Acute lymphoblastic leukemia (ALL) is the most common cancer in children and one of the success stories in cancer therapeutics. Risk-directed therapy based on clinical, biologic and genetic features has played a significant role in this accomplishment. Despite the observed improvement in survival rates, leukemia remains one of the leading causes of cancer-related deaths. Implementation of next-generation genomic and transcriptomic sequencing tools has illustrated the genomic landscape of ALL. However, the underlying dynamic changes at protein level still remain a challenge. Proteomics is a cutting-edge technology aimed at deciphering the mechanisms, pathways, and the degree to which the proteome impacts leukemia subtypes. Advances in mass spectrometry enable high-throughput collection of global proteomic profiles, representing an opportunity to unveil new biological markers and druggable targets. The purpose of this narrative review article is to provide a comprehensive overview of studies that have utilized applications of proteomics in an attempt to gain insight into the pathogenesis and identification of biomarkers in childhood ALL. Acute lymphoblastic leukemia (ALL) is the most common cancer in children . It is aThe purpose of this narrative review article is to provide a comprehensive overview of published studies that have utilized applications of proteomics in an attempt to gain insight into the pathogenetic pathway and biomarkers discovery in childhood ALL. A thorough computerized search of the PubMed/Medline database was carried out along with research material from conference proceedings, publications from American Society of Hematology, European Hematology Association, and book chapters. Literature search on PubMed/Medline database was conducted, referring to manuscripts/studies published between 1 January 2010 and 31 January 2023. The last search was carried out on 30 March 2023 with the following keywords: “pediatric” or “children” or “childhood” AND “acute lymphoblastic leukemia” or “ALL” AND “proteomic profile” or “proteomics” or “proteome”. Search results were narrowed down to studies published in the English language. Exclusion criteria included studies exclusively conducted in adults, studies involving conditions other than ALL as well as abstracts without full-text articles. Relevance and duplicates were primarily assessed based on the title and abstract screening.The review comprises three relevant sections: an overview on the molecular basis of childhood ALL, an overview on proteomic analysis and a discussion of the applications of proteomics research in childhood ALL.Acute lymphoblastic leukemia is a hematologic malignancy of lymphoid origin and the most common childhood cancer representing about 25% of cancer diagnoses . The higAlthough environmental, immunologic, socioeconomic and epidemiologic factors have been evaluated rigorously as contributing factors to leukemogenesis, the exact underlying etiology remains unknown . Before TP53 mutations consistent with Li–Fraumeni syndrome occur frequently in low-hypodiploid ALL subtype [Gross chromosomal alterations in childhood ALL have been associated with outcome. Fluorescence in situ hybridization (FISH) assays and cytogenetics are used to identify structural chromosomal gains or losses in leukemic cells. High-hyperdiploidy (>50 chromosomes: 51–67 chromosomes) with trisomies of chromosomes 4,6,10,14,17,18,21, X occurs in almost 25% of childhood ALL cases and is associated with excellent outcome, even with reduced intensity chemotherapeutic regimens ,20. Low- subtype ,24.Chromosomal translocations represent a molecular hallmark of childhood ALL and represent a significant prognostic factor. Chimeric fusion genes are created by chromosomal rearrangements and involve epigenetic modifiers, tyrosine kinases and transcription factors . They caOther common rearrangements in B-ALL include: t resulting in TCF3-PBX1 (E2A-PBX1) fusion, rearrangement of KMT2A , and t (the Philadelphia chromosome) resulting in BCR-ABL1 fusion. While TCF3-PBX1 ALL was formerly linked to an intermediate or unfavorable prognosis, modern therapeutic regimens have enhanced outcome; thus, TCF3-PBX1 fusion is no longer considered for risk stratification . ChildreAn established molecular-targeted therapy paradigm in childhood ALL is Philadelphia positive (Ph+) ALL with the tq34;q11) resulting in BCR-ABL1 oncoprotein. Three BCR-ABL1 protein isoforms are encoded, the p210, the p190, and the p230, which have persistently enhanced tyrosine kinase (TK) activity. The BCR-ABL fusion gene of childhood and adult ALL have a different molecular basis, with the BCR-ABL fusion gene in adult ALL of the “p210” subtype resembling that found in chronic myeloid leukemia (CML), whereas the childhood subtype is mainly “p190” ;q11 resu,36. BCR-In contrast to B-ALL, the identified genetic alterations that occur in T-ALL do not add a substantial prognostic value in the established risk stratification of T-ALL based on CNS and MRD status . MutatioThe most common translocations in T-ALL involve fusion of T-cell receptor genes. Gene expression signatures define novel oncogenic pathways in T-cell ALL, but their prognostic significance remains unidentified. Although stimulating advances have occurred regarding the genomic characterization of T-ALL, development of precision medicine treatment approaches for T-ALL has proven more challenging .Approximately 20% of pediatric ALL patients experience a relapse with a survival lagging behind newly diagnosed ALL. Major pathways of lymphoid development, kinase signaling, cell cycle regulation and epigenetic modification are involved in the genetic basis of relapsed ALL . MoleculRelapsed and refractory disease pose extreme therapeutic challenges, demonstrating an unmet need for the development of durable therapies. Recent advances in immunotherapy with CD19 inhibitors and CD22 inhibitors  and chimeric antigen receptor (CAR)-T cell therapy, have reformed the management of relapsed and refractory ALL with the price of serious adverse events, such as cytokine release syndrome, immune effector neurotoxicity syndrome, prolonged BM suppression and hypogammaglobulinemia . They ofProteomics studies the structure along with the function of the proteome . The terThe general strategy pursued in proteomics is to compare related samples from different disease stages considering that differences in their proteome could reflect a different disease stage. Proteomic studies are carried out mainly in body fluids such as the cerebrospinal fluid (CSF), peripheral blood (PB) and BM. Body fluids exhibit a great emerging potential for biomarker studies, in particular those that can be collected by minimally invasive techniques ,61. The Biomarkers are recognized using mass spectrometry (MS) . Mass spThere are two different methodological approaches in proteomics. The first, known as top-bottom, is the discovery of a protein through its selective isolation, the characterization of its sequence and structure and the study of function, regulation, interaction and PTM. The second is the bottom-up or the so-called “shotgun” aiming to identify all the proteins present in a sample. In shotgun proteomics, which is a gel-free liquid chromatography (LC)-MS approach, it is essential to know a protein’s identity before quantification, as peptides need to be related to each other and to their parent proteins; only then is protein quantification possible. Therefore, gel-based proteomics usually identifies only proteins with different abundances, while LC-MS identifies all detected proteins . CurrentSince the hallmark of ALL is the uncontrolled clonal proliferation of poorly differentiated lymphoid progenitor cells inside the bone marrow, interfering with the production of blood cells, serum and plasma may serve as rich sources of blood cancer-associated biomarkers. In an attempt to determine potential disease markers in childhood B-ALL, a Colombian exploratory study group performed a proteomic study implementing LC-MS/MS and quantification by label-free methods searching for proteins differentially expressed be-tween healthy children and children with B-ALL. They quantified 472 proteins in depleted blood plasma and found that 25 proteins were differentially expressed .Moreover, differential proteins were analyzed by MALDI-TOF-MS and were identified in lymphocytes in patients with childhood ALL and healthy children, by Wang et al. . Among tCandidate biomarkers for early diagnosis of B-ALL were overexpressed in a proteomic analysis with lectin affinity chromatography LC-MS of serum from pediatric patients with B-ALL performed by Cavalcante et al. . A totalIdentification of tumor autoantibodies may be utilized in early cancer diagnosis and immunotherapy. Serological proteome analysis (SERPA) is another proteomic approach and screening autoantibodies as serum biomarkers of B-ALL using SERPA with combination of 2-DE, immunoblotting and MS revealed that α-enolase and VDAC1 autoantibodies were promising biomarkers for children with B-ALL. Evaluation of serum autoantibodies against α-enolase and VDAC1 show promising clinical applications .Braoudaki et al. . evaluatXu et al. . performJiang et al. . using pHu et al. . hypotheResistance to chemotherapeutics used in ALL is a major challenge and involves com-plex cellular processes. Guzmán-Ortiz et al.  studied Leukemia studies aim to decipher the mechanisms, pathways and the degree to which the proteome impacts leukemia subtypes and to identify whether disease stratification based on proteome features could provide precise targets for therapy. Strategies of phosphoproteomics can be used to profile the activation/deactivation of crucial molecules in signaling pathways which are key to the progression, remission and relapse of leukemia, since leukemogenesis is controlled via the regulation and interaction of signaling cascades ,85. A coThe JAK/STAT pathway have also been implicated in the oncogenesis of many cancers as well as of childhood leukemia . A JAK mHigh hyperdiploid B-cell ALL and ETV6/RUNX1-positive pediatric ALL are among the most common subtypes of childhood leukemia. In a study by Yang et al. . it has Children with T-ALL display resistance in glucocorticoid treatment. Serafin et al. identified, by reverse-phase protein arrays, that lymphocyte cell-specific protein-tyrosine kinase (LCK) was aberrantly activated in PPR patients . They alPhosphoproteomics is designed to provide information on pathway activation and signaling networks and offer opportunities for targeted therapy . In a reStudies on the comparative analysis between the bone marrow tumor microenvironment and the peripheral blood are very important to decipher the ALL biology. Overarching challenges of the hidden mechanisms behind immature lymphoid cells accumulation in the bone marrow and the mechanisms underlying the chemotherapy effects against B-ALL will shed light on the leukemia biology and the cumulative impact of chemotherapy . A recenNoteworthy, interesting results were depicted in a recent study by Leo et al. . who perCentral nervous system involvement remains one of the major causes of ALL treatment failure ,106. DesSome of the proteins are likely to play a vital biological role as biomarkers for the development of ALL, with diverse biological functions after induction chemotherapy. It is noteworthy that those altered proteins should be further investigated as predictive markers of ALL with CNS infiltration, some of which may have the prospect of becoming new therapeutic targets in childhood ALL with CNS involvement. Interesting results have been reported from an exploratory study by Yu et al. . who invChildhood ALL is a biologically heterogeneous disease characterized by structural alterations, genetic and somatic mutations through a process of complex protein-based signaling network pathway modifications. Changes in protein expression can partially be determined by the analysis of the static genome. Although implementation of next-generation genomic, transcriptomic, and epigenetic sequencing tools unveiled the genetic landscape of childhood ALL, uncovering the underlying dynamic changes at a protein level still remains a challenge.Proteomics offers complementary information to genomics and transcriptomics by analyzing protein structure, expression, and modification status. Advances in the field of MS enables high-throughput collection of global proteomic profiles representing an opportunity to discover new biological markers and druggable targets. Novel disease-specific biomarkers will provide an additional reference for predicting treatment responses and individual prognosis. Deeper characterization of biomarkers and molecular pathways, especially in patients with relapsed/refractory disease, will ultimately identify precision medicine candidates for application of translational precision therapy.


The fuzzy scoring function of the entire host–pathogen network has been processed with ~180 million potential interactions generated from 19,281 host proteins and around 242 viral proteins. ~4.5 million potential level one host–pathogen interactions are computed based on the estimated interaction affinity threshold. The resulting host–pathogen interactome is also validated with state-of-the-art experimental networks. The study has also been extended further toward the drug-repurposing study by analyzing the FDA-listed COVID drugs. SARS-CoV-2 is a novel coronavirus that replicates itself via interacting with the host proteins. As a result, identifying virus and host protein-protein interactions could help researchers better understand the virus disease transmission behavior and identify possible COVID-19 drugs. The International Committee on Virus Taxonomy has determined that nCoV is genetically 89% compared to the SARS-CoV epidemic in 2003. This paper focuses on assessing the host–pathogen protein interaction affinity of the coronavirus family, having 44 different variants. In light of these considerations, a GO-semantic scoring function is provided based on Gene Ontology (GO) graphs for determining the binding affinity of any two proteins at the organism level. Based on the availability of the GO annotation of the proteins, 11 viral variants,  The emerging coronavirus (CoV) pandemic has sparked a flurry of research into the SARS-CoV-2 virus and the COVID-19 disease it causes in people . A coronAlong with humans, it also affects mammals and birds. Even though the coronavirus typically causes the common cold, cough, etc., it also causes severe acute, chronic respiratory disease, multiple organ failure, and, ultimately, human mortality. Before SARS-CoV-2, the two primary outbreaks were Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Southern China was the location of SARS’s inception. Its fatality rate was between 14 and 15% [Regarding biology, the three epidemic-starting viruses, SARS, MERS, and SARS-CoV-2, belong to Coronaviridae’s genus Beta coronavirus. Proteins that are both structural and non-structural contribute to the development of SARS-CoV-2. Out of the two, structural proteins such as the spike (S) protein, nucleocapsid (N) protein, membrane (M) protein, and envelope (E) protein play a crucial part in spreading the disease by binding with receptors after entering the human body . The primary factor which needs to be considered while examining the disease transmission process from SARS-CoV-2 to humans is the Protein–Protein Interaction Network (PPIN). It is critical for determining essential proteins and functions ,17,18,19A beta-CoV prevalent in wild mice, the mouse hepatitis virus (MHV) or Murine-CoV is similar to SARS-CoV-2. In-depth research has been done on laboratory MHV strains to understand host antiviral defense systems and coronavirus virulence factors . Murine-The wide variety of mammalian and avian species that coronaviruses have been found to infect and the highly varied disease syndromes they cause are well known. One of the well-known traits of several CoVs is variable tissue tropism, which also allows them to overcome interspecies boundaries easily. Betacoronaviruses, known as bovine CoVs (BCoVs), cause shipping fever, winter dysentery in older cattle, and neonatal calf diarrhea. Interestingly, there have not been any specific genetic or antigenic markers found in BCoVs linked to these unique clinical disorders. BCoVs, on the other hand, are quasispecies that coexists with other CoVs. In addition to cattle, BCoVs and CoVs resembling cattle were found in several domestic and wild ruminant species, dogs, and humans . The pneTylonycteris pachypus) most closely, as well as the bat coronaviruses HKU4 and HKU5 [Two separate teams reported finding SARS-like CoVs (SL-CoVs) in bats in 2005, and they hypothesized that bats were SARS-CoV natural reservoirs ,44. Mostand HKU5 ,48. The and HKU5 ,50.A large-scale PPI network of an organism provides valuable clues for understanding cellular and molecular functionalities, and signaling pathways can provide crucial insights into the disease mechanism, etc. Much biological information is available and encoded in different ontologies called Gene Ontology. Semantic similarity is the degree of relatedness between the two biological entities (Gene/Protein) based on GO annotations that provide a quantitative measure of their GO-level relationship . Differestate-of-the-art database.From the above discussion, it is clear that several similar studies based on GO information have been done on host–pathogen interaction networks. However, a complete PPIN must be identified for humans and different coronavirus organisms to detect probable human targets from all perspectives. So, in this study, the interaction affinity between the protein pairs from the different organisms of the coronavirus family and human spreader proteins is calculated using the available ontological information using the proposed in-silico model. A GO-based Graph theoretic model is proposed to determine the interaction affinity between the host–pathogen protein pairs for humans and different coronavirus organisms. Currently, 19,281 human proteins have GO annotations, whereas around 242 viral proteins are obtained from a selected organism having GO annotations. Based on the above data, level 1 interactors generates ~4.5 million potential host–pathogen interaction. The variety and veracity issue plays a significant role in such a large-scale dynamic PPI network. Handling large, dynamic, heterogeneous networks using in-silico methods is tedious. Therefore, an Apache Spark-Based analytical study is proposed to compute the interaction affinity in large-scale protein–protein interaction networks using the Gene Ontology (GO) graph.“is_a” and “part of” GO graphs are considered for semantic score computation. Considering the similarity between all the GO pairs, the semantic similarity of the protein pairs can be estimated. The shortest path length between a pair of terms in a GO graph and the average information content (IC) [DsjCA) of the respective GO term [AnC(t) is the ascendant term for t and DnC(t) is the descendent term of t. No is the total number of GO terms in ontology O, and PrT(t) is the proportion measure of term t. The GO keywords chosen as cluster centers are those for which this proportion metric is higher than a certain threshold. The cluster centers in this study are selected using the proposed threshold values [ic is the thi cluster center, x is the shortest path length, and k is the width of the membership function. If no path from any GO term to a cluster center is found, then the membership of the GO term with respect to that cluster center will be considered 0. Similar membership for any target GO pair indicates very closely related concepts of GO functionality, and widely related membership value represents separated concepts. For any target pair of GO term , a weight parameter is introduced to estimate these differences in membership. The weight parameter is thus defined by maxD represents the maximum difference in membership values of GO pair  across all cluster centers of any particular GO graph type(CC/MF/BP).Combining the similarity scores of the GO terms connected to the proteins will yield an estimate of the semantic similarity between two interacting proteins ,66,69,70ent (IC)  of the d GO term ,70 measuIC) based information of the disjunctive common ancestor (DsjCAs) of any GO graph is more significant in the semantic similarity assessment of two GO terms [IC of any GO term t, with respect to a GO graph, g is defined as ICg(t) = −log(Pr(t)). The probability Pr(t) is the occurrences of term t with respect to the total annotations of GO graph g. The occurrences of term t depend on its annotations over the protein corpus. Using the IC of the DsjCA, the shared information content (SIC) is computed for the target GO term pair . The SIC is computed asThe information content  for each GO type . The average of the CC, MF, and BP-based semantic similarity is used to define the protein pair’s interaction affinity . When comparing the annotations of the proteins Alpha-, Beta-, Gamma-, and Delta-CoV are the four genera that comprise the enormous family of enveloped positive-strand RNA viruses known as coronaviruses (CoVs). Among all the 44 organisms of coronavirus, here in this work, only 11 organisms have been considered based on the available GO-annotated proteins. The human is considered the host, and the work mainly suggests the affinity of host–pathogen interaction for different coronavirus organisms. Below, a brief description of all selected organisms is given.All potential interactions between human proteins that have been experimentally verified in humans make up the dataset ,72. The SARS-CoV-2 is a biological member of the Coronaviridae, which belongs to the genus Beta coronavirus. The virus contains four structural proteins, namely envelop(E) protein, membrane(M) protein, nucleocapsid(N) protein, and spike(S) protein, which helps in binding with receptors after entering the human body and has a crucial function in spreading the disease . Here thSARS-CoV is a highly pathogenic and zoonotic virus that causes severe respiratory illness, gastrointestinal, neurological, and fatalities among humans ,75,76. TMERS-CoV is also a member of Beta-Coronavirus. It is an even more pathogenic and zoonotic virus in comparison to SARS-CoV. MERS-CoV immerged around 2012 in the Arabian Peninsula with very high transmissibility by affecting more than 2000 people . The datBat coronavirus HKU3 from UniProtKB, having 12 proteins.Surveillance research in Hong Kong among non-caged animals from wild regions found that a closely similar bat coronavirus, SARS-related Rhinolophus bat coronavirus HKU3, was the natural animal host . We haveBat coronavirus (Bt-CoV/Rp3/2004) suggests that the primary reservoir Rhinolophus ferrumequinum may infect secondary reservoirs, domestic and animals living in Italy [With the high geographic spread and species variety, bats represent an order with significant evolutionary success. Bats are the natural reservoirs of several viruses closely related to SARS-CoV . A searcin Italy .An enclosed, positive-sense single-stranded RNA mammalian Group 2 Betacoronavirus called bat coronavirus HKU5 (Bat-CoV HKU5) was found in Japanese Pipistrellus in Hong Kong. This coronavirus strain is closely related to the recently discovered novel MERS-CoV, which is to blame for the coronavirus outbreaks linked to the Middle East respiratory illness in 2012 ,82. Tylonycteris bat coronavirus HKU4 (Bat-CoV HKU4), a member of Betacoronavirus, is an enveloped, single-stranded virus having a genetical similarity with MERS-CoV or HCoV-EMC. The main difference between HCoV-EMC and Bat-CoV HKU4 lies in between the spike protein (S) and envelop (E) protein, where HCoV-EMC have five ORFs instead of four with low amino acid identities to Bat-CoV HKU4 . The humThe spike (S1) and RNA-dependent RNA polymerase proteins of MERS-CoV were subjected to phylogenetic analysis, which indicated that the virus is linked to bat viruses. Coronavirus surveillance investigations in several populations of bats have shown that they are potential reservoirs for this unique virus . DiffereMurine coronavirus (M-CoV), a member of the Betacoronavirus family having Embacovirus subgenus, is mainly found responsible for infecting rats [Murine coronaviruses come in over 25 distinct strains. These viruses, which spread by the fecal-oral or respiratory routes and infect mice’s livers, have been utilized as an animal disease model for hepatitis [ing rats ,88. Enteing rats . Murine epatitis . The strepatitis . Bovine coronavirus (BCoV) is a member of Betacoronavirus 1, and it can infect both cattle and humans [d humans ,93. It id humans ,95. BCovd humans . BCoV cod humans . A phospd humans .Rat coronavirus (RCoV), subset of Murine coronavirus, is also a single stranded RNA virus belonging to Betacoronavirus family which is responsioble for infecting rats [ing rats . The resing rats . When a ing rats ,103,104.state-of-the-art datasets. Any computational model must always consider the input and output source, and our suggested model is no exception.Our developed in-silico model contains the protein interaction affinity between humans and different organisms from the coronavirus family. The in-silico model is validated by identifying the overlapped edges with reference to the Three different forms of GO hierarchical connection graphs can be used to use the GO information to infer the binding affinity of each pair of interacting proteins  . Our proThe 2019 coronavirus disease pandemic was brought on by the novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/nCoV). It affected over 12 million people and caused over 560,000 fatalities in 213 nations . To infeGordon et al.  proposedApart from the high-confidence host–pathogen protein interaction network dataset, Gordon et al. also provided a host–pathogen interaction dataset that contains a human-nCoV protein interaction network without any threshold. This mainly contains scoring results of all bait and all prey proteins showing spectral counts of experimental samples. The dataset contains 22,153 interactions, including 27 bait and 2753 host proteins. Our proposed model generates an interaction network with the said protein, which generates all-vs-all interactions. Among those 22,153 interactions, there are 7866 existing host–pathogen interactions whose scores are calculated. viz. human–human ppin, human–nCoV ppin, and nCoV–nCoV ppin). The edge-overlapping has shown the validation of our computational model between two datasets at different threshold values set on the fuzzy score. Edge overlapping signifies the common edges present in both datasets. For our experiment, we have kept the fuzzy score threshold ranging from 0.1–0.001. At first, we compare our network with the high-confidence human–nCoV network proposed by Gordon et al. The dataset contains 332 host proteins and 27 viral proteins. To validate our computational model, we compare our data set with that proposed by Gordon et al. . To expeThe high-confidence dataset and the other dataset proposed by Gordon et al., which contains scoring results of all bait and all prey proteins showing spectral counts of experimental samples, are also being compared in the same manner discussed above with varying threshold values imposed on fuzzy interaction affinity score. The threshold ranges from 0.1–0.001. The dataset proposed by Gordon et al. contains 2753 host proteins and 27 viral proteins. Protein-protein Interaction Prediction Engine (PIPE) is a sequence-based PPI prediction approach that looks at sequence windows on each query protein proposed by Dick et al. . The eviLike PIPE, the SPRINT predictor gathers data from previously reported PPI interactions based on window similarity with the query protein pair to determine its prediction scores . SPRINT Here, the two datasets produced by Dick et al.  are beinBat coronavirus HKU3, Bat coronavirus Rp3/2004, Bat coronavirus HKU5, Bat coronavirus HKU4, Bat coronavirus 133/2005) forms one group, and Murine-CoV, Bovine-CoV and Rat Coronavirus forms the third group. Then we identified the common host proteins from all three groups separately. Intersected host protein sets from all three groups are identified and again intersected. This results in the common vulnerable host proteins at the specified threshold value. For visualization, we only arbitrarily select a threshold value of 0.1 for constructing the Venn diagram, 0.1 threshold value gives 191 vulnerable host proteins interacting with all selected coronavirus organisms.One of the main focuses of our research is to identify the common vulnerable host proteins at different threshold values. As discussed in All level one human proteins of the coronavirus family are mapped with their matching medicines from DrugBank once the coronavirus family–human PIN has been created . DrugBanIt has around 60% of FDA-approved medications and 10% of investigational drugs. It has been determined through adequate analysis that some spreader nodes in COVID19-human PPIN are the protein targets of possible COVID-19 FDA-listed medicines : hydroxyThe DCS, or frequency of each drug, is therefore calculated. The number of vulnerable host proteins at different threshold values is represented in pro) active-site region [Drug repurposing is a powerful strategy that gives new therapeutic alternatives by identifying other uses for already-approved medications, as vaccine and drug development can take years . The trae region . Zinc supplements also play a crucial role in combating different organisms of coronavirus. The essentiality of Zinc lies in the preservation of natural tissue barriers such as the respiratory epithelium, preventing pathogen entry for a balanced functioning of the human immune system. The deficiency of Zinc can probably lead to the infection and detrimental progression of COVID-19 . The bodIn COVID-19, Zinc supplementation was hypothesized to reduce mortality. Supplementing with Zinc had no positive effects on how the illness progressed. The Zinc-supplemented group’s hospital stay was lengthier. There is no evidence to back up regular Zinc supplementation in COVID-19 . The conPromethazine, an antipsychotic agent showing clathrin-mediated endocytosis, is one most effective drugs for SARS-CoV and MERS-CoV, which has been repurposed for the treatment of COVID-19 as there is almost 89% genetic similarity with SARS-CoV-2 and SARS-CoV . Two pilBased on this validation, further research on the repurposed drug, docking study, and other symptomatic analyses will help to identify the potential drug for the entire coronavirus family. A clinical study on Promethazine and Fostamatinib ,132 is astate-of-the-art dataset. It has been noticed from this assessment that the chosen human spreader nodes, indicated by our suggested model, emerge as the possible protein targets for the different organisms of coronavirus medications authorized by the FDA, which highlights the significance of this proposed work. Finding spreader nodes in any network of host–pathogen interactions is essential for predicting the course of a disease. However, not every protein in a network of interactions is highly capable of transmitting illness. In this work, we used the host–pathogen protein interaction network between humans and different coronavirus family organisms. Based on the available GO annotations of the proteins, a fuzzy interaction affinity score has been proposed for all the host–pathogen interactions. Our proposed model was validated with the The basic hypothesis of the work is listed as follows: (1) Between SARS-CoV and SARS-CoV-2, there is a genetic overlap of around 89%, which also results in a substantial overlap in spreader proteins between human–SARS-COV and human–SARS-COV2 protein-interaction networks . Moreovestate-of-the-art datasets. According to recent research by Gordon et al., who focused on the sequence analysis of SARS-CoV-2 isolates, 332 high-confidence SARS-CoV-2–human protein–protein interactions have been discovered. Using affinity-purification mass spectrometry, they determined the human proteins that were physically linked to each of the 26 of the 29 SARS-CoV-2 proteins after they had been cloned, tagged, and produced in human cells [Our proposed in-silico method for identifying host–pathogen protein interaction networks has been validated through different an cells . While van cells . In addition, our approach is not directly deal with the classification problem and does not require prior knowledge of positive and negative interaction. Further, several experiments show that Gordon et al. do not detect all the significant human–nCoV interactions ,134. ForThe target proteins of the possible FDA medications for the coronavirus family coincide with the spreader nodes of the hypothesized human–coronavirus protein interaction network, which may highlight one of the study’s major findings. Based on the DCS score applied on vulnerable host proteins identified at different threshold values, we have proposed a list of FDA-approved drugs such as Fostamatinib, Copper, Zinc Acetate, Zinc Chloride, etc. Our previous research has proposed Fostamatinib as a potential drug for COVID-19. This analysis demonstrates that these spreader nodes have biological importance in transmitting illness. Additionally, it spurs us to do medication repurposing research which focuses on the fact that apart from Fostamatinib, Promethazine can also be one of the potential drug candidates for coronavirus-related diseases under clinical trials. In a nutshell, the proposed methodology forms a complete PPIN for humans and different coronavirus organisms and adds much more relevant biological information about existing drugs against SARS-CoV-2 through a drug-repurposing study done with proper assessment and in-depth computational study.


Encapsulation of Doxorubicin (Dox), a potent cytotoxic agent and immunogenic cell death inducer, in pegylated  liposomes, is well known to have major pharmacologic advantages over treatment with free Dox. Reformulation of alendronate (Ald), a potent amino-bisphosphonate, by encapsulation in pegylated liposomes, results in significant immune modulatory effects through interaction with tumor-associated macrophages and activation of a subset of gamma-delta T lymphocytes. We present here recent findings of our research work with a formulation of Dox and Ald co-encapsulated in pegylated liposomes (PLAD) and discuss its pharmacological properties vis-à-vis free Dox and the current clinical formulation of pegylated liposomal Dox. PLAD is a robust formulation with high and reproducible remote loading of Dox and high stability in plasma. Results of biodistribution studies, imaging with radionuclide-labeled liposomes, and therapeutic studies as a single agent and in combination with immune checkpoint inhibitors or gamma-delta T lymphocytes suggest that PLAD is a unique product with distinct tumor microenvironmental interactions and distinct pharmacologic properties when compared with free Dox and the clinical formulation of pegylated liposomal Dox. These results underscore the potential added value of PLAD for chemo-immunotherapy of cancer and the relevance of the co-encapsulation approach in nanomedicine. The fin111In]In-PLAD. Mice underwent SPECT/CT imaging at 30 min, 24 h, 48 h, and 72 h post-injection. SPECT imaging was performed with a four-headed multiplexing multipinhole NanoSPECT/CT  using Aperture 3 (1 mm pinholes). A 96 mm field of view comprising the animal from the tip of the nose to the end of the back legs was used, with an energy peak of 171 and 245 KeV ± 10% keV. The acquisition time was adjusted to range from 40 to 80 s, increasing it to compensate for the isotope decay at later time points. A 21-min 360-frame CT image was performed immediately before or after the SPECT acquisition. Reconstruction of the images was performed, including attenuation correction, using the software Scivis HiSPECT version 1.4.1876  with standard parameters. Reconstructed data from SPECT and CT were co-registered using ViVoquant 2020  for further analysis and interpretation.We conducted an imaging study on a WEHI-164 subcutaneous mouse tumor model. After 10–14 days of subculturing, WEHI-164 cells were harvested, and two million cells were inoculated subcutaneously unilaterally in the shoulder of BALB/c mice 8–9 weeks old . On day 9, after inoculation, the mice were injected i.v. by tail vein bolus injection with ca. 10 MBq In-PLAD. Each mouse received a total dose of 4 µmol of lipids by combining [111In]In-PLAD with empty liposomes of the same composition and physicochemical properties  but lacking doxorubicin/alendronate. After intravenous injection, mice were imaged by SPECT-CT  in BALB/c mice inoculated with the WEHI-164 tumor model. As indicated in the Methods section, PLAD was radiolabeled with the gamma-emitter indium-111  T lymphocytes from human donors in an in vivo human tumor model demonstrated a significant antitumor effect of this combination . MoreoveWe therefore conducted experiments to investigate the activity of PLAD in combination with human gamma-delta T cells in a human breast cancer mouse tumor model. As seen in Co-encapsulation in a stable nano-formulation of two active agents, preferably with non-overlapping toxicities and synergistic effects, is a unique advantage of nanomedicines. By space and time co-delivery of two drugs with otherwise different pharmacokinetic-biodistribution profiles, we can exploit combination therapy at its best and achieve optimal synergistic activity. As mentioned in the Introduction section, a clinical example is a liposome-based formulation of cytarabine and daunorubicin at an optimized 5:1 drug-to-drug ratio, known as Vyxeos™, approved for the treatment of adult AML . In thisThe starting point for the formulation is the well-known PLD formulation approved for ovarian and breast cancer and widely used in the clinic for more than 20 years with a great safety record . DespiteIn the said study by Islam et al. , PLAD an89Zr, 111In, 67/68Ga, 64Cu, and 52Mn, and hence has high potential for other therapeutic radionuclides. This property confers the possibility of reliably tracing PLAD biodistribution noninvasively [111In or 89Zr [PLAD offers other advantages in the field of theranostics since Ald is a potent chelator of various metal radionuclides that are used in nuclear medicine for SPECT and PET-CT imaging, such as vasively  and perhvasively . PLAD co or 89Zr . In factThe enhanced tumor deposition and retention of drugs delivered by long-circulating liposomes has been well established and is referred to as the enhanced permeability and retention (EPR) effect ,49,50. BIt is increasingly recognized that therapy aimed at killing cancer cells  is insufficient for inducing durable cancer remissions and that mobilization of the adaptive immune response against cancer cells is necessary. Immunotherapies such as immune checkpoint inhibitors can produce complete remission in metastatic cancer patients who remain relapse-free for years ,53. NoneCo-encapsulation of ALD and DOX in pegylated liposomes leads to a chemo-immunotherapeutic, multi-modality platform with non-overlapping toxicity and with a unique mechanism of activity that may have a profound impact on cancer therapy. These results open the way for further development of PLAD towards clinical applications of a unique product that blends chemotherapeutic and immunomodulating properties.


The tribological assessment was carried out in ambient environmental conditions and high contact pressures in a ball-on-disc experimental set-up. The evaluation yielded that the use of Ti3C2Tx-Graphene-Oxide coatings led to substantial reduction in friction down to 0.065 (at 1 GPa contact pressure and 100 mm/s) in comparison to the uncoated of single-component-coated surfaces, surpassing the state-of-the-art. The coatings also provided excellent protection against wear loss of the substrate and counter-face. The results were explained based on the observations from Raman spectroscopy, scanning electron microscopy, transmission electron microscopy, and nanoindentation measurements. In operando formation of a dense, hard and stiff, dangling-bond-saturated tribolayer was observed to be the reason for the sustained lubricity even at high test loads and sliding speeds. This report presents the holistic exploration and correlation of structure-property-processing pertaining to the advancement of solid lubrication science.Development of solid lubricant materials that render reliable performance in ambient conditions, are amenable to industrial size and design complexities, and work on engineered surfaces is reported. These coatings are composed of Ti Solid lubrication is also of interest to extra-terrestrial applications17 as demonstrated by the systems and technologies developed for the Mars rovers and international space station components18. Commercially successful, robust solid lubrication systems such as diamond-like carbon20, sputter deposited 24, or other layered  have pushed the boundaries of oil-free lubrication, even in harsh environments such as humid and high-temperature applications27. Although these coatings and materials technologies meet the needs of niche applications, the quest for simpler development techniques that are cost-effective and robust under multifarious test conditions is ongoing.Solid lubrication technologies have garnered significant research interest from both fundamental research aspects of materials design30 has emerged. MXenes are layered transition metal carbides, nitrides, or carbonitrides, that have shown exceptional physical31, mechanical36, energy, chemical and electrochemical40, bio-imitating43, optical44 and tribological properties48. Recent reports explore the dry lubrication properties of MXenes and MXene-based coatings in high TRL examples such as roller bearings, thrust ball bearings under ambient conditions54. Recent publication showed superlubric behavior of MXene-based coatings in dry nitrogen atmosphere, with very low dew-point55. Despite these advancements, there is a knowledge gap in realizing pathways enabling high lubricity in ambient/humid conditions, as seen in common place applications. The role of surface and terminal bond passivation is not as consequential when tested in inter atmospheres, as compared to humid conditions. Other equally important variables include microstructural morphosis, and chemical bond changes in tribological contacts, all of which affect the application of MXenes in humid and ambient environment applications. In addition to demonstrating impressive metrics of improved wear-resistance and lubrication, it is perhaps more important to explore and understand the modus operandi to pave way for continual advancement. This report presents the results of synthesis of an MXene-based solid lubricant coating to render low friction, excellent wear loss prevention, and prolonged performance in ambient conditions. The development of the lubricant coatings itself is kept simple and scalable. In addition to demonstrating the lubrication properties, the mechanisms were explained using electron microscopy, nanoindentation, and Raman spectroscopy techniques. Correlations between structural, chemical, physical, and mechanical properties are also discussed. This multivariate analysis is believed to offer insights into hitherto unexplored aspects of materials tribology and, specifically, engineered tribolayer formation, and to advance solid lubrication science at large. Such would not only be of interest to fundamental research but also serve as a template for accelerated lubricant materials discovery in the applied domain.In the context of layered materials, a new class of material systems, having a chemical formula of 3C2Tx) powder obtained from Nanochemazone  was suspended in ethyl-alcohol at 35 g/L concentration, and was mixed with Graphene-Oxide aqueous suspension (5 g/L concentration) obtained from Graphene Laboratories Inc.  in 1:1 v/v to form the suspension containing solids-lubricant materials in 1:3 ratio. The suspension containing the solid lubricant materials was spray coated using pneumatic spray-coater with dry nitrogen at 5 psi line pressure on to a 52100-steel substrate having a hardness of 60 HRc, average surface roughness of Ra = 30 nm, pre-heated to heated to 80 °C. The temperature was maintained such that the carrier liquid evaporated immediately upon contact with the substrate depositing the solids, simultaneously not altering the starting materials’ morphology or tempering the steel substrate. Scrapes from the substrate were lodged onto the lacy-carbon copper grid and imaged using JEOL 2000F transmission electron microscope. The lubrication performance of the coatings was assessed using Anton Paar tribometer in unidirectional sliding mode at 1 N, 10 N and 20 N sliding against 6 mm diameter hardened 52100 steel ball . Each tribological (sliding) test was performed at least three times. The total sliding distance was kept constant at 30 m, and a velocity at 100 mm/s. Morphology of as-received materials, and tribopairs were imaged using FEI Quanta 200 scanning electron microscope at 5 kV beam voltage. Raman spectroscopy was performed using inVia Renishaw instruments with blue laser (457 nm). Changes in the hardness and modulus of the coating were quantified using the iNano nanoindenter, from KLA Instruments . The indentations were made with a diamond Berkovich tip at 10,000 mN load in a continuous sensing mode. A Filmetrics Profilm3D Optical Profilometer was used to generate the 1D and 3D surface, and used to calculate the ball wear and flat rates. Each wear track and ball radius measurements were repeated five times. VersaSCAN micro-scanning electrochemical workstation with scanning kelvin probe (SKP) module was used for relative work function measurements. A tungsten probe was used as a reference for the SKP measurements.Pristine micro-crystalline MXene , just MXene (by 71%), or just Graphene Oxide (by 64%) even though the later two test coupons were prepared using the same processing conditions and lubricant amount on the surface. While the pristine materials’ lubrication properties are in line with previous reportsThe scanning electron microscopy micrograph of the counterface surface is shown in Fig. 61. Literature indicates that materials with low relative work function, identified as active, anodic or having unsaturated terminal bonds tend to be electron transfer sites64 resulting in stiction and adhesion, in contrast to inert or passive phases that by virtue of higher work-function, or, bond saturation resist such interactions, effectively resulting in lower friction during sliding71. The SKP data after the sliding experiments is shown in Fig. in operando formed multi-layer Graphene Oxide or graphitic carbon phase, as seen from the Raman spectrograms are known to have higher electron work function compared to single or few-layer graphene, graphene oxide, or reduced graphene oxide73, aligning with the observed lowered stiction and better lubricious behavior. The results from Figs. The changes in the structure and bonding of lubricant on the counterface Fig. a and weain operando transformation of materials in the tribolayer that contributed to the sustained lubricity performance. These mechanistic transformations are shown in Fig. The tribomechanical response measured using nanoindentation is shown in Fig. 3C2Tx and Graphene Oxide synthesized using a spray-coating process. The coating was observed to provide excellent wear resistance on the substrate, and no detectable wear loss on the counterface ball. The friction values were significantly lower as compared to the state-of-the-art materials tested in ambient temperature and humidity conditions in contact pressures over 1 GPa. This behavior was explained based on observations from white-light-interferometry, scanning and transmission electron microscopy, Raman spectroscopy , and nanoindentation measurements, as the formation of a robust tribolayer that was composed of MXene and graphitic carbon transformed from Graphene Oxide compaction, which prevented metal-on-metal contact. This tribolayer was characterized to possess high hardness, stiffness, and surface passivation that enabled excellent lubrication behavior. The success of this simple coating synthesis advances the technology readiness of solid lubricants for complex and real-world applications.This study reported the wear and friction behavior observed for a novel binary composite of Ti


While laboratory testing for infectious diseases such as COVID-19 is the surveillance gold standard, it is not always feasible, particularly in settings where resources are scarce. In the small country of Lesotho, located in sub-Saharan Africa, COVID-19 testing has been limited, thus surveillance data available to local authorities are limited. The goal of this study was to compare a participatory influenza-like illness (ILI) surveillance system in Lesotho with COVID-19 case count data, and ultimately to determine whether the participatory surveillance system adequately estimates the case count data.A nationally-representative sample was called on their mobile phones weekly to create an estimate of incidence of ILI between July 2020 and July 2021. Case counts from the website Our World in Data (OWID) were used as the gold standard to which our participatory surveillance data were compared. We calculated Spearman’s and Pearson’s correlation coefficients to compare the weekly incidence of ILI reports to COVID-19 case count data.P < 0.001) .Over course of the study period, an ILI symptom was reported 1,085 times via participatory surveillance for an average annual cumulative incidence of 45.7 per 100 people . The cumulative incidence of reports of ILI symptoms was similar among males  and females . There was a slightly higher annual cumulative incidence of ILI among persons living in peri-urban  and urban settings compared to rural areas. The January peak of the participatory surveillance system ILI estimates correlated significantly with the January peak of the COVID-19 case count data (Spearman’s correlation coefficient = 0.49; The ILI trends captured by the participatory surveillance system in Lesotho mirrored trends of the COVID-19 case count data from Our World in Data. Public health practitioners in geographies that lack the resources to conduct direct surveillance of infectious diseases may be able to use cell phone-based data collection to monitor trends.The online version contains supplementary material available at 10.1186/s12879-023-08664-4. Since the emergence of the SARS-CoV-2 virus, public health surveillance data have played a key role in tracking and responding to the virus . SurveilIn Lesotho, a landlocked country of 2.1 million people in Southern Africa, the capacity to conduct laboratory testing for COVID-19 has been limited , 5. AccoLesotho did not conduct COVID-19 testing consistently at the beginning of the pandemic . Thus, iThis paper aims to provide a proof of concept showing that cell phone based participatory surveillance is useful for monitoring infectious disease outbreaks in resource limited settings.“LeCellPHIA”, a cell phone-based surveillance system that calls participants weekly to inquire about Influenza-likeIllness (ILI) symptoms , is an example of a participatory surveillance system. In other settings, surveillance of ILI has been an effective tool for early detection of COVID-19, and is now possible in sub-Saharan Africa given cell phones are increasingly common –15. To eThe LeCellPHIA cell phone-based participatory surveillance system was built from the 2020 Lesotho Population-Based HIV Impact Assessment (LePHIA2020) survey . LePHIA2To build LeCellPHIA, all 342 primary sampling units from the 10 LePHIA2020 districts were sampled. To ensure we had a sufficient number of older adults in our sample, who are at higher risk of COVID-19 mortality, households with elderly persons  . BeginniCOVID-19 data was not available from the Ministry of Health in Lesotho. We sought other sources of comparison data and after considering various sources, we determined Our World in Data (OWID) as the best source. The OWID website launched in 2014 and is updated daily, publishing international data on health outcomes, including daily new confirmed COVID-19 cases . We extrThe LeCellPHIA system captures the incidence of ILI each week. To calculate the weekly LeCellPHIA ILI incidence rate, any report of ILI symptoms  was included in the numerator. The denominator was comprised of participants (including reports from participants about household member symptoms) who answered the symptom questions that week. All results are weighted to adjust for unequal probability of selection, non-response, and potential under-coverage of sampling frame. SAS  and R Studio  were used to conduct all analyses. Gender, age, and location data were obtained from LePHIA2020.To calculate the weekly number of confirmed COVID-19 reports recorded in the OWID surveillance system, daily OWID reports of COVID-19 were aggregated into seven-day periods, corresponding with the weekly dates used by the LeCellPHIA surveillance system. LeCellPHIA dates were then roughly matched to Epi Weeks. The surveillance system collected data for all weeks between July 22, 2020 and July 13, 2021, except for the week of December 23–29, 2020 (Christmas holiday break).LePHIA2020 household weights were used to create LeCellPHIA base weights which were then adjusted for unequal probability of selection, non-response, and potential under-coverage of sampling frame. To create the weighted annual incidence of influenza-like illness using the LeCellPHIA data in Table Both the OWID and LeCellPHIA datasets were tested for normality using the Shapiro–Wilk test, and neither dataset was normally distributed. Due to the non-normal distribution of the datasets, we used a Spearman correlation to compare weekly cumulative incidence rates of LeCellPHIA ILI symptoms with the OWID count of weekly COVID-19 cases. Neither correlation test required the data to be in the same numerical format; therefore we left LeCellPHIA as a rate and the OWID data as a count.Prior studies have used Pearson’s correlation coefficient to assess for correlation between syndromic surveillance systems and other surveillance systems , 22. TheFigure The Lesotho National Research Ethics Committee and Columbia University Institutional Review Board (IRB) approved LeCellPHIA with exemption from committee review. The CDC IRB reviewed the protocol and deemed the research nonhuman subjects.LeCellPHIA collected 122,985 observations between July 15, 2020 – July 13, 2021. Just over half (56.0%) of the total reports were made by women . The cumulative incidence of reports of ILI symptoms was similar among males  and females . Among males, the annual cumulative incidence of ILI reports was highest among persons aged 60 + . Among females, the annual cumulative incidence of ILI reports was highest among persons aged 30–39 . There was a slightly higher annual cumulative incidence of ILI among persons living in peri-urban  and urban compared to rural areas. Persons residing in the Qacha’s Nek district had the annual highest cumulative incidence of ILI reports , while those residing in the Quthing district had the lowest: 22.4, 95% CI 11. 8 -42.2.The highest incidence rate of ILI symptoms was 3.23% during the week of January 13–19, 2021 (Epi Week 3). The lowest rate (0.35%) was the week of April 21–27 (Epi Week 17) . The highest case count was 2,731 during the week of January 6–12, 2021 (Epi Week 2) and the lowest case count was 1 during the week of (Epi Week 13).P < 0.001) and indicates moderate correlation between data collected by the OWID and weekly LeCellPHIA surveillance systems [P < 0.0001), indicating statistically significant, high correlation between the OWID and LeCellPHIA datasets [The Spearman’s correlation coefficient of 0.49 was statistically significant , the LeCellPHIA system may be considered as a feasible method for monitoring trends in the COVID-19 pandemic in Lesotho. Further, LeCellPHIA can be used as a model for the design of future syndromic surveillance systems which can help monitor COVID-19 outbreaks globally and potentially other disease outbreaks, as well. Finally, LeCellPHIA data are useful for implementing response to COVID-19; the Lesotho National COVID-19 Secretariat used LeCellPHIA results to inform the COVID-19 Risk Adjusted strategy.Additional file 1. Weekly Surveillance Questions (English).


Allostery enables changes to the dynamic behavior of a protein at distant positions induced by binding. Here, we present APOP, a new allosteric pocket prediction method, which perturbs the pockets formed in the structure by stiffening pairwise interactions in the elastic network across the pocket, to emulate ligand binding. Ranking the pockets based on the shifts in the global mode frequencies, as well as their mean local hydrophobicities, leads to high prediction success when tested on a dataset of allosteric proteins, composed of both monomers and multimeric assemblages.Out of the 104 test cases, APOP predicts known allosteric pockets for 92 within the top 3 rank out of multiple pockets available in the protein. In addition, we demonstrate that APOP can also find new alternative allosteric pockets in proteins. Particularly interesting findings are the discovery of previously overlooked large pockets located in the centers of many protein biological assemblages; binding of ligands at these sites would likely be particularly effective in changing the protein’s global dynamics.https://github.com/Ambuj-UF/APOP) and as a web server at https://apop.bb.iastate.edu/.APOP is freely available as an open-source code ( Allosteric regulation of function is commonly observed in proteins, ranging from the small G proteins  to largeThe large-scale transitions observed over long times  are not In this study, we simulated the impact of ligand binding on the global mode of proteins by considering pockets identified by the Fpocket algorithm . While bLarger numbers of important allosteric pockets are found. In several cases, we show that APOP can predict alternative allosteric pockets, as well as successfully utilize alternative conformers, such as apo or holo structures. Other important allosteric pockets discovered are the large pockets commonly found at the centers of multimeric assemblies.The allosteric proteins used in this study are taken from the test set of Allopred , togetheOur new allosteric pocket prediction algorithm APOP is comprised of three steps: (i) Pocket hunting. Pockets in the input protein structure are identified by Fpocket protein cavity detections , which uywhere N is the total number of residues/nodes in the protein. GNM is the underlying dynamics model used here to obtain a measure of the impact of perturbations at a given pocket on the protein’s characteristic motions, i.e. the global modes . GNM hasThe connectivity matrix or contact map, ) and eigenvalues Here, 2 regardless of the distances between those pairs of residues. For each perturbed pocket, the eigenvalues, and eigenvectors are calculated for the whole new structure network.To mimic the effect of ligand binding to a specific pocket, we increase the spring constant between all residues participating in that pocket, where ) and the first 15 eigenvectors of the perturbed structure , z-score p on the global dynamics byHere A method . AfterwaHere, z-scores of the pocket local hydrophobic densities , are calculated usingAllosteric pockets were previously shown to have higher local hydrophobic density , Hp, whi in ESSA . The z-sz-scores are then combined to define a pocket allostery score, giving equal weight to each of the two considerations as,Here, Then, the pockets are ranked based on this combined score For benchmarking, we use two machine learning-based methods, Allopred , and PasFor each structure, we report the highest-ranked pocket that is known to have bound allosteric ligand(s). In the multimeric assemblages, the same allosteric ligand(s) can be bound to each subunit. Among those occurrences, we report the highest-ranking pocket observed in the multimer. If this pocket is among the top-ranked three predicted pockets, we count it as a success. To cross-validate our results for APOP, Allopred, and Passer performance, we visually check whether the known allosteric ligand resides within the three top-ranked pockets reported by each method.0 is: The median difference between rank of known allosteric pocket predicted using Allopred and APOP is zero. The contrasting Alternate hypothesis H1 is: The median difference between rank of known allosteric pocket predicted using Allopred and APOP is positive. A positive difference indicates that the predicted rank of known allosteric pocket with Allopred is greater than APOP. A thorough statistical comparison between APOP and Passer was not conducted since the Passer web server provides only the top three ranking pockets, which leads to many unranked pockets.A one-sided Wilcoxon signed-rank test  was applP-value of 0.00088 obtained from the one-sided Wilcoxon signed-rank  nor to Nuclease SbcCD subunit D (PDB ID: 6ASC), since the active site residues were not resolved for these crystal structures, because of missing residues. In contrast, APOP predicts the allosteric pockets at the number one place for both cases. Furthermore, APOP was only able to rank 32% (16/50) of the active site pockets as top ranked pockets , indicatapo structures, with the ligand-binding pockets either formed or stabilized by the ligand. For this purpose, we consider another dataset, of 15 proteins taken from apo and holo structures are available  and 11 out of 15 pockets in apo structures in this set within the top 3 rank. Although conformational rearrangements seem to affect the success rate of our predictions for apo structures, we still achieve a satisfactory prediction rate of 86% (11/14), excluding one cryptic pocket (PDB ID: 1ZG4). For only the top-ranked pockets, APOP is successful in 12 holo and 8 apo structures.We also assess the performance of APOP on vailable , so thatapo/holo-structure dataset. Uridylate kinase is an essential enzyme for pyrimidine biosynthesis, adding a phosphate to uridine monophosphate (UMP) to form uridine diphosphate (UDP) (apo (PDB ID: 3EK6) and holo (PDB ID: 3EK5) structures  . It formte (UDP) . APOP prructures . Moreovensferase .apo and holo states of Tyrosine-protein phosphatase non-receptor type 1 protein are explored. Our results show that APOP is able to predict the known allosteric pocket as the top rank 1 pocket in 12, rank 2 in one case, and rank 5 in one structure from the set of 14 different conformational states  bound with alternative allosteric ligands and APOP can predict such alternative pockets. The first example is ABL kinase, which plays an important role in cell growth and survival through a wide range of molecular functions such as cell motility, autophagy, apoptosis, remodeling of cytoskeleton, and receptor endocytosis . Thus, ASus scrofa (PDB ID: 1KZ8)  and 69 (PDB ID: 1KZ8)—so that concentrating on the top 10% ranking pockets would include all of the allosteric pockets mentioned above. APOP also predicts the top-ranked pocket at the center of the assembly (blue mesh) in both species. In line with other cases discussed , which catalyzes the hydrolysis of fructose-1,6-bisphosphate (F16P) to fructose-6-phosphate (F6P). This homo-tetrameric enzyme plays an important role in regulating gluconeogenesis as a primary control point and helps maintain blood glucose levels. D: 1KZ8)   , which issed see , this cehttps://github.com/Ambuj-UF/APOP), as well as on a user-friendly web interface (https://apop.bb.iastate.edu/). Here, the user can choose either to provide a PDB id or upload a protein structure and can add a specific chain id of interest, where APOP uses all chains present in the structure. APOP uses the default optimal GNM distance cutoff of 10.0 APOP is available as an open-source Python package . APOP can predict allosteric pockets in both e kinase . APOP caBy comparing the APOP-predicted pockets to annotated pockets in the literature, we found that pockets that ranked high in our predictions were likely to be allosteric, even if they were not previously annotated as such. This is illustrated by the examples of fructose-1,6-bisphosphatase and pyruvate kinase , where Abtad275_Supplementary_DataClick here for additional data file.


Building a Renewed ImaGe after Head & neck cancer Treatment) is a brief, tailored cognitive behavioral therapy (CBT) that reduces HNC-related BID. This trial examines the effect of BRIGHT on psychosocial outcomes among HNC survivors with BID.Body image distress (BID) among head and neck cancer (HNC) survivors leads to depression, social isolation, stigma, and poor quality of life. BRIGHT  or dose-and delivery matched survivorship education (attention control [AC]). Secondary psychosocial outcomes were assessed using validated patient-reported outcomes at baseline and 1- and 3-months post-intervention.Among 44 HNC survivors with BID, BRIGHT resulted in a greater reduction in depression relative to AC . BRIGHT also decreased shame and stigma relative to AC  and social isolation .In this planned secondary analysis of a pilot RCT, BRIGHT improved a broad array of psychosocial outcomes among HNC survivors with BID.These promising preliminary data suggest the need for a large efficacy trial evaluating the effect of BRIGHT on psychosocial outcomes among HNC survivors with BID.ClinicalTrials.gov identifier: NCT03831100 In this analysis, we examined the effect of BRIGHT on a broad range of pre-defined secondary psychosocial outcomes among HNC survivors with BID.Although BID is a critical survivorship issue for patients with HNC,eFigure 1 in Supplement 1), methods, and primary analyses for the pilot RCT have been described in detail.20 Results are reported according to the Consolidated Standards of Reporting Trials Extension (CONSORT Extension) reporting guidelines for randomized pilot and psychological intervention trials.22The study and protocol were approved by the institutional review board at the Medical University of South Carolina (MUSC). The CONSORT diagram  psychoeducation about the cognitive model of body image; (2) self-monitoring about thoughts, feelings, and body image behaviors; (3) cognitive restructuring to identify and challenge unhelpful automatic HNC-related body image thoughts; (4) adaptive body image coping strategies; and (5) maintenance and relapse prevention. AC is a tele-supportive care intervention consisting of educational videos that address non-body image aspects of HNC survivorship . Following best practices for choosing control groups within behavior change RCTs,29 we designed AC to match BRIGHT’s dose (5 weekly sessions) and delivery method (video-based telemedicine) while not providing the behavior change mechanism in BRIGHT. Fidelity and adherence to both arms have previously been described.20 AC was not delivered by a mental health professional; adherence to AC was monitored by a member of the research team.In brief, BRIGHT is a theory-based,30) and HNC-related BID (as measured by the IMAGE-HN31) have been previously reported.20Demographic data were collected via self-report; clinical characteristics were extracted from the electronic health record. Patient-reported outcomes were administered electronically using REDCap. The primary analyses for acceptability, cancer-related BID . HNC-related shame and stigma were measured with the Shame and Stigma Scale, a validated 20-item, unidimensional patient-reported outcome measure of shame regarding appearance, stigma, regret, and social/speech concerns in patients with HNC over the prior 7 days.12 The total score ranges from 0 to 80, with higher scores representing greater shame and stigma from HNC.Secondary outcomes related to psychosocial morbidity are described below. Depression was assessed with the PROMIS SF v1.0-Depression 8a, a validated, 8-item measure developed by the NIH to assess patient-reported negative mood, views of self, and decreased positive affect and engagement.1 + (7/20) β2 as therapist A conducted BRIGHT for 13 subjects and therapist B conducted BRIGHT for 7 subjects. Statistical testing was 2-sided,with P < .10 considered statistically significant; 90% confidence intervals (CIs) were reported for point estimates. Waterfall plots of subject-level change scores were generated as well as plots of unadjusted means and 90% CIs for change scores in BRIGHT and AC treatment arms at 1-month and 3-months post intervention.Data collected from the study population were included in all descriptive and model-based analyses. All analyses were conducted using Rstudio (R version 4.2.3). Means and standard deviations were summarized by treatment group for each of the secondary outcomes of interest  at baseline, 1-month post-intervention and 3-months post-intervention. The effect of BRIGHT on the 1-month and 3-month change scores for each outcome was estimated using analysis of covariance. All models of change scores also included the baseline values as covariates to adjust for correlation between the change score and the baseline values. Treatment effects were estimated as a function of treatment group modeled as a 3-level variable  to account for heterogeneity in therapist effect. The overall treatment effect was estimated using a model-based contrast with a weighted average across therapists in the BRIGHT arm (therapist A weight = 13/20 and therapist B weight = 7/20) and contrast equal to (13/20) βeTable 1 in Supplement 1. Patients had a median age of 63 years  and 61% (27/44) identified as female. The most common head and neck subsite was the oral cavity ; 61% of patients (27/44) had stage III/IV HNC, and 61% (27/44) received adjuvant (chemo)radiation.Baseline characteristics are shown in BRIGHT decreased depression from baseline to 1-month post-intervention relative to AC  and from baseline to 3 months post-intervention relative to AC , with BRIGHT showing the largest improvement in BID in this population. Whatever the explanation, it is clear that (1) future studies should include depression as a secondary endpoint and (2) these preliminary data suggest that BRIGHT, in addition to reducing HNC-related BID, may also improve a key psychosocial outcome in these patients.Depression, although common among HNC survivors,42 Thus, one possible interpretation of our findings is that BRIGHT caused a reduction in depression primarily, and the observed improvement in BID is causally downstream of the improvement in depression. It is also possible that there is a bidirectional relationship between depression and BID in which reductions in one results in further reductions in the other. Finally, a third potential interpretation of these data is that BRIGHT improves BID primarily and the reduction in depression is downstream. Although the current study design precludes definitively evaluating the temporal relationship between changes in BID and changes in depression following BRIGHT, we believe this third interpretation is the most likely for two reasons. First, the content and psychotherapeutic techniques of the BRIGHT program focus exclusively on domains related to HNC BID-related and are thus unlikely to be sufficiently therapeutically active to see an improvement in depressive symptoms of this magnitude due to direct effects on depression. Second, limited data from two prospective cohort studies suggest that pre-treatment depression is not a risk factor for HNC-related BID, that BID develops temporally prior to depression in patients for whom the conditions co-occur.43 Additional research is therefore necessary to disentangle the temporal relationship between changes in depression and BID among HNC survivors following BRIGHT.When interpreting the findings from the current trial, it is important to consider the unclear causal and temporal relationship between depression, BID, and QOL. CBT is an effective treatment for depression among cancer survivors and one of the recommended 1 st line therapies for cancer survivors with moderate depression.12 Although common among all HNC survivors, shame and stigma-related concerns are especially prevalent among HNC survivors with disfigurement and other visible differences.6 Patients with facial disfigurement and BID limit social interaction and participation in social functions.45 BID among HNC survivors is also associated with unemployment.10 Outside the context of psychosocial oncology, shame and stigma have significant effects on social, family, and professional relationships. Although they are not universally included,40 shame, stigma, and social isolation are all key secondary endpoints for trials evaluating interventions to improve BID among HNC survivors. In this pilot trial, we provide preliminary evidence that BRIGHT reduces HNC-related shame and stigma, decreases social isolation, and improves satisfaction with social roles and activities among HNC survivors with BID. Our data align with other studies which have observed similar benefits of BID-focused interventions on outcomes of social avoidance and fear of social interactions.39 These preliminary data suggest that managing BID among HNC survivors with BID through interventions such as BRIGHT may thus contribute to improvements in performance in key social domains. As with depression, the inter-relationship and causal dependency of BID with each of these constructs (and with each of these constructs with one another) is complex. However, based on current conceptual models of HNC-related BID, it is likely that the effect of BRIGHT on shame and stigma, social isolation, and social activities is downstream of its effect on HNC-related BID.Shame, stigma, and social isolation are all important, if understudied, psychosocial outcomes for HNC survivors.20 With regard to the limitations of the specific secondary outcomes analyzed herein, the study was not powered for these outcomes, nor was it powered for more complex analyses that examined the relative associations of BID and depression to quality of life. Therefore, these planned secondary analyses should be considered hypothesis-generating and require confirmation in a larger trial. In addition, the clinical significance of the statistically significant improvements in measures of shame and stigma, depression, social isolation, and satisfaction with social roles and activities is not known. Therefore, further psychometric work is necessary to understand clinically meaningful differences in these measures over time and between groups within this patient population. Finally, although the trial was designed prior to the COVID-19 pandemic, it was conducted primarily during the pandemic when masking and social isolation were recommended public health measures. As a result, the external validity of study findings about the effect of BRIGHT on depression, anxiety, social isolation, and satisfaction with social activities outside the context of COVID-19 related masking  and social avoidance public health measures is unknown and thus requires further study.As discussed in the publication of the primary outcomes for this pilot RCT, findings should be interpreted within the context of several trial limitations. Consistent with its pilot objective, the trial had a single-site design, small sample size, and short follow-up.BID among HNC survivors is common and associated with devastating psychosocial morbidity including depression, anxiety, social isolation, and stigma. In this planned secondary analysis of a pilot RCT, BRIGHT improved a broad array of psychosocial outcomes among HNC survivors with BID. The improvements in depression, HNC-related shame stigma, social isolation, satisfaction with social roles and activities, seen with BRIGHT, when considered in conjunction with the previously reported improvement in HNC-related BID, further support conducting a large multisite efficacy trial to establish BRIGHT as the first evidence-based treatment for HNC survivors with BID.


Recovery was operationally defined as when the respective weekly average gait metric was no longer statistically different than pre-operative. Walking speed and step length were lowest, and timing asymmetry and double support percentage were greatest at week two post-operative (p < 0.0001). Walking speed recovered at 21 weeks  and double support percentage recovered at week 24 . Asymmetry percentage was recovered at 13 weeks  and was consistently superior to pre-operative values at week 19 . Step length did not recover during the 24-week period ; however, this difference is not likely clinically relevant. The data suggests that gait quality metrics are most negatively affected two weeks post-operatively, recover within the first 24-weeks following TKA, and follow a slower trajectory compared to previously reported step count recoveries. The ability to capture new objective measures of recovery is evident. As more gait quality data is accrued, physicians may be able to use passively collected gait quality data to help direct post-operative recovery using sensor-based care pathways.Advances in algorithms developed from sensor-based technology data allow for the passive collection of qualitative gait metrics beyond step counts. The purpose of this study was to evaluate pre- and post-operative gait quality data to assess recovery following primary total knee arthroplasty. This was a multicenter, prospective cohort study. From 6 weeks pre-operative through to 24 weeks post-operative, 686 patients used a digital care management application to collect gait metrics. Average weekly walking speed, step length, timing asymmetry, and double limb support percentage pre- and post-operative values were compared with a paired-samples  The primary objectives of total knee arthroplasty (TKA) are to alleviate pain and restore mobility and physical function. Early mobilization is a primary focus to enhance recovery following surgery . AlthougThe validity of self-reported physical activity questionnaires in assessing physical function recovery following lower extremity arthroplasty is controversial . For exaFree-living monitoring of daily step count with commercially available fitness trackers have been studied as an objective measure of physical activity and functional recovery following TKA ,11, and Gait analysis is an established and reliable tool to assess human ambulation , and theAnalysis of gait in patients with osteoarthritis via wearable sensors has nearly doubled in the past decade . Most stThe use of commercially available sensor-based technologies allows for gait analysis during activities of daily living  and has clinicaltrials.gov: NCT# 03737149). Data reviewed from this study included procedure type, sex, and passively collected gait quality metrics across a 30-week time period. The global study has been described in previous reports and consists of three phases including a pilot phase, a randomized controlled trial (RCT) phase, and a longitudinal cohort phase [This was a secondary analysis of a level II study with prospectively collected data from an ethics approved (WCG IRB # 20182013) global, multicenter prospective cohort study. Participants underwent primary TKA between January 2020 and March 2022  capable of pairing with the Apple Watch  and supporting updates, scheduled for a primary total knee arthroplasty (TKA), and capable of walking with minimal assistance  pre-operatively. Exclusion criteria included patients with substance abuse issues, inflammatory arthropathies, participating in any other surgical intervention, physical therapy, or pain management study that would compromise the results of this study, and patients requiring simultaneous or staged bilateral knee arthroplasties less than 90 days apart. All patients gave written consent to participate.® Care Management Platform, Zimmer Biomet, Warsaw, IN, USA). Patients consented to receive the watch for the duration of the study and ethics committees reviewed and determined the retention of the watch upon study exit. Pre-operatively, patients were provided with education and exercise content. Post-operatively, patients were provided with an at-home-based therapy program standard to the surgical institution’s standard of care through the app, beginning at discharge through 90 days post-operative. Patient compliance with the therapy program was tracked through the application, which automatically recorded patient activity and the outcome variable gait parameters, including walking speed, step length, asymmetry percentage, and double limb support percentage, directly. Walking speed is an estimation of the patient’s velocity while walking on flat ground, step length is an estimation of the distance between foot strikes, double support time is an estimation of the percentage of a gait cycle when both feet are in contact with the ground, and walking asymmetry is an estimation of the percentage of the time that asymmetric steps occur within a walking bout [Patients who met the inclusion and exclusion criteria, provided informed consent, and did not already own an Apple Watch were provided with an Apple Watch and the digital care management application  on a pressure mat while carrying an iPhone in the side pocket for walking speed , step length , double support percentage  and asymmetry percentage  with the iPhone . Comparet-tests. Statistical analysis was performed using SAS v9.4  and significance was assessed at p < 0.05.As a secondary analysis, the study used a convenience sample of all patients in the prospective study that met the inclusion and exclusion criteria. All data are reported as means with standard deviations unless otherwise indicated. A minimum of one day per week was required to be collected to be included in the analysis, and data was grouped as weekly averages. Data collected during the first six weeks pre-operative were averaged to represent pre-operative values. The analysis population selection criteria included: all patients eligible and consented, unilateral TKA, key demographic data collected, follow-up data no shorter than 24 weeks post-operative, and at least one of the involved Health Kit data  collected. Recovery was operationally defined as when the respective weekly average gait metric was no longer significantly inferior to the respective pre-operative value. Pre- and post-operative gait metrics were compared using paired samples N = 686, Female: n = 431 (62.8%), Age: 63.1 + 8.7 years, BMI: 31.5 + 6.4 kg/m2) is presented in A Strobe flow diagram of all patients (p < 0.001). Walking speed was recovered (p = 0.063), but never exceeded average pre-operative values.Compared to pre-operative (1.01 + 0.15 m/s), walking speed was lowest at post-operative week two  compared to pre-operative (0.60 + 0.08 m). Step length approached pre-operative values at week 24 (0.59 + 0.06 m) but remained statistically (p = 0.004) lower than pre-operative values . Asymmetry recovered at week 13  and was significantly (p = 0.001) improved compared to the average pre-operative value at week 19  and remained elevated before recovering at week 24 , double support percentage was greatest at week 2 (32.8 + 2.1%, The most important outcome from this study was the ability to demonstrate recovery curves of gait quality using free-living, passively collected objective measures. Specifically, the data demonstrate that all measures of gait quality were most negatively affected two-weeks post-operative, and although asymmetry percentage recovered at 13 weeks, walking speed, step length, and double limb support percentage required at least 22 weeks to fully recover.Monitoring mobility in the home setting has historically suffered from several challenges, including accuracy, technology portability, and data accessibility. Gait speed and symmetry have been used to assess dysfunction and treatment progress in the clinical environment ; howeverThe recovery curves presented in this study are similar to other recovery patterns following TKA found in literature, which show that the majority of physical function is recovered within the first three months post-operative ,41,42,43Based upon the assessment of pre- and early post-operative step counts, Twiggs et al.  recommenCompared to step counts, gait quality metrics may also provide deeper insights related to the recovery of function and ability to accomplish activities of daily living or participate in recreational activities following TKA. With specific regards to daily living, the mean walking speed used by pedestrians at crosswalks is 1.32 m/s and an absolute minimum of 0.49 m/s is necessary to cross a two-lane street with full time allotment . RegardiGiven the industry sponsorship of this study and the use of industry authors, the potential for bias exists, as does a potential conflict of interest. For transparency, five of the seven authors of this manuscript are employed by Zimmer Biomet, Inc. The disclosures can be found following the conclusion, but it is important to note this risk for bias and conflict of interest within the manuscript. However, the topic of industry authorship itself is controversial. For example, Gotzsche et al. noted that ghost writing in industry studies was common and recommended improved transparency . FurtherEvaluating passively collected data from digital care management systems has certain inherent limitations. This includes patient-specific behaviors associated with carrying their smartphone; for example, if the phone is on an armband, gait quality metrics will not be collected. However, given this is unique to each patient it seems reasonable that these behaviors would be similar both pre- and post-operatively. There may be some effects of the study on patient behavior, but collection of free-living data from a patient’s smartphone likely eliminates the Hawthorne effect, resulting in gait evaluations similar to everyday life, as opposed to those collected in the lab on a treadmill, as seen in traditional gait analyses. This study is also limited by the lack of control associated with both patient comorbidities and post-operative adverse events. Further analysis is needed to determine the effect these have on gait patterns.Using commercially available sensor-based technologies, we identified recovery trajectories of gait quality metrics in TKA patients specific to the study devices. We found the recovery was longer in duration and discordant to those previously reported for step counts or self-reported physical activity. We have demonstrated that two-week postoperative gait metrics are the most inferior in the recovery curve, while most of these gait metrics recover at 24 weeks. The results of this study demonstrate the ability to collect gait quality metrics via commercially available sensor-based technologies and provides recovery curves that may be used to assist sensor-based-technology-assisted care management. Further research, with larger samples, are needed to determine if sensor-based care pathways can improve the quality of care.


Amidst the fourth COVID-19 wave in Viet Nam, national lockdowns necessitated the closure of numerous dental schools. To assess DDS  graduation exams, this study analyzed their 2021 implementation in comparison to onsite exams conducted in 2020 and 2022 at the Faculty of Odonto-Stomatology, University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam (FOS-UMPH). The final online examination comprises two main sessions: a synchronous online examination using FOS-UMPH e-Learning for theories  and a synchronous online examination using Microsoft Teams for practicum (comprising of 12 online OSCE stations). The final grades were evaluated using the same metrics in face-to-face final examinations in 2022 and 2020. A total of 114, 112 and 95 students were recruited for the first-time exams in 2020, 2021 and 2022, respectively. In order to analyze the reliability, histogram and k-mean clustering were employed. The histograms from 2020, 2021 and 2022 showed a striking similarity. However, fewer students failed in 2021 and 2022  compared to 2020 (28%), with clinical problem-solving part grades (belonging to theory session) being notably higher in 2021 and 2022. Intriguingly, the MCQ Score results showed the identical patterns. The courses of orthodontics, dental public health, and pediatrics subjects (in the group of prevention and development dentistry) stood out for their exceptional accuracy across both sessions. After examining data gathered over three years, we identified three distinct clusters: the first comprised of scattered average and low scores, the second characterized by high scores but unstable and scattered and the third cluster boasting consistently high and centered scores. According to our study, online and onsite traditional graduation exam results are relatively equivalent, but additional measures are necessary to standardize the final examination and adapt to the new normal trend in dental education. The COVID-19 pandemic has had a widespread impact on numerous facets of society, including dental education and assessment of undergraduate students. To cope with the crisis, dental students have had to adapt to a temporary change in their education. Clinical placements have been cancelled, forcing them to switch to remote study from home. Dental schools have responded proactively by introducing online lectures and teaching opportunities to ensure that the students’ learning is not hampered through virtual platforms such as Zoom, Microsoft Teams, sOLAT and Web 2.0 tools [Amid the COVID-19 pandemic, clinicians have admirably balanced their clinical duties with teaching which is highly appreciated. The e-learning course consisted of various components, including educational materials, project tasks, practice tests, and interface ask a teacher, which allowed for a comprehensive online learning experience . HoweverTo objectively uncover novel insights from the data, we employed k-mean clustering analysis in this research. Our study offered an alternative method to assess the reliability of the final exam scores, moving beyond traditional comparative analysis statistics like t-test and one-way ANOVA.The research plan was approved by the Ethics Committee of University of Medicine and Pharmacy at Ho Chi Minh city. The score collection was approved by “the FOS-UMPH Academic Affairs Unit”.The final exam framework for 6th year dental students who have been completed their curriculum is detailed in In 2021, conventional assessments comprise in-person theoretical tests, where students are provided with computer system, and clinical examinations where they rotate among different stations and are assessed face-to-face for specific tasks. For virtual assessments, Microsoft Teams (v1.0.23) was utilized to facilitate both theoretical and practical examinations across multiple meeting rooms . We applTheory and practicum scores were collected by using the same evaluation metrics in both onsite  and online (2021). There were 114 students taking the final exam in 2020, 112 students in 2021 and 95 students in 2022 . In eachDental Basic Sciences, Periodontology, Restorative Dentistry and Endodontics, Prosthodontics, Oral Implantology (Block of Restorative Dentistry)Pediatric Dentistry, Dental Public Health, Orthodontics (Block of Development & Preventive Dentistry)Oral Pathology, Maxillo-facial Surgery, Oral Surgery, Oral Radiology Data were processed and analyzed using R version 4.1.3 and RStudio 2021.09.0 Build 351, PBC. We visualized scores in 2020, 2021 and 2022 with histograms, density plots, boxplots using ggplot2 (v3.3.5) and lvplot (v0.2.0) R packages. For each histogram, scores (ranged from 0 to 10 presented by different color) were visualized. For each density plot, scores (ranged from 0 to 10) were visualized with the number of students getting regarding score for 3 groups .We applied K-mean clustering method by factoextra (v1.0.7), stats (v4.1.1) R packages to analyze score data in three years . The pacK-means clustering is a method of vector quantization to partition n number of students/ year (observations) into k clusters in which each student (observation) belongs to the cluster with the nearest mean of scores (cluster centers). This results in a partitioning of the data space into Voronoi cells. k-means clustering minimizes within-cluster variances (squared Euclidean distances). At the minimum, all cluster centers were at the mean of their Voronoi sets (the set of data points which were nearest to the cluster center). Algorithm of Hartigan and Wong (1979) was applied by default . Charactp value less than 0.05 was considered significant.All results were expressed as means ± standard error of the mean. Statistical differences were determined by 2-way ANOVA with Bonferroni post-test or by 2-tailed Student’s t test. A While the composition score spectrum showed similarity between years in total theory score and total practicum score, there was a disparity in scores between years on closer observation  Table 1Table 1. Among the final exam subjects, Development and Preventive Dentistry subjects  had the most overlapped score distribution in both Clinical Problem Solving vs. Clinical Exam forms  between To characterize the features of score across 3 years, we performed k-mean clustering analysis. The results revealed 3 clusters in data collected in these 3 years showing the same characteristics . The 1stViet Nam faced a surge of SARS-COVID19 cases in 2021 that resulted in a public health lockdown from May 31 to September 30. The restrictions imposed included stay-at-home orders, mandatory mask-wearing, social distancing; and gathering limits . It is iThe initial difference in subject scores between years can be attributed to the variance in assessment tools—online and offline examination. Although online education and evaluation have been around for some time, the recent pandemic has brought it to the forefront. A study by Jagadeesan and Neelakanta (2021) utilized an online self-assessment tool for medical students in biochemistry during the pandemic, highlighting the successful transition from traditional classroom teaching to online education for dentistry as evidenced by examination results . This stOnline examinations offer several advantages like ease of access, time and cost savings, instant feedback, and multimedia support in question design, among others. They also encourage creative and analytical thinking, provide personalized options for question display, and clarity in answer reception , 16. TheDespite similarities in course material and lectures, significant differences in practicum exam scores were observed between courses. However, it is important to note that assessment practices are not standardized, and each instructor has their own subject criteria for evaluation. As such, the reliability of our qualitative analysis may be influenced by external factors such as pandemic, adjustments made by teachers to help students perform better, and the challenges posed by transitioning from in-person to online exams, which impact students’ technical, emotional, and intellectual abilities.The COVID-19 pandemic has led to the closure of many dental schools, thus necessitating the need for effective and reliable online teaching and assessment tools . HoweverThe consequences of the COVID-19 pandemic might also be a factor that affected the students’ health and psychology in their examination preparation and examination process, but this issue has not been fully investigated in this study. Hence, further research is required to understand the potential challenges and limitations of online dental final exams, and how they may differ from traditional in-person examinations. Additionally, the lack of direct observation and physical interaction with patients during an online exam may limit the ability of examiners to accurately assess a student’s clinical skills and decision-making abilities. These are important considerations that need to be addressed to ensure the reliability of online dental final exams. Further studies are needed to explore these factors in depth and to develop best practices for online dental education and assessment.In this study, we applied k-mean clustering analysis as a new approach to evaluate reliability of final exam score besides the conventional statistics based on p-value looking on each single subject. The tool provided a comprehensive vision of the present data with feature discovering of each cluster. On a positive note, our final year written examination and clinical OSCE distance assessments proved successful in evaluating student performance. In light of this, we may consider retaining online written summative MCQs and distance assessments with extended matching questions. However, remote assessment may not be practical for certain OSCE tasks within and beyond our field. While simultaneous remote assessments help evaluate competency with great accuracy, we must prioritize in-person clinical OSCEs whenever feasible.S1 Fig(PDF)Click here for additional data file.S1 File(XLSX)Click here for additional data file.S2 File(PDF)Click here for additional data file.