success rate or solution rate), (ii) to correctly find the reported pathway exactly as it appears in the knowledge base (hit rate of pathways), and (iii) to correctly recover the building blocks used in the known biosynthetic pathway (hit rate of building blocks). We introduced the hit rate of building blocks because the pathway of ground truth is not necessarily unique. There may be multiple pathways between a natural product and its building blocks. Even if a candidate pathway is not the ground truth, the candidate is also meaningful as a non-native biosynthetic pathway or an inspiration for pathway reconstruction and design. To ensure a fair comparison, all deep learning models were limited to 100 iterations and 10 expansions, while RetroPathRL20 (52.7%). Meanwhile, BioNavi-NP achieved 56.0% and 24.7% for the hit rates of building blocks and pathways, remarkably outperforming RetroPathRL (4.8% and 3.8%), respectively. It should be noted that RetroPathRL contains the reaction rules extracted from MetaNetX7, while all the internal test NPs were included in MetaNetX. When changing the searching algorithm to MCTS, BioNavi-NP (MCTS) achieved a substantially lower success rate of 34.8%, indicating the importance of searching strategy to manage the highly-branched multi-step search. As users may prefer well-known or user-specific building blocks in practice, we set the building blocks of ground truth as the user-defined building blocks (UDBs), and terminated predictions only with the UDBs. As expected, the BioNavi-NP_UDB model increased both the hit rates of building blocks and pathways  while decreased the success rate (74.7%). The same trend was observed between RetroPathRL and RetroPathRL_UDB.As summarized in Table To guide the reconstruction of the biosynthetic pathway, it is important to explore more than one pathway for each target NPs. Therefore, in addition to the abovementioned hit rate of pathways, we also counted the average number of predicted pathways as a direct indicator for the tool’s practical use. When selecting the output option as top-5  from recent publications that did not appear in the training set or internal test set. Out of these, 22 cases successfully found at least one candidate pathway with a success rate of 88%, roughly the same as the 90.2% in the internal test. For the 3 remaining cases, incomplete results were still outputted for analysis. 17 cases had correctly identified at least one building block with the hit rate of building blocks of 68%, higher than the 56% in the internal test  and the pathways (hit rate of pathways). For a fair comparison, we used the same building block library (extended library) containing 437 available precursor metabolites extracted from iML1515 model46, as used in RetroPathRL. The parameters of BioNavi-NP were set to a maximum of 100 iterations and 10 expansions. As shown in Supplementary Table For a direct comparison with existing works, we tested BioNavi-NP on two benchmark datasets (namely LASER and Golden dataset) used by RetroPathRL47 did, only the structure of the target molecule is strictly required, but the default settings and list of building block can be modified as needed. The total number of output pathways is influenced by several options, especially the “pathway_top_k” (default is top-10). The length of the pathways is affected by the “Max_depth” (default is 10). One can increase the number to a maximum of 20 upon request. These default settings  and colletorin D acid (intermediate 4) to lead the fourth and fifth candidate pathways, respectively, where the fourth candidate pathway was ultimately traced back to the building block farnesyl diphosphate (3), while the fifth candidate way was a hybrid biosynthesis style originated from the acyl CoA (5), malonyl CoA (6), and dimethylallyl diphosphate (7). Both the fourth and fifth candidates are confirmed biosynthetic pathways according to the previous studies53. This case shows us that BioNavi-NP is capable of dealing with complex structures including those derived from the hybrid pathway and to trace them back to essential building blocks.Sterhirsutin J is a sesquiterpenoid derivative firstly isolated from the culture of 54. Herein using BioNavi-NP, the predicted third candidate pathway belongs to one of the lysine (8) degradation pathways55, and the seventh one is highly similar to an experimentally reconstructed pathway for glutaconate production56, both of which are already existed in our training set, so it is not surprising that BioNavi-NP can predict those two pathways which have been constructed in E. coli for glutarate production58. The fourth candidate is not contained in our training set, and it takes a successive decarboxylation strategy from homoisocitrate (9), which is predicted to be originating from the basic building block pyruvate (10). Interestingly, Wang et al.59 recently established a glutarate biosynthetic pathway from α-ketoglutarate by incorporation of a “+1” carbon chain extension and α-keto acid decarboxylation, which covers the fourth candidate pathway predicted herein. This case study is a typical example to show the capability of BioNavi-NP in exploring the biosynthetic pathways beyond the known biogenesis. Thus, it is useful for biosynthetic pathways redesign.Glutarate  is an important raw material for the chemical industry, but biobased production of glutarate suffers from low titers62 to aid experimental biosynthesis.Herein, we proposed a practical retro-biosynthesis protocol for navigating biosynthetic pathways to complex NPs from simple building blocks. In contrast to rule-based models, BioNavi-NP is a fully data-driven model that is constructed based on curated biosynthetic and organic reaction data without the need for cumbersome or heuristic extraction of reaction templates. Comprehensive evaluations on internal and external test sets demonstrate that our method achieves a high success rate  when generating biosynthetic routes to complex NPs that recapitulate known pathways and building blocks, particularly in comparison to other methods at a comparable computational time. By combining an existing enzyme prediction tool, we further provide a user-friendly server that can not only predict biosynthetic pathways but also rank the biological feasibility of these pathways according to the estimated preference of species and enzymes. This is a valuable feature considering that template-free methods often predict new reactions outside of current knowledge. We have validated the potential of this webserver to predict native biosynthetic pathways as well as redesigning pathways for complex NPs, although we acknowledge that the pathway scoring function is not perfect due to the limited data availability and inherent limitations of the search algorithm. Therefore, extra modules that link the predicted intermediates and reactions to the known data sources were added to the webserver to offer annotation and facilitate the re-ranking of pathways. In this sense, we have improved the reproducibility of the reported biosynthesis routes and the enumeration ability of alternative biosynthetic pathways, provided an easy operational and visualizable webserver with some key options for users to balance accuracy and efficiency in practical use, and also supplemented multiple criteria for judging the rationality of the predicted pathways and building blocks. Future improvements can be made by providing further information, such as the promiscuity, fidelity, and diversity of enzyme catalysts, and introducing advanced enzyme prediction and design tools64 into the rule-free models will allow better mass-balance for the single-step retro-biosynthesis predictions.There still remain certain challenges for the refinement of the BioNavi-NP. For example, at present, it could not correctly predict the biosynthetic starting materials for some complex NPs involving many building blocks or reaction steps, even though a much longer pathway could be found compared to some other methods Table . AlternaIn summary, this work combines transformer models and the Retro* search algorithm to develop a leading-edge biosynthesis navigator (BioNavi-NP), which can enumerate diverse biosynthetic pathways and trace natural products back to biologically-plausible building blocks. BioNavi-NP achieves a high success rate at generating biosynthetic routes and searching building blocks for NPs. Therefore, it is promising for native biogenesis analysis, biosynthetic pathway reconstruction, and rational design.7 integrated a number of major resources of metabolites and biochemical reactions including MetaCyc5, KEGG6, The SEED65, Rhea66, BiGG67 and so on. However, the information regarding reaction directionality and compartmentalization were generally disregarded, which are important to predict the precursors of the NPs. So we first extracted reactions directly from MetaCyc (version 23.5) pathway ontology and KEGG  pathway maps, where the “irrelevant” agents such as cofactors and minor substrates or products were removed. These reactions were excluded from MetaNetX (version 4.1) dataset, and following the previous work34, we derived pairs of precursors and metabolites where the maximum common substructure exceeds 40% of the atoms of the metabolite for the rest of the reactions. Then, multi-product reactions were decomposed to multiple mono-product reactions with the same substrates and the cofactors were removed. Compounds containing Coenzyme A (CoA) play an important role in the biosynthesis of natural products especially polyketides and lipids. Although CoA is a complex structure that contains 84 heavy atoms, it is usually not involved in the reaction center, so the CoAs in the molecules were replaced by “*” in the SMILES format and restored when the results were output. Considering that the stereochemistry is often poorly annotated in the structure databases, we firstly checked the structures in our reaction dataset. The potential stereochemical centers exist in 15,372 out of 20,710 structures, and 10,909 (71.0%) of them are completely annotated with the stereochemistry, 12,763 (83.0%) are annotated with at least half of the stereochemistry. Thus the stereochemistry was preserved in our dataset. The resulting BioChem dataset consists of 33,710 unique pairs of precursors and metabolites, 1000 of which were selected as the test set and another 1000 as the validation set  between any component (reactants and/or products) of each reaction in the USPTO database and the NPs from the DNP1 database (version 27.2), resulting in 60,000 chemical reaction equations. The USPTO_NPL dataset was merged with the BioChem dataset to train the single-step model.MetaNetX version 3.5 pathwTo obtain a set of target natural products for the quantitative evaluation of a multi-step model that contains different scaffolds, structures from the BioChem dataset were clustered according to their biosynthetic building blocks. Then 368 target molecules with complete biosynthetic pathways  were randomly extracted from the different clusters, which can be further divided into five broad categories . Moreover, 25 unseen natural products  whose biosynthetic pathways are unclear or not included in the data source were chosen to evaluate the generalization of our model.4.Given an input of a target molecule, our task is to recursively decompose the molecule into available biogenetic precursors following the biosynthesis scheme. In this study, a biogenetic reaction was described by a variable-length string containing one pair of SMILES notations representing the reactants and target compound  on the training set, saving one checkpoint every 10,000 steps and averaging the last five checkpoints. Hyperparameters are selected based on the performance of the model on the validation set. A beam search procedure72 was then used to infer multiple precursors candidates on the test set. We used the best performance model to infer the candidate sequences of precursors with a beamwidth of 10. As a result, the top10 candidate sequences ranked by total probability were retained. The training details can be seen Supplementary Method The single-step prediction was made by the transformer neural networks39  and the total cost is the sum of all steps scores along the pathway.For multi-step planning, we adopt Retro*Each time a full pathway is found during the tree expansion, the pathway is returned, and an additional bonus is received by the node, to allow for biasing toward similar successful pathways. At the end of the search, the most visited pathway is returned (i.e. the best one), and all pathways are returned ranked in order of decreasing cost. When performing multi-step evaluation on the internal set, we set the beam size of the transformer, max route, iteration, max depth as 10, 5, 100 and 10, respectively. It is worth noting that increasing the width, depth of the search and the number of iterations will certainly improve the accuracy, but the time consumption will also increase exponentially.Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Increases in anti-Asian COVID-19 related discriminatory behaviors have been observed, many of which targeted older adults. Studies demonstrate that racial discrimination is associated with worse health outcomes, including anxiety, depression, and sleep difficulties. No previous studies have examined the impact of day-to-day experiences of discrimination before and during COVID-19 on both Asian and non-Asian older adults within the same sample. We examined whether everyday discrimination was associated with increased anxiety and depression symptoms, decreased levels of functioning, and increased sleep difficulties among Asian and non-Asian US older adults before and during the pandemic. Data came from the Positive Minds-Strong Bodies randomized clinical trial, an evidence-based mental health and disability prevention intervention for racially and ethnically diverse older adults with elevated depression or anxiety symptoms and minor to moderate disability. We conducted secondary data analyses in a cohort of 165 older adults (56 Asian and 109 non-Asian) assessed before COVID-19 (May 2015-May 2018) and during COVID-19 (March 2021-July 2022). Regression models examined whether everyday discrimination impacted health outcomes differently before and during COVID-19, and whether this effect was stronger among Asian compared to non-Asian older adults. Non-Asian older adults reported the same levels of everyday discrimination before and during COVID-19. Consistent with literature suggesting that social distancing has inadvertently kept US Asian populations from experiencing discrimination, Asian older adults reported marginally lower levels of everyday discrimination during the pandemic compared with pre-pandemic. We found that everyday discrimination was not associated with health outcomes before COVID-19. In contrast, during the pandemic, everyday discrimination was associated with worse anxiety and depression symptoms and worse levels of functioning, although only the impact on depression was significantly stronger compared with before the pandemic. This negative impact of everyday discrimination on health outcomes during the pandemic appeared to affect both Asian and non-Asian older adults similarly. Social support and social cohesion buffered against the negative effect of everyday discrimination on depression and level of functioning during the pandemic. Results suggest that public health interventions aimed at reducing everyday discrimination and emphasizing social support and cohesion can potentially improve health outcomes for all US older adult populations.www.ClinicalTrials.gov; identifier: NCT02317432. Due to misinformation about the novel coronavirus , anti-Asian racism and xenophobic attacks against Asian Americans have significantly increased since the beginning of the COVID-19 pandemic . From MaThis prior evidence on the association between anti-Asian COVID-19 related discrimination and health outcomes has been limited by two factors. The first one relates to the use of samples that include Asian populations only. The one exception is a prior study showing that both Asian and non-Asian US young adults had negative affective reactions to anti-Asian COVID-19 related discrimination . Yet, otThe second limitation relates to a lack of pre-pandemic baseline data against which to measure changes in discrimination within individuals. Although recent studies have confirmed that racial discrimination during COVID-19 is associated with poorer mental and physical health, in the absence of pre-pandemic data these studies implicitly assume that lower levels of discrimination would have been reported had the pandemic not happened. However, the pandemic has imposed some restrictions that could have led to decreased opportunities to experience discrimination. After the World Health Organization declared the COVID-19 outbreak a global pandemic on March of 2020, many US states enacted stay-at-home orders to prevent the spread of COVID-19. Whereas, social isolation itself can negatively affect mental and physical health , a recenLancet Health Longevity , the present study had three aims. Our first aim was to investigate changes in self-reported everyday discrimination and mental and physical health  within Asian and non-Asian older adults before and during COVID-19. Our second aim sought to quantify the association between self-reported everyday discrimination and mental and physical health before and during COVID-19, and to test whether these associations were stronger among Asian older adults compared with non-Asian older adults. In alignment with prior research, our last goal was to examine whether social support and social cohesion were possible moderators altering the association between discrimination and health outcomes of older adults.This is a secondary analysis using data from the Positive Minds-Strong Bodies (PMSB) randomized clinical trial, a disability preventive intervention aimed to improve mental health and physical functioning of racial and ethnic minority older adults with mild to severe depression or anxiety symptoms and minor to moderate disability . ResearcAs part of a follow-up study aimed to assess the impact of the COVID-19 pandemic among older adults previously enrolled in PMSB, research assistants re-contacted study participants between March 2021 and July 2022 and invited them to participate in a COVID-19 follow-up assessment. Self-reported measures of mental and physical health were included in all assessments . However, self-reported everyday discrimination was included in the baseline and COVID-19 follow-up assessments only. Thus, the present study used the baseline assessment, conducted between May 2015 and May 2018, as the only pre-pandemic data. The COVID-19 follow-up assessment, collected between March 2, 2021, and July 18, 2022, was used as the during-pandemic data. Study participants completed the COVID-19 follow-up assessment ~2.9–6.4 years post-baseline. In the initial RCT, study procedures were approved by the Institutional Review Boards of Massachusetts General Hospital/Partners HealthCare and New York University, with ceded reviews for partnering CBOs conducting human subjects' research. The Institutional Review Boards for Massachusetts General Hospital and New York University approved the ongoing COVID-19 follow-up assessment. All participants provided informed consent.In the initial RCT, 1,057 potential participants were screened at the participating CBOs and community clinics to assess eligibility. Eligible participants were 60 years old and above, spoke either English, Spanish, Mandarin, or Cantonese, and presented mild to severe depression or anxiety symptoms and minor to moderate disability. Mild to severe depression symptoms were defined as scoring five and above on either the Patient Health Questionnaire-9 (PHQ-9)  or the Gvia phone interviews . Because of small sample size in some racial and ethnic groups, all 109 non-Asian older adults were analyzed together  screened participants were eligible, of which 307 (80.6%) agreed to participate and were randomized to either PMSB or EUC conditions. In the COVID-19 follow-up study, we attempted to re-contact 302 of the 307 previously enrolled participants, as five of them were identified as deceased according to study records. An additional 20 participants have been identified as deceased from the National Death Index, and two more during COVID-19 follow-up data collection. Further, 17 participants were re-contacted but unable to participate due to medical conditions . Among the remaining 263 participants, 165 (62.7%) were successfully reached and completed the COVID-19 follow-up assessment The PMSB is a combined psychosocial and exercise training intervention. The psychosocial intervention, which was delivered within 6 months, included ten one-h individual sessions focused on psychoeducation, mindfulness, cognitive restructuring, noticing and overcoming unhelpful thoughts, and creating a self-care plan. The exercise training intervention, delivered within 12–14 weeks and concurrently with the psychosocial intervention, included 36 group sessions of physical exercise focused on enhancing functioning and preventing physical disability. As described in Alegría et al. , the intnot at all and 3 = nearly every day). Total scores are calculated summing all items , with higher scores representing worse symptoms.Depression symptoms were assessed using the GDS-15, a 15-item self-reported measure used to screen, diagnose, and evaluate depression in older adults . The meacannot do and 5 = none). Total scores are calculated summing all items , and higher scores represent greater levels of physical functioning. Sleep difficulties were assessed using five items about the following past-month self-reported difficulties with sleep: Falling asleep, staying asleep, waking up too early, frequent awakening during the night, and sleeping during the day. Responses are rated on a 4-point scale (0 = never and 3 = three or more times a week). Total scores were calculated summing all items , and higher scores represent lower sleep quality.Level of functioning was assessed using the Function Component of the Late-life Functioning and Disability Instrument (Late-life FDI), a 32-item self-reported measure for older adults that assess difficulties performing daily physical activities without help from others or assisted devices . The insnever and 5 = almost every day). Total scores were calculated summing all items , and higher scores represent higher levels of perceived discrimination. Because on average non-Latinx White populations tend to report lower levels of discrimination compared to other racial and ethnic groups, we conducted sensitivity analyses that excluded non-Latinx White older adults from our sample. Since our main findings were not affected by removing non-Latinx White participants, we chose not to exclude them from our analyses.The 9-item Everyday Discrimination Scale (EDS) was used to assess the frequency of day-to-day experiences with unfair treatment that are chronic or episodic but generally minor  . Becausenever and 3 = always). Three items assessed instrumental social support by asking whether the respondent could depend on either relatives, neighbors/friends, or spouse/partner for help with practical things (0 = no and 3 = yes). One item assessed satisfaction with social support (0 = very unsatisfied and 3 = very satisfied) and the remaining two items asked about frequency of getting together with family and friends and frequency of being taken care of by family members (0 = never and 3 = at least once a week). Total scores are computed by averaging all items , and higher scores indicate greater quantity and quality of social support. Social cohesion was assessed using the social cohesion and trust section of the Collective Efficacy Scale . Total scores were computed as the sum of all items , and higher scores represent greater neighborhood social cohesion.Social support was assessed using 10 items about the quantity and quality of social support . Four itcy Scale , a self-We used baseline data to adjust for age, sex , education level (less than high school or high school and above), and intervention condition (PMSB or EUC). We also used baseline data to characterize participants in terms of household size, birthplace (foreign born or US born), and primary language . We noted that all Asian older adults in our sample were foreign born and reported their primary language as either Mandarin or Cantonese. Further, all non-Asian older adults reported their primary language as either English or Spanish. Thus, neither birthplace nor primary language were adjusted for because the effect of these two individual characteristics was indistinguishable from the effect of Asian race.We began by describing differences in the distribution of pre-pandemic baseline data between participants who completed and did not complete the COVID-19 follow-up assessment within Asian and non-Asian older adults. Examining these differences allowed us to assess whether, for example, older adults with higher levels of perceived discrimination or worse mental health symptoms were more likely to not have responded to the COVID-19 follow-up assessment. We then described changes in self-reported everyday discrimination and mental and physical health  within Asian and non-Asian older adults before and during COVID-19. Afterwards, we examined the association between self-reported discrimination and mental and physical health outcomes before and during COVID-19 using linear regression models and tested whether these associations were stronger among Asian compared with non-Asian older adults. Mental and physical health outcomes were separately modeled as the dependent variable. Further, separate linear regression models were estimated using baseline pre-pandemic data and COVID-19 follow-up data. However, because self-reports before and during COVID-19 were likely correlated within individuals, regression models were estimated using a system of two linear equations, one using the baseline pre-pandemic data and another the COVID-19 follow-up data. These two regressions are related because the error term associated with the dependent variable may be correlated. By explicitly modeling this potential correlation, we could also test whether the effect of discrimination on health outcomes was stronger during COVID-19 compared with the pre-pandemic period. The system of equations representing this conceptualization was as follows:i pre-pandemic and i during COVID-19. The superscript “0” is used to indicate a self-reported measure at the pre-pandemic baseline assessment, and the superscript “1” is used to indicate a self-reported measure at the COVID-19 follow-up. Xi is the vector of covariates that were adjusted for . The error terms where In the above system of equations, the parameter rsion 15 .In As show in p = 0.10) or among non-Asian older adults .In p = 0.017; anxiety symptoms: 6.33 before vs. 4.32 during COVID-19; p = 0.001).Changes in depression and anxiety symptoms, level of functioning, and sleep difficulties within individuals before and during COVID-19 are presented in Linear regression model estimates for the effect of everyday discrimination on health outcomes are presented in None of the covariates that were adjusted for were significantly associated with the outcomes either before or during COVID-19 except for level of functioning. Results from To investigate whether social support and social cohesion moderated the negative impact of everyday discrimination on health outcomes during the pandemic, we estimated models that included two-way interactions between everyday discrimination and social support and cohesion. As shown in In The present study is among the first to investigate within-person changes in self-reported discrimination before and during the COVID-19 pandemic among Asian and non-Asian US older adults. Contrary to our expectations, we found that Asian older adults reported fewer experiences of day-to-day unfair treatment (everyday discrimination) during the pandemic compared with before the pandemic . Increased social isolation during COVID-19 may have resulted in decreased opportunities to experience discrimination. For example, some news reports have suggested that, to better protect themselves against exposure to COVID-19, many Asian older adults started isolating socially even before the stay-at-home orders were enforced . Recent Lower levels of perceived everyday discrimination during COVID-19 among Asian older adults might also be related to the specific characteristics of our sample. As shown in Our results also indicate that average levels of depression and anxiety symptoms among Asian older adults remained stable during COVID-19 compared with their pre-pandemic levels. In addition, non-Asian older adults reported lower anxiety and depression symptoms during COVID-19 compared with before COVID-19. Older adults have experienced disproportionately greater adverse effects from the pandemic . HoweverWe found that everyday discrimination was not associated with worse depression and anxiety symptoms, lower levels of functioning, or increased sleep difficulties pre-pandemic. Older adults from the present study were eligible for the PMSB trial based on pre-existing mental and physical conditions, and they were also not receiving mental health services. There is increasing evidence suggesting that people with mental illnesses who are not receiving care avoid treatment because of stigma and expected discrimination . Thus, tA plausible explanation for why discrimination negatively impacted mental and physical health during but not pre-pandemic is that older adults may have had fewer resources to cope with discrimination during the pandemic. For example, a recent study showed that US Asian adults who experienced discrimination during COVID-19 appeared to use social media as a coping tool, and social media use was associated with better subjective wellbeing . Prior sAnother plausible explanation is that the negative associations observed during the pandemic could be related to the specific type of discrimination measured in the present study. Since everyday discrimination assessed day-to-day experiences with unfair treatment, older adults who reported discrimination during COVID-19 are potentially more likely to have experienced such discrimination on a personal level . A prior study found that observed discrimination through media during the COVID-19 pandemic was not a strong predictor of greater anxiety, vigilance, and worry . On the Our last set of results indicated that social support and social cohesion offset the impact of everyday discrimination on depression symptoms and level of functioning during the COVID-19 pandemic, despite not being directly linked to better mental and physical outcomes. We found that although everyday discrimination during COVID-19 had a negative impact on depression symptoms and level of functioning for all older adults, the negative effect of discrimination on these two outcomes was attenuated at higher levels of social support and cohesion. This result supports the stress-buffering model, which posits that social support protects mental health through the indirect pathway of interacting with the stressor  rather than by being directly associated with lower levels of psychological distress . AccordiOur study has several limitations. The COVID-19 follow-up assessment started in March 2021, a year after the World Health Organization declared the COVID-19 outbreak a global pandemic. Thus, the effect of the COVID-19 pandemic on discrimination and mental and physical health at the early stages of the pandemic may differ from those we found in the present study. For example, a prior longitudinal study found that depression and anxiety symptoms sharply increased right at the beginning of the pandemic, but they rapidly declined within the next 20 weeks . Our stuNotwithstanding these limitations, our study represents one of the first efforts to investigate within-person changes in day-to-day experiences of unfair treatment before and during the COVID-19 pandemic, and how these experiences of discrimination might have impacted health outcomes differently before vs. during the pandemic among Asian and non-Asian older adults. Our findings suggest that although older adults might have been less likely to be exposed to everyday situations where they could experience discrimination during COVID-19, the pandemic might still have exacerbated the negative impact of discrimination on health outcomes. However, social support and social cohesion can act as protective factors that buffer against this increased negative impact of discrimination. Our results suggest that public health interventions aimed at reducing everyday discrimination and emphasizing social support can potentially improve health outcomes of all US older adult populations, particularly those with pre-existing depression, anxiety, and functional limitations.smarkle@mgh.harvard.edu.The data used to obtain the results presented in this manuscript is not publicly available because it involves a racial and ethnic minority sample including participants with depression, anxiety, and functional limitations. The author/s are not able to release the data used in the current manuscript given the sensitivity of the data and their agreements with the Institutional Review Boards of the participating institutions. Reasonable requests to access the data can be directed to Sheri Markle, at Study procedures involving human participants were reviewed and approved by the Institutional Review Boards of Massachusetts General Hospital/Partners HealthCare and New York University, with ceded reviews for partnering Community-Based Organizations conducting human subjects research. The patients/participants provided their written informed consent to participate in this study.LZ, MC-G, and MA contributed to the conception, design of the study, and wrote the first draft of the manuscript. LZ and MC-G organized the database and performed the statistical analysis. ZL, XO, and FZ wrote sections of the manuscript. All authors contributed to manuscript revision and approved the submitted version.Research reported in this publication was supported by the National Institute on Aging and the National Institute of Mental Health under Grant Number R01AG046149 and its COVID supplement. The funders  had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.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.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.


Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, the disease has rapidly become a global threat. The constant emergence of new variants has increased the difficulty of controlling this disease. Vaccination is still considered the most effective method to prevent COVID-19. Vaccination has expanded to include children aged 3–17 years old, and some countries have lowered the age of vaccination to 6 months . However, children under 3 years old are still not able to be vaccinated in most countries. In this study, we summarize the COVID-19 vaccination status in pregnant women, comprehensively elaborate on the status of maternal immune response and maternal antibody transfer after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination, and further analyze the possible influencing factors of maternal antibody transfer according to the currently available evidence on the topic. It was concluded that pregnant women develop an immune response and produce antibodies that can be transmitted through the placenta after vaccination, but more data are needed to determine the transfer rate and duration of these maternal antibodies and potential factors. The results provide a scientific basis for studying the protective effect of maternal antibodies on infants, formulating a vaccination strategy for pregnant women, and preventing SARS-CoV-2 infection in infants. Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to spread worldwide and poses a serious threat to human health. According to the World Health Organization (WHO), as of 30 March 2022, a total of 483,556,595 confirmed cases have been reported worldwide, including 6,132,461 deaths [Since the COVID-19 outbreak began, different kinds of COVID-19 vaccines have been quickly approved for marketing, including live-attenuated vaccines, inactivated vaccines, recombinant vector vaccines, subunit vaccines, and nucleic acid vaccines . To dateAs a special population, pregnant women and infants have received ongoing attention during the COVID-19 epidemic. Pregnant women have been excluded from vaccination clinical trials and the preliminary stages of large-scale vaccination, so data are currently lacking on the efficacy and safety of vaccination in this group. Due to physiological changes in the immune and cardiopulmonary systems, pregnant women are associated with a higher risk of serious COVID-19 infection and adverse pregnancy outcomes. Adequate vaccine safety and efficacy data have increased public confidence in the vaccine, and many countries have started to recommend that pregnant women receive the COVID-19 vaccine. Increasing lines of evidence indicate that vaccinating pregnant women with COVID-19 before and during pregnancy is safe and effective. Inoculation with a COVID-19 vaccine during pregnancy can not only stimulate an immune response in pregnant women, reducing the risk of infection and severe illness, but also generate antibodies that can be transferred from the mother to the fetus through the placenta, which may be of great significance for the protection of the mother and the newborn ,7.An infant’s immune system is not yet completely developed, and its ability to defend the body from the virus is weak. After infants suffer from COVID-19, the most common symptoms are respiratory symptoms, including respiratory distress, lack of oxygen, low oxygen saturation, and cough, and 38% of previously infected neonates require intensive care [Although studies have pointed out that pregnant women can transfer SARS-CoV-2 antibodies to the fetus after vaccination, helping the fetus to have some resistance to the virus, research conducted with a large enough sample size is lacking. The transfer rate and attenuation law of maternal antibodies as well as the factors and mechanisms affecting antibody transfer are still uncertain. In the present study, from the perspective of the vaccination status of children and pregnant women, we analyzed the antibody production and metastasis of pregnant women diagnosed with COVID-19 or who have been vaccinated with a COVID-19 vaccine during pregnancy. This work aimed to comprehensively describe the transmission efficiency, attenuation law, and influencing factors of maternal antibodies to provide a basis for formulating COVID-19 vaccination strategies for pregnant women and infants.The vaccination coverage of pregnant women is closely related to vaccination recommendations and the willingness of pregnant women to receive vaccination in each country; recommendations for vaccination during pregnancy also change over time . IncreasAlthough many national policies encourage pregnant women to become vaccinated, the willingness of pregnant women for vaccination is another important factor that affects vaccination. In a British survey , pregnanPregnant women who are infected with SARS-CoV-2 are at a high risk of serious maternal and neonatal complications. In a meta-analysis covering 61 studies, 790 COVID-19-positive women and 548 newborns were analyzed. The incidence rates of cesarean section, premature delivery, low birth weight, and adverse pregnancy events were 72%, 23%, 7%, and 27%, respectively . In a syMany countries around the world have begun to vaccinate children aged 3–17 years old against COVID-19. For example, China expanded the vaccination age to three years old and above in November 2021 . In ColoIn a systematic review of 49 studies including a total of 655 pregnant women and 666 neonates, no clear evidence of vertical mother-to-child COVID-19 transmission was found , althougTo determine whether the antibodies produced by the mother after being infected with SARS-CoV-2 can be effectively passed to a newborn during pregnancy, a cohort study in the United States detected the IgG antibody in 83 maternal and 72 cord blood sera. The antibody-negative neonates were born to pregnant women who had IgM-only or lower IgG antibody concentrations. These pregnant women with SARS-CoV-2 infection had a placental antibody transfer rate of more than 1.0 . In addiAs SARS-CoV-2 maternal antibodies can be effectively delivered to neonates, another scientific concern is how long they will last. Wang X et al. demonstrated that the SARS-CoV-2 IgG levels of newborns with SARS-CoV-2-infected mothers dropped sharply to one-tenth two months after birth . Similarp < 0.001); this conclusion was also confirmed by Joseph and Rathberger et al. [SARS-CoV-2 antibodies can indeed be transmitted to newborns through the maternal placenta (as shown in r et al. ,41. Hower et al. ,41 foundr et al.  came to r et al. . Many stStudies have confirmed not only that pregnant women infected with SARS-CoV-2 produce specific antibodies but also that these antibodies can be transferred to the fetus through the placenta, which may have a protective effect on infants. However, additional data are needed to clarify whether the immune response and antibody transfer following COVID-19 vaccination during pregnancy are similar to those in pregnant women infected with SARS-CoV-2.Israel was the first country to start vaccinations and boost immunization. Similarly, Israel was one of the first countries to recommend vaccination for pregnant women, providing us with a lot of vaccination experience. A study in Israel found that the BNT162b2 COVID-19 vaccine induced strong maternal immunization during pregnancy, and the antibodies were effectively transferred to the fetus, supporting the effects of vaccination during pregnancy . AnotherThe maternal antibody level in neonates and its persistence affect the protection and duration of antibodies during infancy. In a cohort of newborns born to women vaccinated against SARS-CoV-2, the titer of IgG antibodies in the cord blood was significantly higher than it was in those born to infected individuals . The folFirst, whether or not the mother has been completed vaccinated is a factor. A study showed that only 43.6% of newborns born to women who received one dose of vaccine had detectable IgG, while 98.5% of newborns born to women who received two doses of vaccine had detectable IgG . MoreoveVaccination is essential for protecting pregnant women and their offspring from SARS-CoV-2 infection. Studies have shown that vaccinated women have significantly reduced COVID-19 infection during pregnancy compared with unvaccinated women  and thatThe COVID-19 epidemic has been ongoing for more than two years and has spread worldwide. Maternal immunization can not only protect the mother and fetus from SARS-CoV-2 infection but also provide passive protection for babies after birth due to the antibodies transmitted through the placenta. However, some problems persist: the best time for mothers to become vaccinated to protect newborns is unclear; the transfer rate of maternal antibodies and the duration and level of maternal antibody transfer in infants also require more data. The data needed to determine the extent to which maternal antibodies protect lactating newborns remain insufficient; whether these antibodies have potential adverse effects on the active immune response of newborns and how much they can help protect infants from SARS-CoV-2 infection, serious diseases, and death also remains unclear. We need to explore unknown mechanisms that may affect the antibody transfer process from mother to child. Therefore, against the background of the ongoing COVID-19 pandemic, information should be collected through well-designed prospective or longitudinal studies to provide a scientific basis for the safe and effective implementation of maternal and pediatric vaccination strategies.


No post-procedure complications were noted. The 22G EUS-FNB needle proved superior to 22G EUS-FNA in terms of tissue acquisition diagnostic accuracy and histologic adequacy in focal liver lesions.Endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) or fine-needle aspiration (EUS-FNA) from focal liver lesions are indicated in selected cases, but there has been no previous comparison of needle types of the same size. The aim of our study was to compare the histologic diagnostic accuracy and adequacy of cores obtained with EUS-FNB needles in contrast to those obtained with FNA needles in focal liver lesions. This prospective one-center study included patients with left lobe hepatic focal lesions with contraindications for percutaneous liver biopsy or need for EUS for concomitant lesions. Each patient had one pass of 22G EUS-FNB (Franseen) needle and one pass of 22G EUS-FNA in a crossover manner, without macroscopic on-site evaluation. Each sample was analyzed separately for histologic adequacy and diagnosis. The final diagnosis was based on histology results or on imaging follow-up in the case of negative biopsies. The EUS-FNB samples (n = 30) were found to be more adequate for histologic analysis, with more cellularity and longer tissue aggregates than the EUS-FNA samples (n = 30). The accuracy of EUS-FNB was 100%, whereas that of EUS-FNA was 86.7% ( Focal liver lesions require histological and immunohistochemical diagnosis for appropriate treatment, especially in the context of malignant disease. Endosonography (EUS) can visualize hepatic lesions <1 cm, which were not identified by cross-sectional imaging, especially during staging for digestive cancers, although it is limited to the left lobe and the proximal region of the right lobe  whenever appropriate. The performances of EUS-FNB and EUS-FNA were compared with Z-test for proportions whenever appropriate. The clinical utility index (CUI) was used to evaluate the relevance of FNB and FNA in screening and diagnosis  [The patient data were collected in a Microsoft Excel spreadsheet with the results of FNB and FNA as paired data , longest core tissue length (mm), core surface (mmreening) .Thirty-two consecutive patients were evaluated between January 2019 and March 2021. Two patients were excluded because the FNA and FNB samples were not analyzed separately following the study’s protocol. The characteristics of the evaluated patients are presented in The final diagnosis was based on EUS-FNB or EUS-FNA results in 25 patients with malignant lesions (14 metastases and 11 primary liver tumors). The remainder of the six benign lesions were abscesses with a solid aspect treated with antibiotics and were not further identified at the follow-up transabdominal imaging examination in all but one case with primary sclerosing cholangitis on MRI (magnetic resonance imaging) and repeated negative biopsy at 6-month follow-up.All focal liver lesions were hypoechoic or hyperechoic with a hypoechoic rim in the case of hepatic metastasis.The adequacy of EUS-FNB compared to EUS-FNA samples is reported in EUS-FNB was found to provide a better diagnostic rate than EUS-FNA , with exOur prospective study shows, for the first time, 22G FNB needles are statistical superior in terms of diagnostic accuracy compared to 22G FNA needles in focal liver lesions.Liver imaging provides high diagnostic accuracy in cases of liver lesions, but differential diagnosis might be difficult in cases of a well-differentiated hepatocellular neoplasm or a regenerative nodule, which demand histology. Tissue acquisition can be obtained through ultrasound or CT-guided percutaneous biopsy or through EUS-guided biopsy.The use of FNA of FNB needles during EUS depends on the choice of endoscopists, pathologists, and, in some cases, the quantity of samples needed for ancillary tests, such as immunohistochemistry (IHC), especially in cases of poorly differentiated neoplasms or for the establishment of the origin of a metastatic focal liver mass. Goldhoff et al.  demonstrIn the case of diffuse liver disease, a meta-analysis comprising seven studies proved that the length of the specimen when EUS-FNB was used was similar to the percutaneous result . AdditioThe diagnostic rate for EUS-FNB was reported to be 93.9%, with an adverse rate of 2.3%, and an insufficient core was considered to be 4% compared to 20% in the case of FNA needles . Two pasIn the case of focal liver lesions, few articles have been published concerning the needle size or type, with the rate of adverse events varying from 0 to 6.1%, with a median of 3% . The ratFirst-generation FNB needles have been studied in retrospective studies, showing that the diagnostic accuracy of reverse-beveled needles for solid hepatic lesions was 89.7–90%, and the adequacy for IHC was 88–91% ,12,13 bup = 0.01, A retrospective study including focal liver lesions sampled with multiple types of FNB needles and 19G FNA with multiple passes compared the results to those obtained with percutaneous biopsy, revealing that the EUS-guided technique offered similar adequacy and diagnostic accuracy to the percutaneous technique , with a longer procedure duration (seven vs. one minute). The length of the cores obtained with FNB needles was shorter than that obtained with EUS-FNA (10 vs. 15 mm) , which iThe strength of our study is associated with the crossover nature of the inclusions and the comparison of the immunohistological quality of the specimens. The limitations of our study include that it is a single-center study and the limited number of patients because of the low number of indications for this procedure. Additionally, all the examinations were performed by an experienced endoscopist, who could not be blinded to the needle type, and the pathologist was very experienced with liver biopsy results. Another limitation is the lack of cytology of the FNA samples, which may have decreased the diagnostic difference, although IHC on cytology specimens is limited. In our analysis of the cores obtained from both EUS-FNA and EUS-FNB, we did not use rapid on-site or macroscopic on site evaluation because we wanted to compare the real value of one pass with EUS-FNA and one pass with EUS-FNB, although their association might improve the accuracy of the EUS-FNA method ,33,34,35In conclusion, 22G EUS-FNB needles outperform 22G EUS-FNA needles without macroscopic on-site evaluation in terms of diagnostic accuracy and adequacy, with no adverse events, despite higher costs. Further steps are necessary to standardize the technique and the selection of patients, which will aid in the development of this technique of endohepatology.


In Italy, COVID-19 vaccination campaign for school personnel started in February 2021 and began mandatory from 15th December 2021 to all the people who work within schools. Here we described Italian school principals’ beliefs about vaccines and its association with feelings about information regarding coronavirus, COVID-19 and the pandemic.Data collection started in October 2021 and is ongoing. Beliefs about vaccines were investigated both for COVID-19 vaccination and for vaccination in general.A total of 726 questionnaires were analyzed so far. The majority feels to be well informed about the coronavirus or the pandemic (75%) and not at all nor a little confused about COVID-19 information (89%). Only 2% disagree/strongly disagree with the statement “vaccination is compatible with my attitudes or religious beliefs”. Beliefs regarding vaccines in general are correlated with those regarding COVID-19 vaccines. When different beliefs are described, we observed a trend towards considering COVID-19 vaccines less safe and effective, but more important to protect themselves and their family than other vaccines. Moreover, beliefs about vaccination in general and regarding COVID-19 are associated with how well they feel informed about the coronavirus or the pandemic, and whether they feel confused about COVID-19 information. In particular: the better they feel informed about the coronavirus and the related pandemic, the higher the perception of vaccines in general and COVID-19 vaccine as important, safe, and effective; the less they feel confused about COVID-19 information.School principals showed a high level of confidence on vaccines. The association between beliefs in vaccinations and the characteristics of information about COVID-19 supported the effectiveness of Italian vaccination policy and information campaigns.


Optical quantum information science and technologies require the capability to generate, control, and detect single or multiple quanta of light. The need to detect individual photons has motivated the development of a variety of novel and refined single-photon detectors (SPDs) with enhanced detector performance. Superconducting nanowire single-photon detectors (SNSPDs) and single-photon avalanche diodes (SPADs) are the top-performer in this field, but alternative promising and innovative devices are emerging. In this review article, we discuss the current state-of-the-art of one such alternative device capable of single-photon counting: the resonant tunneling diode (RTD) single-photon detector. Due to their peculiar photodetection mechanism and current-voltage characteristic with a region of negative differential conductance, RTD single-photon detectors provide, theoretically, several advantages over conventional SPDs, such as an inherently deadtime-free photon-number resolution at elevated temperatures, while offering low dark counts, a low timing jitter, and multiple photon detection modes. This review article brings together our previous studies and current experimental results. We focus on the current limitations of RTD-SPDs and provide detailed design and parameter variations to be potentially employed in next-generation RTD-SPD to improve the figure of merits of these alternative single-photon counting devices. The single-photon detection capability of RTDs without quantum dots is shown. High-speed and high-efficiency single-photon detectors (SPDs) are a fundamental requirement for a broad range of applications, particularly in optical quantum information technologies, such as quantum key distribution, boson sampling, quantum sensing or optical quantum computing ,2,3. Evientation , whereasentation ,6,7.Overall, a growing demand for ever better detector performance has resulted in a variety of novel optoelectronic devices and device refined device concepts. By far the most impactful single-photon detector technology of the past decade are superconducting nanowire single-photon detectors (SNSPDs) ,9. They Blakesley et al., who showed that the resonant tunneling current across a double barrier quantum well can be modulated by the entrapment of individual photogenerated holes within an adjacent quantum dot (QD) layer [Another emerging class of single-photon detectors are semiconductor resonant tunneling diodes (RTDs) . RTDs arD) layer .RTD single-photon detectors boast, at least in theory, a variety of desirable characteristics when compared to conventional SPDs. In contrast to SNSPDs and SPADs, a photon detection event does not cause a breakdown (quenching) of the current flow, which makes RTD-SPDs inherently photon-number resolving and deadtime free in the classical sense. Remarkably, the PNR can even be achieved at elevated temperatures .Combining our previous work ,22, and The Fundamentals of Resonant Tunneling Single Photon Detection, we discuss the underlying physics and working principles of RTD SPDs.In Resonant Tunneling Diodes, we briefly introduce the RTD as nanoelectronic device on the basis of the example of a III-V semiconductor double-barrier quantum well.In . The Photodetection Mechanism and Operational Modes, we revisit the RTD photodetection mechanism and elaborate on how the NDC region enables various operational modes.In Section 2.2Single-Photon Detection with Resonant Tunneling Diodes, we provide a theoretical framework on the pre-requisites required to achieve single-photon detection that can be used for device optimization and performance predictions. The model is then experimentally checked and verified.In Practical Device Design Considerations, we elaborate on various design considerations in order to optimize future detector performance.In Quantum Dots are not a Necessity, we demonstrate that photon-counting with RTDs is possible even without QDs as minority charge carrier traps.In Detector Architectures and Device Design, we revisit various RTD photodetector architectures, and compare their respective advantages and disadvantages.In Strategies against the Quantum Efficiency Dilemma–Cavity-Enhanced Detectors, we provide a pathway to near-unity detection efficiencies in RTD-SPDs based on a carefully designed heterostructure integrated into an optical distributed Bragg reflector (DBR) cavity.In Quantifying the Device Performance of RTD-SPD, we assess and compare the performance of RTD single-photon detectors in terms of spectral range, deadtime, dark count rate, detection efficiency, timing jitter, and the ability to resolve photon number.In the final RTDs are structurally rather simple two-terminal nanoelectronic devices that make use of two quantum-mechanical effects: energy quantization due to electronic confinement and tunneling through a potential barrier. Notable, these quantum mechanical effects in RTDs can be observed even at room temperature and above.0.6Ga0.4As/GaAs DBQW. Dark contrast refers to the Al-rich barriers. The two 3 nm tick Al0.6Ga0.4As barriers are sandwiching a 4 nm thick GaAs quantum well. The conduction band profile is shown as orange line and overlayed with the TEM image. Due to the confinement potential of the two Al0.6Ga0.4As barriers, quantization of the energy occurs. The DBQW ground state wavefunction absolute square The energy of electrons in the emitter side with respect to the ground and/or excited energy states can be tuned by applying a bias voltage between emitter and collector contact. In terms of RTD-SPDs, the NDC region gives rise to a higher functionality as multiple operation modi can be used dependent on the external circuit or biasing condition. For example, the electrical gain provided by the NDC region can be used to drive high-speed oscillator circuits see c. With ff=2 THz , RTDs arf=2 THz ,25, and f=2 THz .RTD photodetectors are based on the principle that the resonant tunneling current can be influenced by introducing changes to their local electrostatic potential. Such a change in the local electrostatic potential can be induced by capturing optically generated minority charge carriers in the vicinity of the resonant tunneling structure at the collector-sided depletion region . These eAs a novel class of single-photon detectors, the detailed impact of the RTD-SPD heterostructure layer material properties on the device performance remains largely unexplored. The choice of a single design parameter of the epilayer stack typically influences multiple device parameters simultaneously. The doping profiles of the emitter and collector region can be considered a prime example. The high doping densities of the emitter side up to the resonant tunneling structure with a spacer layer of only a few nm will lead to increased current densities as well as lower operation voltages. However, the degradation of the peak-to-valley current ratio might be expected. In particular, the Geiger mode operation profits from large PVCRs. Conversely, the collector side depletion region determines the detection efficiency of the RTD-SPD. To ensure a maximum percentage of photogenerated minority charge carriers is captured for the accumulation in vicinity of the resonant tunneling structure, doping should be kept low and the collector side depletion region should comprise a lower bandgap energy absorption layer.There are numerous ways an RTD photodetector can be operated. The mode of operation determines how the RTD photodetector is controlled and read out. The most common way to operate an RTD photodetector is in the phototransistor mode, which is presented in One of the detection modes that exploits the RTD’s unique NDC region is the Geiger mode  ,42.RTD material and heterostructure design: [RTD leverage factor. The RTD leverage factor determines the efficiency with which the applied bias voltage shifts the energy level(s) of the quantized state(s) within the double-barrier quantum well with respect to emitter states. This takes into account the voltage drops across the various layers, interfaces and contacts. The In a first order approximation and assuming that capturing a photogenerated minority charge carrier is similar to charging of a plate capacitor,  design: ,28(2)ΔVThus, via Equations (1)–(3), we can evaluate the maximal device areas, RC limitations, operational speed, step height of RTD-SPDs, and the expected signal-to-noise ratio. Please note that we restrict our derivation to shot-noise only, which is dominant at in high-speed frequencies far of the 1/f noise contribution.0.3Ga0.7As barriers, a 10 nm thick GaAs quantum well, and self-assembled InGaAs quantum dots grown 4 nm after the DBQW. The sample was grown on an n-type Si-doped GaAs substrate with −3. The emitter (bottom) contact layer is formed by 340 nm of n-type-doped GaAs with a decreasing doping concentration of −3 to −3. The DBQW is separated from the emitter contact region by an undoped spacer layer with a thickness of 25 nm. Subsequently to the quantum dots, 300 nm of undoped GaAs were grown that serve as a depletion region in which photogenerated minority charge carriers (holes) will drift towards the DBQW. Here, they can be captured within the adjacent QDs. The sample was finalized with a 50 nm thick GaAs collector contact region with a doping concentration of −3.In this paper, we demonstrate the ability of Equations (1)–(3) to accurately determine current step heights needed for single photon detection. Even though there is no strict requirement for quantum dots adjacent to or within the resonant tunneling structure, single-photon detection in RTDs has been exclusively demonstrated in devices containing quantum dots. This might be surprising, considering that there are several advantages in using quantum wells instead of quantum dots for minority charge carrier trapping.In contrast to QDs that are distributed heterogeneously in position and energy, QWs form a well-defined homogenous layer across the growth surface, which allows for the reproducible fabrication of individual devices. The use of semiconductors such as GaAsSb can provide a deeper electric confinement potential of the quantum well in the valence band, while leaving the conduction band profile nearly unaffected. Stronger confinement of the photogenerated minority charge carriers is assumed to enable operation at even higher temperatures.e-lh at 790 nm and e-hh at 800 nm), the GaAs emitter and collector regions, and the GaAsSb quantum well. Similar to the QD-RTD, the QW-RTD was operated at To verify our hypothesis that single-photon detection is possible in RTDs without quantum dots, we grew an RTD with a heterostructure that is identical to that of 2 fW see c. From tWe showed that µm to sub-µm device geometries are favorable to ensure the electrical signal generated by a single photogenerated charge carrier is greater than the current noise (see Equation (3)) . At the Since predominantly minority charge carriers created in the collector-side depletion region contribute to the photodetection mechanisms, we highly recommend the incorporation of a lower bandgap absorption layer within the collector depletion region independent of the chosen detector architecture. The other epilayers should be chosen to have a bandgap energy larger than the photon energy of the targeted wavelength.2-sized active area can be manufactured and contacted. For the smallest devices, the optical aperture can cut-off a large fraction of the incident light power. Due to the relatively high reflection at the semiconductor-air interface and the short interaction length for incident light, the ring-contact geometry suffers from a low quantum efficiency. Higher quantum efficiencies can be achieved by integrating the RTD photodetector into a dielectric photonic crystal structure, such as a distributed Bragg reflector cavity [The ring-contact architecture is amongst the most used device geometries for RTD photodetectors. It is closely related to the standard LED or VCSEL design. An RTD mesa structure is defined by dry- or wet-chemical etching and an annular, ring-shaped contact is applied on top of the RTD mesa structure. The main advantage of the ring-contact architecture is its relative ease of fabrication with which RTDs with a µmr cavity ,43.In the integrated waveguide geometry, the light propagation occurs along an optical waveguide core and perpendicular to the electronic transport. A high quantum efficiency and detector bandwidth can be achieved simultaneously. RTDs integrated in optical waveguides were first employed as high-speed and low-voltage electro-absorption modulator ,45,46. LInspired by the rod cells of the human eye , the nan2-sized active areas [The RTD cross-wire geometry was introduced as a method to fabricate diodes with sub-µmve areas . Cross-wnt light ,59,60. H., Refs. ,61,62). ., Refs. . FurtherOne of the most severe limitations of RTD single-photon detectors and RTD photodetectors in general has been their comparably low detection (quantum) efficiency of only a few percent, or even less ,63,64,65−1 up to −1 plotted against the absorption length . The blue-shaded area marks the region covered by RTD photodetectors and single-photon detectors [etectors ,35,39,66−3) as well as the DBQW RTS and the subsequent 26 nm thick low-bandgap GaAs0.8Sb0.2 absorption layer. The GaAsSb absorption layer is placed at the field maximum in the center of the cavity to ensure optimal absorption.Cavity-enhanced photodetectors can significantly increase the detection efficiency of a photodetector at a target wavelength . Near-un2. The passivation was removed where the bottom intra-cavity contact was applied. The oxide-open areas beneath the bottom contact are clearly visible from the optical microscopy image.The DBR cavity-enhanced RTD photodetector can readily be fabricated in ring-contact geometry. Hadfield’s review article on single-photon detectors for optical quantum information applications to compare different detector technologies against each other [In this section, we assess the performance of RTD single-photon detectors in terms of spectral range, deadtime, dark count rate, detection efficiency, timing jitter, and the ability to resolve photon number. These are the figures of merit that are used in ch other .RTD-SPDs have been realized on both GaAs and InP substrates, therefore covering the visible and near-infrared spectral range including the telecommunication wavelengths ,64. WithThe deadtime d photon . The deaense see b because−1 have been demonstrated with negligible reduction in detection efficiency [The dark-count rate in RTD single-photon detectors has been among the lowest reported for any single-photon detector . Values RTD dark counts can be divided into virtual dark counts due to current noise, and actual dark counts due to minority charge carriers that had not been generated in a photon absorption process.Dark counts due to current noise become relevant in the phototransistor mode, when the current increment induced by a captured minority charge carrier is of the same order of magnitude as the shot noise or near the resolution limit of the read-out electronics.Actual dark counts are caused by minority charge carriers that originate from a process that does not involve photoexcitation due to the absorption of an incident photon. At low operation voltages, the main source is the intrinsic generation recombination current in the collector-side depletion region. For operation voltages exceeding dominant ,70. Hencdominant .The detection efficiency is the probability of a single incident photon to cause a registered detection event. The RTD quantum efficiency sets an upper bound to the detection efficiency but can further be limited by the read-out circuit. When using differentiating electronics to convert the current step into a trigger pulse, see b, the diRTDs are amongst the fastest electronic devices that have been manufactured by humankind. As such, they promise fast and precise detection, that is, a low timing jitter. Owing to the large RC-time constant of the circuit and the cross-wire geometry, the first RTD SPDs showed a relatively large timing jitter of about 150 ns . HoweverRTD single-photon detectors are inherently capable of photon-number resolution. The PNR capability of RTDs was already evident in the photocurrent–times traces shown in the pioneering work of Ref. , yet theT≤77 K .RTD single-photon detectors offer a unique and rich platform for photon counting with plenty of uncharted territory open for discovery to the curious researcher.