TREATMENT OF HIP AND KNEE PERIPROSTHETIC JOINT INFECTION REQUIRES EXTENSIVE ADMINISTRATIVE WORK.

INTRODUCTION: Treatment of periprosthetic joint infections (PJI) typically requires more resource utilization than primary total joint arthroplasty (TJA). This study quantifies the amount of time spent in the electronic medical record (EMR) for patients who have PJI requiring surgical intervention. METHODS: A retrospective analysis of EMR activity for 165 hip and knee PJI was performed to capture work during the preoperative and postoperative time periods. Independent sample t tests were conducted to compare total time based on procedure, age, insurance, health literacy, sex, race, and ethnicity. RESULTS: The EMR work performed by the orthopaedic team was 338.4 minutes (min) (SD [standard deviation] 130.3), with 119.4 minutes (SD 62.8) occurring preoperatively and 219.0 minutes (SD 112.9) postoperatively. Preoperatively, the surgeon's work accounted for 35.7 minutes (SD 25.4), mid-level providers 21.3 minutes (SD 15.9), nurses 38.6 minutes (SD 36.8), and office staff 32.7 minutes (SD 29.9). Infectious Disease (ID) colleagues independently performed 158.9 minutes (SD 108.5) of postoperative work. Overall, PJI of the knees required more postoperative work. Secondary analysis revealed that patients who have hip PJI and a BMI < 30 and patients < 65 years required more work when compared to the PJI of heavier and older individuals. There was no difference in total work based on insurance, health literacy, race, or ethnicity. CONCLUSION: Over 8 hours of administrative work is required for surgical management of PJI. Surgeons alone performed 451% more work for PJI during the preoperative period (7.9 versus 35.7min) compared to primary TJA. In efforts to provide best care for our sickest patients, much work is required perioperatively. This work is necessary to consider when assigning value and physician reimbursement.

Diffuse idiopathic skeletal hyperostosis (DISH): Detection on dental radiologic examinations in two older adults and overview of the literature.

BACKGROUND: Diffuse idiopathic skeletal hyperostosis (DISH) is a potentially serious osteopathic disorder associated with coalescing ossifications of the anterior vertebrae and may be concomitant with a constellation of symptomatology and systemic comorbidities. There is limited dental literature describing this finding on panoramic radiographs and cone beam computed tomography (CBCT) scans. CASE PRESENTATIONS: Two case reports of DISH are provided. One patient manifested extensive ossifications along the cervical vertebrae and consequent episodes of dysphagia and hoarseness. The other affected patient's cervical ossification was found at an earlier stage of formation and without symptomatology. Panoramic radiography, cervical spine radiography, and CBCT examinations have been provided. CONCLUSION: Attending dental healthcare practitioners should carefully evaluate all areas of interest and surrounding fields of view when taking panoramic radiographs and CBCT scans for manifestations of DISH and other potential disorders of the cervical vertebrae. A suspected radiologic finding of DISH should prompt timely referral for comprehensive medical assessment to mitigate neurologic deficits and other comorbidities.

Florid follicular lymphoid hyperplasia of the palate: review of the literature and report of an illustrative case.

OBJECTIVE: The aim of this report is to review oral FLH, with emphasis on palatal lesions. METHOD AND MATERIALS: A comprehensive search was performed on PubMed for case reports and case series of palatal FLH published in the English language literature. Relevant data from collated articles was sought, including patient demographics, clinical manifestations, imaging modalities and findings, comorbidities, etiopathogenesis, lesional management, and lesional outcome. A new palatal case has also been provided to illustrate several features of this lesion. RESULTS: In total, 32 cases were assembled to establish clinicopathologic correlations, representing the largest aggregation of published cases. Most of the affected patients were at least 60-years old and with a decisive female predilection. The majority of lesions were ≤ 3 cm, appearing as normal color, purple-red or red, and varied from soft to firm. Notably, 32% of palatal FLHs were associated with denture wear and lesional recurrence was recorded in 16% of cases. To date, none of the reported cases of palatal FLH has undergone malignant transformation. CONCLUSIONS: Palatal FLHs often arise as a reactive process. Critical histopathologic and histochemical assessments are necessary to establish benignity. Postoperatively, clinicians should follow patients for at least 5 years for recurrence and remain vigilant for neoplastic change as several published accounts of non-oral FLHs have undergone malignant transformation, usually to lymphoma.

Expanding the CHARMM36 United Atom Chain Model for the Inclusion of Sphingolipids.

The inclusion of accurate yet computationally inexpensive lipid force fields (FF) is pertinent for the study of lipids and lipid-containing systems using molecular dynamics (MD). Within the past decade, the implementation and further expansion of a united atom (UA) FF for lipids have been developed in the CHARMM family of FFs. The most recent version of the UA presented more accurate descriptions of lipid properties for several phospholipids with saturated and monounsaturated chains, termed C36UAr. However, the original C36UAr model lacks parameters for an important class of lipids, such as sphingolipids. The focus of this article is to broaden the scope of the C36UAr chain model to incorporate these lipids. In this study, two common sphingolipids, N-palmitoyl sphingomyelin and N-stearoyl sphingomyelin are converted to a UA-chain representation and simulated to investigate the accuracy and speed over the all-atom FF model for sphingolipids. Improvements were found among multiple parameters, for example, in the surface area per lipid (SA/lip) and hydrogen order parameters, over the all-atom simulations of these sphingomyelins in C36, while as much as halving the simulation time for simulations of the same setup otherwise. Thus, the accuracy and efficiency found in this study are consistent with those found in the C36UAr model for phospholipids and expand the application of C36UAr to a wider array of membrane models to better match that in vivo.

Chlorpromazine inhibits EAG1 channels by altering the coupling between the PAS, CNBH and pore domains.

EAG1 depolarization-activated potassium selective channels are important targets for treatment of cancer and neurological disorders. EAG1 channels are formed by a tetrameric subunit assembly with each subunit containing an N-terminal Per-Arnt-Sim (PAS) domain and C-terminal cyclic nucleotide-binding homology (CNBH) domain. The PAS and CNBH domains from adjacent subunits interact and form an intracellular tetrameric ring that regulates the EAG1 channel gating, including the movement of the voltage sensor domain (VSD) from closed to open states. Small molecule ligands can inhibit EAG1 channels by binding to their PAS domains. However, the allosteric pathways of this inhibition are not known. Here we show that chlorpromazine, a PAS domain small molecule binder, alters interactions between the PAS and CNBH domains and decreases the coupling between the intracellular tetrameric ring and the pore of the channel, while having little effect on the coupling between the PAS and VSD domains. In addition, chlorpromazine binding to the PAS domain did not alter Cole-Moore shift characteristic of EAG1 channels, further indicating that chlorpromazine has no effect on VSD movement from the deep closed to opened states. Our study provides a framework for understanding global pathways of EAG1 channel regulation by small molecule PAS domain binders.

Surveying the landscape of diagnostic imaging in dentistry's future: Four emerging technologies with promise.

BACKGROUND: Advances in digital radiography for both intraoral and panoramic imaging and cone-beam computed tomography have led the way to an increase in diagnostic capabilities for the dental care profession. In this article, the authors provide information on 4 emerging technologies with promise. TYPES OF STUDIES REVIEWED: The authors feature the following: artificial intelligence in the form of deep learning using convolutional neural networks, dental magnetic resonance imaging, stationary intraoral tomosynthesis, and second-generation cone-beam computed tomography sources based on carbon nanotube technology and multispectral imaging. The authors review and summarize articles featuring these technologies. RESULTS: The history and background of these emerging technologies are previewed along with their development and potential impact on the practice of dental diagnostic imaging. The authors conclude that these emerging technologies have the potential to have a substantial influence on the practice of dentistry as these systems mature. The degree of influence most likely will vary, with artificial intelligence being the most influential of the 4. CONCLUSIONS AND PRACTICAL IMPLICATIONS: The readers are informed about these emerging technologies and the potential effects on their practice going forward, giving them information on which to base decisions on adopting 1 or more of these technologies. The 4 technologies reviewed in this article have the potential to improve imaging diagnostics in dentistry thereby leading to better patient care and heightened professional satisfaction.

Real-Time Three-dimensional Dynamic Navigation for Post Space Preparation in Root Canal-Treated Teeth: An In vitro Study.

INTRODUCTION: The aim of this study was to investigate the feasibility of a real-time three-dimensional dynamic navigation system (3D-DNS) for post space preparation (PSP) in root canal-treated teeth and to compare the accuracy and efficiency of 3D-DNS to freehand (FH) for PSP. METHODS: Fifty-four maxillary molars were divided into two groups: 3D-DNS (n = 27) and FH group (n = 27). Cone beam computed tomography (CBCT) scans were taken preoperatively and postoperatively. The drilling path for the PSP was virtually planned in the preoperative CBCT scan in the X-guide software (X-Nav Technologies, Lansdale, PA). For the 3D-DNS group, the PSP drilling was conducted under dynamic navigation. The 3D deviations and angular deflections were calculated. The residual dentin thickness (RDT) was determined after PSP. The operation time and the total number of mishaps were recorded. Shapiro-Wilk, t-test or Mann-Whitney rank sum, weighted Cohen's kappa, and Fisher exact tests were used (P < .05). RESULTS: The PSP was completed in all samples (54/54). The 3D-DNS was more accurate than the FH, with significantly fewer 3D deviations and angular deflections (all, P < .05). The 3D-DNS required less operating time than the FH (P < .05). For the 3D-DNS, no teeth had RDT < 1 mm, whereas 6/27 in the FH showed RDT < 1 mm after the PSP. There was no difference in the total number of mishaps (P > .05). CONCLUSION: Within the limitations of this in vitro study, the 3D-DNS is feasible for PSP. The 3D-DNS improved the accuracy and efficiency of PSP. The dynamic navigation system can potentially become a safe and reliable technology for PSP.

Performance of AI chatbots on controversial topics in oral medicine, pathology, and radiology.

OBJECTIVES: In this study, we assessed 6 different artificial intelligence (AI) chatbots (Bing, GPT-3.5, GPT-4, Google Bard, Claude, Sage) responses to controversial and difficult questions in oral pathology, oral medicine, and oral radiology. STUDY DESIGN: The chatbots' answers were evaluated by board-certified specialists using a modified version of the global quality score on a 5-point Likert scale. The quality and validity of chatbot citations were evaluated. RESULTS: Claude had the highest mean score of 4.341 ± 0.582 for oral pathology and medicine. Bing had the lowest scores of 3.447 ± 0.566. In oral radiology, GPT-4 had the highest mean score of 3.621 ± 1.009 and Bing the lowest score of 2.379 ± 0.978. GPT-4 achieved the highest mean score of 4.066 ± 0.825 for performance across all disciplines. 82 out of 349 (23.50%) of generated citations from chatbots were fake. CONCLUSIONS: The most superior chatbot in providing high-quality information for controversial topics in various dental disciplines was GPT-4. Although the majority of chatbots performed well, it is suggested that developers of AI medical chatbots incorporate scientific citation authenticators to validate the outputted citations given the relatively high number of fabricated citations.

PC-PEP, a Comprehensive Daily Six-Month Home-Based Patient Empowerment Program Leads to Weight Loss in Men with Prostate Cancer: A Secondary Analysis of a Clinical Trial.

Background: The Prostate Cancer-Patient Empowerment Program (PC-PEP) is a six-month daily home-based program shown to improve mental health and urinary function. This secondary analysis explores weight loss in male PC-PEP participants. Methods: In a randomized clinical trial with 128 men undergoing curative prostate cancer (PC) treatment, 66 received 'early' PC-PEP, while 62 were assigned to the 'late' waitlist-control group, receiving 6 months of standard-of-care treatment followed by 6 months of PC-PEP. PC-PEP comprised 182 daily emails with video-based exercise and dietary (predominantly plant-based) education, live online events, and 30 min strength training routines (using body weight and elastic bands). Weight and height data were collected via online surveys (baseline, 6 months, and 12 months) including medical chart reviews. Adherence was tracked weekly. Results: No attrition or adverse events were reported. At 6 months, the early PC-PEP group experienced significant weight loss, averaging 2.7 kg (p < 0.001) compared to the waitlist-control group. Weight loss was noted in the late intervention group of PC-PEP, albeit less pronounced than in the early group. Early PC-PEP surgery patients lost on average 1.4 kg (SE = 0.65) from the trial's start to surgery day. High adherence to exercise and dietary recommendations was noted. Conclusions: PC-PEP led to significant weight loss in men undergoing curative prostate cancer treatment compared to standard-of-care.

Dental implant failure possibly attributed to embedded pencil graphite: first clinical report.

Implant failures have been associated with a diversity of etiologic processes, predominately arising from bone loss (peri-implantitis) due to inadequate maintenance of oral hygiene or excess luting agents. The aim of this article is to report a novel case of the apparent failure of a dental implant to undergo osseointegration in the presence of submerged pencil graphite. Practitioners are advised to carefully evaluate the clinical and radiographic site of a proposed implant for occult foreign substances. Embedded pencil graphite in the jawbone may promote a foreign body reaction and should be considered in the list of possible contributing factors to dental implant complications.

Artificial intelligence for classification and detection of oral mucosa lesions on photographs: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to review and synthesize studies using artificial intelligence (AI) for classifying, detecting, or segmenting oral mucosal lesions on photographs. MATERIALS AND METHOD: Inclusion criteria were (1) studies employing AI to (2) classify, detect, or segment oral mucosa lesions, (3) on oral photographs of human subjects. Included studies were assessed for risk of bias using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). A PubMed, Scopus, Embase, Web of Science, IEEE, arXiv, medRxiv, and grey literature (Google Scholar) search was conducted until June 2023, without language limitation. RESULTS: After initial searching, 36 eligible studies (from 8734 identified records) were included. Based on QUADAS-2, only 7% of studies were at low risk of bias for all domains. Studies employed different AI models and reported a wide range of outcomes and metrics. The accuracy of AI for detecting oral mucosal lesions ranged from 74 to 100%, while that for clinicians un-aided by AI ranged from 61 to 98%. Pooled diagnostic odds ratio for studies which evaluated AI for diagnosing or discriminating potentially malignant lesions was 155 (95% confidence interval 23-1019), while that for cancerous lesions was 114 (59-221). CONCLUSIONS: AI may assist in oral mucosa lesion screening while the expected accuracy gains or further health benefits remain unclear so far. CLINICAL RELEVANCE: Artificial intelligence assists oral mucosa lesion screening and may foster more targeted testing and referral in the hands of non-specialist providers, for example. So far, it remains unclear if accuracy gains compared with specialized can be realized.

Tropical cyclone winds and precipitation stimulate cone production in the masting species longleaf pine (Pinus palustris).

Many trees exhibit masting - where reproduction is temporally variable and synchronous over large areas. Several dominant masting species occur in tropical cyclone (TC)-prone regions, but it is unknown whether TCs correlate with mast seeding. We analyzed long-term data (1958-2022) to test the hypothesis that TCs influence cone production in longleaf pine (Pinus palustris). We integrate field observations, weather data, satellite imagery, and hurricane models to test whether TCs influence cone production via: increased precipitation; canopy density reduction; and/or mechanical stress from wind. Cone production was 31% higher 1 yr after hurricanes and 71% higher after 2 yr, before returning to baseline levels. Cyclone-associated precipitation was correlated with increased cone production in wet years and cone production increased after low-intensity winds (≤ 25 m s-1 ) but not with high-intensity winds (> 25 m s-1 ). Tropical cyclones may stimulate cone production via precipitation addition, but high-intensity winds may offset any gains. Our study is the first to support the direct influence of TCs on reproduction, suggesting a previously unknown environmental correlate of masting, which may occur in hurricane-prone forests world-wide.

How Many Patients Qualify for Extended Oral Antibiotic Prophylaxis Infection Following Primary and Revision Hip and Knee Arthroplasties?

Extended oral antibiotic prophylaxis (EOAP) has been suggested to reduce rates of periprosthetic joint infection (PJI) postoperatively after total joint arthroplasty (TJA). The purpose of this multicenter study is to define how many TJA patients are considered high risk for developing PJI based on published EOAP criteria and determine whether this status is associated with socioeconomic or demographic factors. All primary and aseptic revision TJAs performed in 2019 at three academic medical centers were reviewed. High-risk status was defined based on prior published EOAP criteria. Area deprivation index (ADI) was calculated as a measure of socioeconomic status. Data were reported as means with standard deviation. Both overall and institutional differences were compared. Of the 2,511 patients (2,042 primary and 469 revision) in this cohort, 73.3% met criteria for high risk (primary: 72.9% [1,490] and revision: 74.6% [350]). Patient's race or age did not have a significant impact on risk designation; however, a larger proportion of high-risk patients were women (p = 0.002) and had higher Elixhauser scores (p < 0.001). The mean ADI for high-risk patients was higher (more disadvantaged) than for standard-risk patients (64.0 [20.8] vs. 59.4 [59.4]) (p < 0.001). Over 72% of primary and revision TJA patients at three medical centers met published criteria for EOAP. These patients were more often women, had more comorbidities, and lived in more disadvantaged areas. Our findings suggest that most patients qualify for EOAP, which may call for more stringent criteria on who would benefit extended antibiotic prophylaxis.

Diminutive compound odontoma in a child: a case report with emphasis on early detection.

The odontoma is regarded as a hamartomatous process of the jaws. Most are discovered as an incidental radiographic finding, averaging 15 mm in size. This report describes a case of a diminutive odontoma that was surgically removed before the onset of eruptive and pathologic consequences. A compilation of documented complications and syndromes associated with odontomas is also presented.

Multiscale Molecular Dynamics Simulations of the Homodimer Accessory Protein ORF7b of SARS-CoV-2.

The SARS-CoV-2 ORF7b protein has drawn attention for its potential role in viral pathogenesis, but its structural details and lateral membrane associations remain elusive. In this study, we conducted multiscale molecular dynamics simulations to provide detailed molecular insights of the protein's dimerization, which is crucial for unraveling its structural model of protein-protein interface important to regulating cellular immune response. To gain a deeper understanding of homodimer configurations, we employed a machine learning algorithm for structural-based clustering. Clusters were categorized into three distinct groups for both parallel and antiparallel orientations, highlighting the influence of the initial monomer conformation on dimer configurations. Analysis of hydrogen bonding and π-π and π-cation stacking interactions within clusters revealed variations in interactions between clusters. In parallel dimers, weak stacking interactions in the transmembrane (TM) region were observed. In contrast, antiparallel dimers exhibited strong hydrogen bonding and stacking interactions contributing to tight dimeric packing, both within and outside the TM domain. Overall, our study provides a comprehensive view of the structural dynamics of ORF7b homodimerization in both parallel and antiparallel orientations. These findings shed light on the molecular interactions involved in ORF7b dimerization, which are crucial for understanding its potential roles in SARS-CoV-2 pathogenesis. This knowledge could inform future research and therapeutic strategies targeting this viral protein.

Development and validation of a next-generation sequencing assay with open-access analysis software for detecting resistance-associated mutations in CMV.

Cytomegalovirus (CMV) resistance testing by targeted next-generation sequencing (NGS) allows for the simultaneous analysis of multiple genes. We developed and validated an amplicon-based Ion Torrent NGS assay to detect CMV resistance mutations in UL27, UL54, UL56, and UL97 and compared the results to standard Sanger sequencing. NGS primers were designed to generate 83 overlapping amplicons of four CMV genes (~10 kb encompassing 138 mutation sites). An open-access software plugin was developed to perform read alignment, call variants, and interpret drug resistance. Plasmids were tested to determine NGS error rate and minor variant limit of detection. NGS limit of detection was determined using the CMV WHO International Standard and quantified clinical specimens. Reproducibility was also assessed. After establishing quality control metrics, 185 patient specimens previously tested using Sanger were reanalyzed by NGS. The NGS assay had a low error rate (<0.05%) and high accuracy (95%) for detecting CMV-associated resistance mutations present at ≥5% in contrived mixed populations. Mutation sites were reproducibly sequenced with 40× coverage when plasma viral loads were ≥2.6 log IU/mL. NGS detected the same resistance-associated mutations identified by Sanger in 68/69 (98.6%) specimens. In 16 specimens, NGS detected 18 resistance mutations that Sanger failed to detect; 14 were low-frequency variants (<20%), and six would have changed the drug resistance interpretation. The NGS assay showed excellent agreement with Sanger and generated high-quality sequence from low viral load specimens. Additionally, the higher resolution and analytic sensitivity of NGS potentially enables earlier detection of antiviral resistance.

Molecular mechanism of EAG1 channel inhibition by imipramine binding to the PAS domain.

Ether-a-go-go (EAG) channels are key regulators of neuronal excitability and tumorigenesis. EAG channels contain an N-terminal Per-Arnt-Sim (PAS) domain that can regulate currents from EAG channels by binding small molecules. The molecular mechanism of this regulation is not clear. Using surface plasmon resonance and electrophysiology we show that a small molecule ligand imipramine can bind to the PAS domain of EAG1 channels and inhibit EAG1 currents via this binding. We further used a combination of molecular dynamics (MD) simulations, electrophysiology, and mutagenesis to investigate the molecular mechanism of EAG1 current inhibition by imipramine binding to the PAS domain. We found that Tyr71, located at the entrance to the PAS domain cavity, serves as a "gatekeeper" limiting access of imipramine to the cavity. MD simulations indicate that the hydrophobic electrostatic profile of the cavity facilitates imipramine binding and in silico mutations of hydrophobic cavity-lining residues to negatively charged glutamates decreased imipramine binding. Probing the PAS domain cavity-lining residues with site-directed mutagenesis, guided by MD simulations, identified D39 and R84 as residues essential for the EAG1 channel inhibition by imipramine binding to the PAS domain. Taken together, our study identified specific residues in the PAS domain that could increase or decrease EAG1 current inhibition by imipramine binding to the PAS domain. These findings should further the understanding of molecular mechanisms of EAG1 channel regulation by ligands and facilitate the development of therapeutic agents targeting these channels.

Hurricane wind regimes for forests of North America.

Despite the ubiquity of tropical cyclones and their impacts on forests, little is known about how tropical cyclone regimes shape the ecology and evolution of tree species. We used a simple meteorological model (HURRECON) to estimate wind fields from hurricanes in the Western North Atlantic and Eastern North Pacific tropical cyclone basins from storms occurring between 1851 and 2022. We characterize how the intensity and frequency of hurricanes differ among geographically distinct hurricane regimes and define four hurricane regimes for North America (Continental, Inland, Coastal, and Fringe). Along this coastal-to-inland gradient, we found major differences in the frequency and intensity of hurricane wind regimes. The Fringe regime experiences category 1 winds relatively frequently [return period (RP) 25 y], whereas the Inland regime experiences category 1 winds very infrequently (RP ~3,000 y). We discuss how species traits related to tree windfirmness, such as mechanical properties and crown traits, may vary along hurricane regime gradients. Quantitative characterization of forest hurricane regimes provides a critical step for understanding the evolutionary and ecological role of hurricane regimes in wind-prone forests.

Detection of extracranial and intracranial calcified carotid artery atheromas in cone beam computed tomography using a deep learning convolutional neural network image segmentation approach.

OBJECTIVE: We leveraged an artificial intelligence deep-learning convolutional neural network (DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed tomography (CBCT) images. STUDY DESIGN: We obtained 137 full-volume CBCT scans with previously diagnosed CCAAs. The DL model was trained on 170 single axial CBCT slices, 90 with extracranial CCAAs and 80 with intracranial CCAAs. A board-certified oral and maxillofacial radiologist confirmed the presence of each CCAA. Transfer learning through a U-Net-based CNN architecture was utilized. Data allocation was 60% training, 10% validation, and 30% testing. We determined the accuracy of the DL model in detecting CCAA by calculating the mean training and validation accuracy and the area under the receiver operating characteristic curve (AUC). We reserved 5 randomly selected unseen full CBCT volumes for final testing. RESULTS: The mean training and validation accuracy of the model in detecting extracranial CCAAs was 92% and 82%, respectively, and the AUC was 0.84 with 1.0 sensitivity and 0.69 specificity. The mean training and validation accuracy in detecting intracranial CCAAs was 61% and 70%, respectively, and the AUC was 0.5 with 0.93 sensitivity and 0.08 specificity. Testing of full-volume scans yielded an AUC of 0.72 and 0.55 for extracranial and intracranial CCAAs, respectively. CONCLUSION: Our DL model showed excellent discrimination in detecting extracranial CCAAs on axial CBCT images and acceptable discrimination on full-volumes but poor discrimination in detecting intracranial CCAAs, for which further research is required.

Conformational Fluctuations in ß2-Microglubulin Using Markov State Modeling and Molecular Dynamics.

Conformational dynamics in proteins can give rise to aggregation prone states during folding, and these kinetically stable states could form oligomers and aggregates. In this study, we investigate the intermediate states and near-folded states of ß2-microglobulin and their physico-chemical properties using molecular dynamics and Markov state modeling. Analysis of hundreds of microseconds simulation show the importance of the edge strands in the misfolded states that give rise to a high exposure of hydrophobic residues in the core of the protein that could initiate oligomerization and aggregate formation. Our study sheds light on the first step of aggregation of ß2m monomers and gave a better picture of the landscape of protein misfolding and aggregation.