Likelihood Of Matching Research Articles

Exploring the 6-year Trend in Dedicated Research Years among Integrated Plastic and Reconstructive Surgery Residents.

The plastic and reconstructive surgery (PRS) match has become more competitive with an emphasis on research productivity. With the transition of the US Medical Licensing Examination step 1 examination to pass-fail grading, alternative evaluation metrics for residency applications are needed. Our study provides a landscape of the incidence of research years amongst integrated PRS residents and the potential impacts of gender and race. A retrospective study was conducted for all integrated PRS residents who matched between 2017 and 2022, using publicly available sources including residency websites, PubMed, Doximity, and social media. Demographics, educational background, and participation in a dedicated PRS research year were recorded. Among 993 residents across 85 accredited integrated PRS programs, 15.7% (156 of 993) took a research year, with a significant increase over 6 years (R 2 = 0.73, P = 0.019). The majority were men at 51.9%, and White at 53.5%, with underrepresented in medicine residents comprising 13.5%. A total of 73.1% came from a medical school with a home program, and 52.6% matched into a top 20 residency program. No significant difference was seen in the racial/ethnic or gender representation of residents who took a research year compared with all PRS applicants and active PRS residents. Research years before applying to residency are becoming more common among integrated PRS residents. Research years are especially common with students who do not have a home program and may help them gain skills and access to mentorship that improves the likelihood of matching.

Evaluating the Impact of the Standardized Letter of Recommendation on a Successful Match in Urology Residency

ObjectivesTo evaluate the contribution of the SLOR to the likelihood of matching in urology residency by applying a novel scoring system and characterize utilization in the 2022 application cycle. MethodsWe conducted an investigation of all applicants to our urology residency program during the 2022 cycle. We developed a scoring system to assess SLOR strength across all templates. Match outcomes were verified with the Society of Academic Urologists listing. Statistical analysis was performed to assess for factors predictive of a successful match. ResultsOut of 386 total applicants, 239 (61.9%) had at least one SLOR in their application. SLOR utilization was more prevalent in MD applicants, in those with higher Step 2 scores, and in those who matched (p < 0.01). The majority of SLOR scores (66.5%) were above a 3.5/5 in our cohort. Step 1 score, number of research entries, and presence of a SLOR were predictive of successful match. However, a SLOR score of < 3 was strongly associated with not matching (OR 0.021, p < 0.01). ConclusionsThe presence of a SLOR in our cohort overall was associated with a successful match. A poor SLOR score was highly deleterious to an applicant’s chance of matching in urology. Our SLOR scoring system can be used across all letter templates and demonstrates that strength of SLOR can significantly impact an applicant’s chance of matching.

Match rate of neurosurgery residents in the United States at their home institution: A comparative analysis of Pre COVID-19, During COVID-19 and Post COVID-19 pandemic

ObjectiveLimitations to medical student clinical rotation opportunities brought on by the pandemic has the potential to exacerbate differences in access to clinical experience between medical schools, and thus impact the distribution of graduates matching into neurosurgical programs nationwide. The utilization of virtual interviews that started after the pandemic are likely here to stay. In this study we seek to evaluate match rates for American (AMGs) and international medical graduates (IMGs) across the 6 most recent academic years, examining specifically the rate of home-institution matching before, during, and after the COVID-19 pandemic. MethodsAll neurological surgery residents for the years 2018–2024 were included in this analysis, with basic information about each resident being collected using publicly available online resources. For any remaining programs where information was not publicly available, program directors were contacted. Statistical analysis was performed using SPSS version 26.0 with a level of significance p<0.05. ResultsOf the total of 1271 AMGs, 1005 (79.1 %) matched away from their home institution. When dividing the 6 academic years into 3 subgroups (pre, intra, and post COVID-19), there was no significant variation between the rates of home institution matching (pre=21.0 %, during=20.4 %, post=21.3 %, p=0.740). Similar results were found while assessing IMGs (pre=28.6 %, during=30.8 %, post=32.3 %, p=0.777). Our analysis found no variation in match rates when isolating for gender across the 6 years studied either for AMGs or IMGs. However, overall institute-specific variations were found where some programs showed increased likelihood of home program match (p<0.001). ConclusionPreliminary data analysis suggests that contrary to the broader trends seen in other specialties, neurosurgery applicants do not exhibit a significant shift towards matching in closer proximity to their home institutions post COVID-19 pandemic and during the virtual interviews era.

Sending a Signal: Evaluating the Impact of Program and Geographic Preference Signaling on the Internal Medicine Residency Match.

Background For over a decade, the number of residency applications has surged, a trend known as "application inflation." COVID-19 further intensified this trend, leading the Association of American Medical Colleges (AAMC) to addressthe issue by introducing a supplemental application in the 2021-2022 cycle, allowing programs to identify applicants with a connection to their program or geographic region. For the 2022-2023 cycle, the number of program signals increased from five to seven. The impact of the supplemental application and the increase in signals on the likelihood of an applicant matching with a programhas yet to be evaluated. Methods This retrospective cohort study evaluated the impact of program signaling and geographic preference on the matching likelihood in our internal medicine residency program. Data from MyERAS® and the Supplemental Application for 640 applicants who applied to our large, urban, university-based program in the Southeastern United States during the 2020-2021 and 2022-2023 application cycles were included. Using univariate and multivariate analysis, we examined the correlation between program signal, geographic preference, and final match location. Results Applicants who sent a program signal had nearly three-foldhigher odds of matching with our program. Geographic preference was numerically but not statistically associated with higher odds of matching. Both signaling a preference for matching with a program in an urban environment and couples matching correlated with decreased odds of matching with our program. Geography was an important predictor of match location as residing in our AAMC geographic region, our four-state area, and our specific state had increased odds of matching with our program. Conclusions Signaling our program was associated with increased odds of matching with our program. Geographic preferences were less predictive of a match with our program; however, they did predict the likelihood of a match at a program within that region. Future studies are needed to ensure external validity.

Enhancing Map Matching Accuracy Using Backtracking Technique

Map matching integrates positioning data with road network information to accurately identify a vehicle exact location on a specific road. Modern location-based services heavily rely on accurate map matching techniques to match observed trajectories with road networks. This paper presents a novel map matching approach that leverages topological information and integrates the backtracking technique to enhance the accuracy and robustness of map matching. By considering the logical relationships between road segments, our method achieves excellent results in scenarios with complex road geometries and challenging urban environments. We integrate the backtracking technique to address noise and ambiguity in trajectory data, resulting in improved precision and a reduced likelihood of false matches. Extensive experimentation using real-world trajectory datasets in Beijing validates the effectiveness of our approach, highlighting its superiority over traditional methods. The algorithm accuracy achieved as high as 99.92%. The results of the evaluation demonstrate that the proposed approach exhibits superior performance compared to earlier map-matching algorithms in both simple and complex road networks. Additionally, it can be effectively implemented on GPS datasets with different time intervals. In addition to the obvious map matching applications of our technology, it has the potential to be adapted across domains, with implications in transportation, urban planning, and location-based services. This paper not only presents a substantial advancement in map matching but also opens new avenues for location-based analyses enhancing and services across various domains.

The evolution and impact of the Society for Vascular Surgery Resident and Student Program

ObjectiveThere is an ongoing national shortage in the vascular surgery (VS) workforce. To increase interest in the specialty, the Society for Vascular Surgery (SVS) Resident and Student Outreach Committee (RSOC) developed a dedicated general surgery (GS) resident and medical student (MS) program at the Vascular Annual Meeting (VAM) and invested in a scholarship program to help reduce attendee expenses. This study assesses the program’s effectiveness, correlating recipient feedback with the likelihood of matching into a VS training program. MethodsRecords related to the SVS VAM GS resident and MS program from 2013 to 2023 were reviewed, focusing on attendee evaluations of the program. The program included a simulation session from 2013 to 2019. VS training program match rates among scholarship recipients were determined. The annual average match rate in VS was used to divide the survey responses into two groups: below average (BA) and above average (AA) match rate groups. Survey responses were based on a 5-point Likert scale and allowed for comments. Responses were divided into high value, strongly favoring the activity (scores 4-5), and low value (scores 1-3) categories. The survey responses from the group of years with AA match rates were compared with the group of years with BA rates. ResultsThe SVS awarded 1040 GS resident and MS travel scholarships over the 10 years assessed. Overall, applicants had a 43% success rate in receiving a scholarship. During the study period, the annual number of applicants increased, whereas the number of scholarships and match success rates significantly decreased. The average match rate into VS among scholarship recipients was 50.2%. The survey response rate was 33%. During AA match rate years, evaluations for simulation allotted time and lectures were significantly more likely to be high value compared with BA years. Simulation content and the residency fair consistently had the most favorable evaluations (>90% high value), and overall, the program had a consistently positive impact on recipients’ interest in VS (>90% high value). Trainees in the AA group were significantly more likely to provide positive comments (73% vs 55%; P < .001). Numerous recipients commented on the need for a dedicated space to interact with faculty and mentors and highlighted simulation as the standout aspect of the program. ConclusionsThe SVS VAM RSOC program is positively correlated with attendee interest in VS, with approximately 50% of scholarship recipients matching into the field. The quality of the program and the number of scholarships correlate with VS match rates. Additional investments in similar programs could help close the workforce gap.

Osteopathic Students Have Decreased Match Rates in Orthopaedic Surgery Compared with Allopathic Students.

Orthopaedic surgery continues to be one of the most competitive specialties to match into as a medical student, particularly for osteopathic medical students. Therefore, in this study, we sought to examine the prevalence of osteopathic students (DO) matching into orthopaedic surgery at traditional Accreditation Council for Graduate Medical Education (ACGME) accredited programs (former allopathic residency programs) in recent years. A retrospective review of National Residency Match Program annual reports and Association of American Medical Colleges's Electronic Residency Application Service Statistic reports were performed to determine the number of applications and match rates among osteopathic (DO) and allopathic (MD) medical students into orthopaedic surgery from 2019 to 2023. Data on the degree type of current residents at all ACGME-accredited residency programs were identified. During the analyzed study period of 2019 to 2023, there were 3,473 (74.5%) allopathic students and 571 (59.9%) osteopathic students who successfully matched into orthopaedic surgery. This match rate for allopathic students was 74.5% compared with 59.9% for osteopathic students. Of the 3,506 medical students who hold postgraduate orthopaedic surgery positions at former allopathic programs over the past 5 years, only 58 (1.7%) hold an osteopathic degree. Of the 560 medical students who hold postgraduate orthopaedic surgery positions at former osteopathic programs over the past 5 years, 47 (8.4%) hold an allopathic degree. The match rate of allopathic students at former osteopathic programs is significantly higher than the match rate of osteopathic students at former allopathic programs. Osteopathic students continue to match into orthopaedic surgery at lower rates than their allopathic counterparts. In addition, there remains a consistent and low number of osteopathic students matching into former allopathic programs. Allopathic students also have a higher likelihood of matching into former osteopathic programs when compared with osteopathic students matching into previous allopathic orthopaedic surgery programs.

"Home Field Advantage": The Presence of a "Home" Neurosurgical Residency Training Program is Associated With Improved Match Outcomes.

Competition for neurosurgical residency training positions remains fierce. The support provided by applicants' home neurosurgery residency training programs (NRTP) is suspected to play a key role in the National Resident Matching Program (NRMP) process. We sought to evaluate the impact of the presence of an Accreditation Council for Graduate Medical Education-accredited NRTP at medical students' home institutions has on NRMP match outcomes. Our cross-sectional observational study examined all US allopathic senior student Electronic Residency Application Service applications to a single NRTP from 2016 to 2022. We analyzed a total of 1650 Electronic Residency Application Service applications to a single NRTP, of which 1432 (86.8%) were from schools with an Accreditation Council for Graduate Medical Education-accredited NRTP (NRTP+) and 218 (13.2%) were from schools without a residency (NRTP-). NRTP+ applicants matched a higher rate on both pooled analysis (80.8% vs 71.6%, P = .002) and paired analysis ( P = .02) over the seven-cycle study period. This difference was present before (82.4% vs 73.9%, P = .01) and after (77.2% vs 65.6%, P = .046) the COVID-19 pandemic. Cohorts were overall similar; however, NRTP+ applicants had more publication experiences (19.6 ± 19.0 vs 13.1 ± 10.2, P < .001) and were more likely to complete a research gap year (RGY) (25.8% vs 17.0%, P = .004). Completing a RGY was associated with an increased likelihood of matching for NRTP+ applicants but not for NRTP- applicants: NRTP+: 84.9% vs 78.1% ( P = .0056); NRTP-: 70.3% vs 70.9% ( P = .94). The presence of a NRTP at a medical student's home institution is associated with improved NRMP match outcomes. This held true both before and after the COVID-19 pandemic. Applicants from schools with a NRTP had more publication experiences and were more likely to complete a RGY. Completion of a RGY is associated with an increased likelihood of matching only for students with an affiliated NRTP.

Improving Unrelated Donor Equity: Assessing Mismatched Donor Opportunities with Real-World Data in a Minority-Predominant Cohort

Recent advances in graft-versus-host disease (GVHD) prophylaxis including post-transplant cyclophosphamide (PTCy) and abatacept have significantly improved outcomes following HLA-mismatched allogenic hematopoietic stem cell transplantation (allo-HSCT) and have tremendous potential for reducing racial disparities in donor availability. A recent small study employing bone marrow as the source of stem cells showed similar outcomes after 5/8 versus 7/8 matches and is currently being tested in a larger study using peripheral blood stem cells. In this study, we examine real-world alternative donor HSCT options for a minority-predominant cohort in the Bronx, NY, focusing on the availability of lesser-matched (5/8 to 7/8) donors. Records of patients who underwent HLA typing at Montefiore Medical Center (2019 to 2022) were reviewed. The National Marrow Donor Program registry was queried to evaluate the availability of donors with at least 99% likelihood of HLA match at various levels (5/8, 6/8, 7/8, 8/8). Two hundred forty-one patients were included, 70% were non-White. Although the availability of ≥7/8 donors was less common in non-White patients, 100% of patients from each group had at least one or more 5/8 and 6/8 HLA-matched donors and more than 80% of these patients had >100 potential 5/8 and 6/8 HLA-matched donors. There was no statistical difference by race or ethnicity in the mean number of donors at 5/8 and 6/8 HLA-match levels. We demonstrate through real-world data that patients from diverse ethnic and racial backgrounds have access to 5/8 and 6/8 HLA-matched donors for allo-HSCT, potentially eliminating disparities in donor availability and allowing prioritization of other donor selection characteristics such as donor age, sex, ABO, and B leader matching. Further work is needed to study whether the use of mismatched donors offers a more potent graft-versus malignancy effect and optimal GVHD prophylaxis.

Vertical Metabolome Transfer from Mother to Child: An Explainable Machine Learning Method for Detecting Metabolomic Heritability.

Vertical transmission of metabolic constituents from mother to child contributes to the manifestation of disease phenotypes in early life. This study probes the vertical transmission of metabolites from mothers to offspring by utilizing machine learning techniques to differentiate between true mother-child dyads and randomly paired non-dyads. Employing random forests (RF), light gradient boosting machine (LGBM), and logistic regression (Elasticnet) models, we analyzed metabolite concentration discrepancies in mother-child pairs, with maternal plasma sampled at 24 weeks of gestation and children's plasma at 6 months. The propensity of vertical transfer was quantified, reflecting the likelihood of accurate mother-child matching. Our findings were substantiated against an external test set and further verified through statistical tests, while the models were explained using permutation importance and SHapley Additive exPlanations (SHAP). The best model was achieved using RF, while xenobiotics were shown to be highly relevant in transfer. The study reaffirms the transmission of certain metabolites, such as perfluorooctanoic acid (PFOA), but also reveals additional insights into the maternal influence on the child's metabolome. We also discuss the multifaceted nature of vertical transfer. These machine learning-driven insights complement conventional epidemiological findings and offer a novel perspective on using machine learning as a methodology for understanding metabolic interactions.

An analysis of osteopathic medical students applying to surgical residencies following transition to a single graduate medical education accreditation system.

Upon requests from osteopathic medical schools, the National Resident Matching Program (NRMP) Charting Outcomes were redesigned to include osteopathic medical school seniors beginning in 2018 and one joint graduate medical education (GME) accreditation system, the Accreditation Council for Graduate Medical Education (ACGME), formed in 2020. The goal of this study is to analyze the match outcomes and characteristics of osteopathic applicants applying to surgical specialties following the ACGME transition. A retrospective analysis of osteopathic senior match outcomes in surgical specialties from the NRMP Main Residency Match data from 2020 to 2022 and the NRMP Charting Outcomes data from 2020 to 2022 was performed. For surgical specialties, results show matching increased as United States Medical Licensing Examination (USMLE) Step 2 CK (clinical knowledge) and Comprehensive Osteopathic Medical Licensing Examination (COMLEX) Level 2 CE (cognitive evaluation) scores increased along with the number of contiguous rankings (p<0.001). The greatest indication for matching looking at scores alone were those who scored greater than 230 on Step 2 CK compared to below (p<0.001) and above 650 on Level 2 CE (p<0.001). However, those who scored 240 (p=0.025) on Step 2 CK were just as likely to match as those who scored 250 (p=0.022) when compared to those who scored below those scores. Increasing research involvement had little to no significance with the likelihood of matching across most surgical subspecialties. Our study demonstrates that there are unique thresholds for Step 2 CK scores, Level 2 CE scores, and the number of contiguous ranks for each surgical specialty that, when reached, are significantly associated with match success. Although certain board score delineations are linked with higher match success rates, the rates level off after this point for most surgical specialties and do not significantly increase further with higher scores. In addition, thresholds within contiguous ranks for increasing match likelihood exist and vary across surgical specialties. Overall, this study highlights that the quantitative metrics utilized to assess applicants lack the correlation reported historically, and the data presently available need to be more substantiated.

Influence of the Number, Timing, and Types of Advanced Pharmacy Practice Experiences on Residency Matching

ObjectiveTo characterize the association between the number, timing, and type of Advanced Pharmacy Practice Experiences (APPEs) and the likelihood of postgraduate year 1 (PGY1) residency match outcomes. MethodsA retrospective cohort study was performed among PGY1 residency-seeking pharmacy students from graduating years 2018–2021 as identified from the National Matching Services Inc enrollee list. The number of APPEs of interest (AOI) most likely to align with general PGY1 residencies (acute care, ambulatory care, and elective rotations with significant direct patient care interactions) completed before January of the respective graduation year (GY) was compared between matched and unmatched students to a PGY1 program in any phase. Classification and regression tree analyses were performed to identify the AOI threshold associated with an increased likelihood of matching. ResultsAmong 155 students meeting inclusion criteria, 115 students (74%) matched during the study period. The probability of matching was 36%, 74%, and 83% for students completing 2, 3 or 4 AOI, respectively. Classification and regression tree analyses identified 3 or more AOI completed before January of the GY as the threshold significantly associated with PGY1 residency matching. ConclusionCompleting at least 3 AOI before January of the GY was associated with a significantly increased probability of PGY1 residency matching. These findings may influence students’ preferences for sequencing of APPEs to improve match results, but may be limited by institutional capacity.

The determinants of online matching platforms for freight services

With the development of information technology and the success of E-commerce, online freight exchange platforms have expanded to trucking freight services by matching truckers with shippers directly. Despite the endeavors of online freight platforms to emulate the success of other platform services, they face difficulties in facilitating successful matches. By analyzing the transactional data of an existing freight service platform, we seek to identify the salient factors that improve platform matching rates using a linear regression with splines for freight rate, capturing non-linearities, and a RUM discrete outcome model for matching. Both models are estimated jointly (simultaneously) using full information maximum likelihood (FIML). The empirical findings indicate that successful matching is more likely if the online freight platforms allow making substantial price adjustments once a job has been posted, as well as allowing shippers to have a longer lead time for loading their shipments, particularly in cases where finding a suitable trucker is challenging. Furthermore, allowing customers to revise shipment information provides greater flexibility in accommodating customer needs and ultimately enhances the likelihood of successful matching. Our analysis provides actionable and pragmatic suggestions to improve matching rates for online platforms of freight services.

DB-Tracker: Multi-Object Tracking for Drone Aerial Video Based on Box-MeMBer and MB-OSNet

Drone aerial videos offer a promising future in modern digital media and remote sensing applications, but effectively tracking several objects in these recordings is difficult. Drone aerial footage typically includes complicated sceneries with moving objects, such as people, vehicles, and animals. Complicated scenarios such as large-scale viewing angle shifts and object crossings may occur simultaneously. Random finite sets are mixed in a detection-based tracking framework, taking the object’s location and appearance into account. It maintains the detection box information of the detected object and constructs the Box-MeMBer object position prediction framework based on the MeMBer random finite set point object tracking. We develop a hierarchical connection structure in the OSNet network, build MB-OSNet to get the object appearance information, and connect feature maps of different levels through the hierarchy such that the network may obtain rich semantic information at different sizes. Similarity measurements are computed and collected for all detections and trajectories in a cost matrix that estimates the likelihood of all possible matches. The cost matrix entries compare the similarity of tracks and detections in terms of position and appearance. The DB-Tracker algorithm performs excellently in multi-target tracking of drone aerial videos, achieving MOTA of 37.4% and 46.2% on the VisDrone and UAVDT data sets, respectively. DB-Tracker achieves high robustness by comprehensively considering the object position and appearance information, especially in handling complex scenes and target occlusion. This makes DB-Tracker a powerful tool in challenging applications such as drone aerial videos.

Perceptions of Preference Signaling in Orthopaedic Surgery: A Survey of Applicants and Program Directors.

To improve transparency between candidates and training programs, a preference signaling program (PSP) was implemented before the 2022 to 2023 orthopaedic surgery match. The PSP allows applicants to 'signal' up to 30 programs, informing the program of the applicant's particular interest in interviewing for their available position(s). This study reports the perspectives of orthopaedic surgery residency applicants and program directors (PDs) on the effects of preference signaling on the orthopaedic match. Electronic surveys were distributed to PDs and applicants. Almost all programs participated in the PSP (90%), and most of the applicants (97.6%) used 25 to 30 of their allotted preference signals. Most of the applicants (67.2%) thought that their likelihood of obtaining an interview was improved at 'signaled' programs but decreased at programs without a 'signal' designation (85.3%). Both applicants and PDs considered preference signaling to be one of the three most important factors for interview selection, along with Step 2 CK score and letters of recommendation. The applicants did not think that their likelihood of matching would improve with fewer allotted signaling tokens (35.2%), and 55.2% of PDs believed 21 to 30 tokens were optimal. Preference signaling is highly regarded by applicants and PDs. Signaling a program will likely improve an applicant's chance to interview. The optimal number of signaling tokens remains unknown, although both groups favored a larger allotment of tokens than has been seen in other specialties. Universal guidelines and recommendations for applicants and PDs would improve the utility of preference signaling.

Existence of HLA-Mismatched Unrelated Donors Closes the Gap in Donor Availability Regardless of Recipient Ancestry

In patients without a matched sibling donor (MSD) or well-matched unrelated donor (MUD), hematopoietic cell transplantation (HCT) can still be successful when using an HLA-mismatched unrelated donor (MMUD) in combination with post-transplantation cyclophosphamide (PTCy), abatacept, or other novel approaches. This may allow clinicians to choose a suitable donor from a wide range of donor options while optimizing other donor selection characteristics, including donor age. We hypothesized that allowing for a 5/8 HLA match level considering high-resolution matching at HLA-A, -B, -C and -DRB1, there is a potential to close the donor availability gap for all patients regardless of their race/ethnicity. In this work, we estimate the likelihood of matching for all racial/ethnic groups at different HLA match thresholds. Our study aimed to assess the potential for identifying an available MUD or MMUD in the National Marrow Donor Program (NMDP)/Be The Match (BTM) donor registry for 21 detailed and 5 broad racial/ethnic groups, using high-resolution HLA matching for HLA-A, -B, -C, and -DRB1 at various levels (8/8, 7/8, 6/8, and 5/8). We used donor registry population data from the NMDP/BTM in 2020 and redistributed the donor registry data according to existing population ratios, accounting for demonstrated donor availability. Finally, we used a genetic model at the population level to estimate the match likelihood for detailed and broad racial/ethnic groups. Likelihood of 8/8 HLA match ranging from 16% to 74% were obtained for various detailed racial/ethnic groups with available donors age ≤35 years. When considering more mismatches in the HLA loci, registry coverage became >99% with a 5/8 HLA match level for donors of all ages or those age ≤35 years, with HLA-DPB1 T cell epitope permissive matching, or when searching for donors outside of their racial/ethnic group. Our registry models demonstrate the potential for using MMUDs at various HLA match levels to study whether this will expand access to HCT across racial/ethnic groups. Expanded donor options may erase the donor availability gap for all patients while allowing for selection of MMUDs with favorable characteristics, such as younger age.

Host Associations of Culicoides Biting Midges in Northeastern Kansas, USA.

Culicoides biting midges (Diptera: Ceratopogonidae) are hematophagous flies that transmit several viruses of veterinary concern to livestock. Understanding blood feeding behaviors is integral towards identification of putative vector species and preventing the transmission of these pathogens. PCR-based blood meal analysis was conducted on 440 blood-engorged Culicoides midges collected in northeastern Kansas, with 316 (71.8%) returning non-human vertebrate identifications at the ≥95% identity match level. Broadly, Culicoides sonorensis, Culicoides stellifer, and Culicoides variipennis were found to feed heavily on mammalian hosts, while Culicoides crepuscularis and Culicoides haematopotus fed on avian hosts. The blood meals in all specimens were graded prior to DNA extraction to determine whether blood meal size or digestion status significantly impacted the likelihood of a quality host match. Size had a significant impact on the likelihood of a quality match at grades 3-5, whereas digestion only significantly impacted outcomes at the most extreme grade. These vector-host dynamics have not previously been studied in Culicoides collected in Kansas, which represents a unique tallgrass prairie biome within the United States that is heavily interspersed with livestock operations. Based on these data, the highly abundant species C. crepuscularis and C. haematopotus are unlikely to be major vectors of mammalian viruses.

Evaluating gender discrepancies in the time to successful match into a small animal surgery residency program.

To determine any association between gender and likelihood of first attempt match and overall time to match into an American College of Veterinary Surgery (ACVS)-registered small animal surgical residency program (SASRP). Online survey. A total of 100 (77 female, 23 male) ACVS small animal surgery residents or diplomates participating in a SASRP during the past 5 years. An online survey was sent to eligible individuals. Respondents anonymously provided information related to demographics, postgraduate internships, and qualifications at the time of each surgical residency application. First attempt and overall match success were evaluated by gender through univariable analysis and then via a multivariable model. Men were 2.89 times more likely to match directly into a SASRP following a rotating internship than women (p = .041), and women completed more total internships than men prior to successful match into a SASRP (p = .030); however, men were found to have more publications at the time of first residency application (p < .001) or successful match (p = .018). Multivariable analysis revealed no association between gender on overall match success or first attempt match rate when considering all other qualifications. No evidence for gender bias was found during the Veterinary Internship and Residency Matching Program (VIRMP) SASRP applicant selection process; however, gender specific patterns in research qualifications were identified. Gender-blinded assessment is not considered necessary for the VIRMP small animal surgical resident selection process. Efforts should be made to educate applicants about the impact of research on the residency selection process and encourage research engagement of female students and graduates.

An integrated deep learning framework for the interpretation of untargeted metabolomics data.

Untargeted metabolomics is gaining widespread applications. The key aspects of the data analysis include modeling complex activities of the metabolic network, selecting metabolites associated with clinical outcome and finding critical metabolic pathways to reveal biological mechanisms. One of the key roadblocks in data analysis is not well-addressed, which is the problem of matching uncertainty between data features and known metabolites. Given the limitations of the experimental technology, the identities of data features cannot be directly revealed in the data. The predominant approach for mapping features to metabolites is to match the mass-to-charge ratio (m/z) of data features to those derived from theoretical values of known metabolites. The relationship between features and metabolites is not one-to-one since some metabolites share molecular composition, and various adduct ions can be derived from the same metabolite. This matching uncertainty causes unreliable metabolite selection and functional analysis results. Here we introduce an integrated deep learning framework for metabolomics data that take matching uncertainty into consideration. The model is devised with a gradual sparsification neural network based on the known metabolic network and the annotation relationship between features and metabolites. This architecture characterizes metabolomics data and reflects the modular structure of biological system. Three goals can be achieved simultaneously without requiring much complex inference and additional assumptions: (1) evaluate metabolite importance, (2) infer feature-metabolite matching likelihood and (3) select disease sub-networks. When applied to a COVID metabolomics dataset and an aging mouse brain dataset, our method found metabolic sub-networks that were easily interpretable.

MULTIMODAL MICROSCOPY IMAGE ALIGNMENT USING SPATIAL AND SHAPE INFORMATION AND A BRANCH-AND-BOUND ALGORITHM.

Multimodal microscopy experiments that image the same population of cells under different experimental conditions have become a widely used approach in systems and molecular neuroscience. The main obstacle is to align the different imaging modalities to obtain complementary information about the observed cell population (e.g., gene expression and calcium signal). Traditional image registration methods perform poorly when only a small subset of cells are present in both images, as is common in multimodal experiments. We cast multimodal microscopy alignment as a cell subset matching problem. To solve this non-convex problem, we introduce an efficient and globally optimal branch-and-bound algorithm to find subsets of point clouds that are in rotational alignment with each other. In addition, we use complementary information about cell shape and location to compute the matching likelihood of cell pairs in two imaging modalities to further prune the optimization search tree. Finally, we use the maximal set of cells in rigid rotational alignment to seed image deformation fields to obtain a final registration result. Our framework performs better than the state-of-the-art histology alignment approaches regarding matching quality and is faster than manual alignment, providing a viable solution to improve the throughput of multimodal microscopy experiments.