Currently Available Large Language Models Do Not Provide Musculoskeletal Treatment Recommendations That are Concordant With Evidence-Based Clinical Practice Guidelines.

PURPOSE: To determine whether leading, commercially-available LLMs provide treatment recommendations concordant with evidenced-based clinical practice guidelines (CPGs) developed by the American Academy of Orthopedic Surgeons (AAOS). METHODS: All CPGs concerning the management of rotator cuff tears(n=33) and anterior cruciate ligament (ACL) injuries(n=15) were extracted from the AAOS. Treatment recommendations from Chat-generative pretrained transformer version-4 [ChatGPT-4; OpenAI], Gemini (Google), Mistral-7B (Mistral AI), and Claude-3 (Anthropic) were graded by two blinded physicians as being "concordant," "discordant," or "indeterminate" (i.e., neutral response without definitive recommendation) with respect to AAOS CPGs. The overall concordance between LLM and AAOS recommendations were quantified, while the comparative overall concordance of recommendations amongst the four LLMs was evaluated through the Fischer's-exact test. RESULTS: Overall 135(70.3%) responses were concordant, 43(22.4%) indeterminate, and 14(7.3%) discordant. Inter-rater reliability for concordance classification was excellent (Kappa=0.92). Concordance with AAOS CPGs was most frequently observed with ChatGPT-4 (n=38, 79.2%), and least frequently with Mistral-7B (n=28,58.3%). Indeterminate recommendations were most frequently observed with Mistral-7B (n=17,35.4%) and least frequently with Claude-3 (n=8, 6.7%). Discordant recommendations were most frequently observed with Gemini (n=6,12.5%) and least frequently with ChatGPT-4 (n=1,2.1%). Overall, no statistically significant differences in concordant recommendations was observed across LLMs (p=0.12). Only 20 (10.4%) of all recommendations were transparent and provided references with full bibliographic details or links to specific peer-reviewed content to support recommendations. CONCLUSION: Among leading commercially-available LLMs, more than one-in-four recommendations concerning the evaluation and management of rotator cuff and ACL injuries do not reflect current evidenced-based CPGs. Although ChatGPT-4 demonstrated the highest performance, clinically significant rates of recommendations without concordance or supporting evidence were observed. Only 10% of responses by LLMs were transparent, precluding users from fully interpreting the sources from which recommendations were provided. CLINICAL RELEVANCE: While leading LLMs generally provide recommendations concordant with CPGs, a substantial error-rate exists, and the proportion of recommendations that do not align with these CPGs suggest that LLMs are not trustworthy clinical support tools at this time. Each off-the-shelf, closed-source LLM has strengths and weaknesses. Future research should evaluate and compare multiple LLMs to avoid bias associated with narrow evaluation of few models as observed in current literature.

Understanding How ChatGPT May Become a Clinical Administrative Tool Through an Investigation on the Ability to Answer Common Patient Questions Concerning Ulnar Collateral Ligament Injuries.

Background: The consumer availability and automated response functions of chat generator pretrained transformer (ChatGPT-4), a large language model, poise this application to be utilized for patient health queries and may have a role in serving as an adjunct to minimize administrative and clinical burden. Purpose: To evaluate the ability of ChatGPT-4 to respond to patient inquiries concerning ulnar collateral ligament (UCL) injuries and compare these results with the performance of Google. Study Design: Cross-sectional study. Methods: Google Web Search was used as a benchmark, as it is the most widely used search engine worldwide and the only search engine that generates frequently asked questions (FAQs) when prompted with a query, allowing comparisons through a systematic approach. The query "ulnar collateral ligament reconstruction" was entered into Google, and the top 10 FAQs, answers, and their sources were recorded. ChatGPT-4 was prompted to perform a Google search of FAQs with the same query and to record the sources of answers for comparison. This process was again replicated to obtain 10 new questions requiring numeric instead of open-ended responses. Finally, responses were graded independently for clinical accuracy (grade 0 = inaccurate, grade 1 = somewhat accurate, grade 2 = accurate) by 2 fellowship-trained sports medicine surgeons (D.W.A, J.S.D.) blinded to the search engine and answer source. Results: ChatGPT-4 used a greater proportion of academic sources than Google to provide answers to the top 10 FAQs, although this was not statistically significant (90% vs 50%; P = .14). In terms of question overlap, 40% of the most common questions on Google and ChatGPT-4 were the same. When comparing FAQs with numeric responses, 20% of answers were completely overlapping, 30% demonstrated partial overlap, and the remaining 50% did not demonstrate any overlap. All sources used by ChatGPT-4 to answer these FAQs were academic, while only 20% of sources used by Google were academic (P = .0007). The remaining Google sources included social media (40%), medical practices (20%), single-surgeon websites (10%), and commercial websites (10%). The mean (± standard deviation) accuracy for answers given by ChatGPT-4 was significantly greater compared with Google for the top 10 FAQs (1.9 ± 0.2 vs 1.2 ± 0.6; P = .001) and top 10 questions with numeric answers (1.8 ± 0.4 vs 1 ± 0.8; P = .013). Conclusion: ChatGPT-4 is capable of providing responses with clinically relevant content concerning UCL injuries and reconstruction. ChatGPT-4 utilized a greater proportion of academic websites to provide responses to FAQs representative of patient inquiries compared with Google Web Search and provided significantly more accurate answers. Moving forward, ChatGPT has the potential to be used as a clinical adjunct when answering queries about UCL injuries and reconstruction, but further validation is warranted before integrated or autonomous use in clinical settings.

Defining clinically relevant outcome thresholds for pain and function after osteochondral autograft transplantation of the knee.

PURPOSE: To define the minimal clinically important difference (MCID) for measures of pain and function at 2, 5 and 10 years after osteochondral autograft transplantations (OATs). METHODS: Patients undergoing OATs of the knee were identified from a prospectively maintained cartilage surgery registry. Baseline demographic, injury and surgical factors were collected. Patient-reported outcome scores (PROMs) were collected at baseline, 2-, 5- and 10-year follow-up, including the International Knee Documentation Committee (IKDC) score, Knee Outcome Survey Activities of Daily Living Scale (KOS-ADLS), Marx activity scale and Visual Analogue Scale (VAS) for pain. The MCIDs were quantified for each metric utilizing a distribution-based method equivalent to one-half the standard deviation of the mean change in outcome score. The percentage of patients achieving MCID as a function of time was assessed. RESULTS: Of 63 consecutive patients who underwent OATs, 47 (74.6%) patients were eligible for follow-up (surgical date before October 2021) and had fully completed preoperative PROMs. A total of 39 patients (83%) were available for a minimum 2-year follow-up, with a mean (±standard deviation) follow-up of 5.8 ± 3.4 years. The MCIDs were determined to be 9.3 for IKDC, 2.5 for Marx, 7.4 for KOS-ADLS and 12.9 for pain. At 2 years, 78.1% of patients achieved MCID for IKDC, 77.8% for Marx, 75% for KOS-ADLS and 57.9% for pain. These results were generally maintained through 10-year follow-ups, with 75% of patients achieving MCID for IKDC, 80% for Marx, 80% for KOS-ADLS and 69.8% for pain. CONCLUSIONS: The majority of patients achieved a clinically relevant outcome improvement after OATs of the knee, with results sustained through 10-year follow-up. Patients who experience clinically relevant outcome improvement after OATs in the short term continue to experience sustained benefits at longer-term follow-up. These data provide valuable prognostic information when discussing patient candidacy and the expected trajectory of recovery. LEVEL OF EVIDENCE: Level III.

A Tale of Two Tails: Rotational Spectroscopy of N-Ethyl Maleimide and N-Ethyl Succinimide.

Broadband microwave spectra of N-ethyl maleimide (NEM) and N-ethyl succinimide (NES) have been recorded using chirped pulse Fourier transform microwave spectroscopy in the Ka-band (26.5-40 GHz). The spectra for both molecules were fit to a Watson A-reduced Hamiltonian in the Ir representation to obtain best fit experimental rotational constants (NEM: A0 = 2143.1988(29), B0 = 1868.7333(22), C0 = 1082.98458(36); NES: A0 = 2061.47756(14), B0 = 1791.73517(12), C0 = 1050.31263(11)), centrifugal distortion constants, and nuclear quadrupole coupling constants. While the heavy atoms of the five-membered ring of both molecules are planar, the ethyl chain has its terminal methyl group perpendicular to the ring. Along the relaxed potential energy curve for the ethyl dihedral angle (θ1 = C(6)-C(5)-N-C(4)), the ethyl group experiences significant steric strain when it is in the plane of the ring, associated with the interaction of the ethyl group with the two carbonyl oxygens. This leads to calculated barriers of θ1 = 1469 cm-1 and θ1 = 1680 cm-1 in N-ethyl maleimide and N-ethyl succinimide, respectively.

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Segond Fractures Can Be Identified With Excellent Accuracy Utilizing Deep Learning on Anteroposterior Knee Radiographs.

Purpose: To develop a deep learning model for the detection of Segond fractures on anteroposterior (AP) knee radiographs and to compare model performance to that of trained human experts. Methods: AP knee radiographs were retrieved from the Hospital for Special Surgery ACL Registry, which enrolled patients between 2009 and 2013. All images corresponded to patients who underwent anterior cruciate ligament reconstruction by 1 of 23 surgeons included in the registry data. Images were categorized into 1 of 2 classes based on radiographic evidence of a Segond fracture and manually annotated. Seventy percent of the images were used to populate the training set, while 20% and 10% were reserved for the validation and test sets, respectively. Images from the test set were used to compare model performance to that of expert human observers, including an orthopaedic surgery sports medicine fellow and a fellowship-trained orthopaedic sports medicine surgeon with over 10 years of experience. Results: A total of 324 AP knee radiographs were retrieved, of which 34 (10.4%) images demonstrated evidence of a Segond fracture. The overall mean average precision (mAP) was 0.985, and this was maintained on the Segond fracture class (mAP = 0.978, precision = 0.844, recall = 1). The model demonstrated 100% accuracy with perfect sensitivity and specificity when applied to the independent testing set and the ability to meet or exceed human sensitivity and specificity in all cases. Compared to an orthopaedic surgery sports medicine fellow, the model required 0.3% of the total time needed to evaluate and classify images in the independent test set. Conclusions: A deep learning model was developed and internally validated for Segond fracture detection on AP radiographs and demonstrated perfect accuracy, sensitivity, and specificity on a small test set of radiographs with and without Segond fractures. The model demonstrated superior performance compared with expert human observers. Clinical Relevance: Deep learning can be used for automated Segond fracture identification on radiographs, leading to improved diagnosis of easily missed concomitant injuries, including lateral meniscus tears. Automated identification of Segond fractures can also enable large-scale studies on the incidence and clinical significance of these fractures, which may lead to improved management and outcomes for patients with knee injuries.

Sequencing of Kaposi's Sarcoma Herpesvirus (KSHV) genomes from persons of diverse ethnicities and provenances with KSHV-associated diseases demonstrate multiple infections, novel polymorphisms, and low intra-host variance.

Recently published near full-length KSHV genomes from a Cameroon Kaposi sarcoma case-control study showed strong evidence of viral recombination and mixed infections, but no sequence variations associated with disease. Using the same methodology, an additional 102 KSHV genomes from 76 individuals with KSHV-associated diseases have been sequenced. Diagnoses comprise all KSHV-associated diseases (KAD): Kaposi sarcoma (KS), primary effusion lymphoma (PEL), KSHV-associated large cell lymphoma (KSHV-LCL), a type of multicentric Castleman disease (KSHV-MCD), and KSHV inflammatory cytokine syndrome (KICS). Participants originated from 22 different countries, providing the opportunity to obtain new near full-length sequences of a wide diversity of KSHV genomes. These include near full-length sequence of genomes with KSHV K1 subtypes A, B, C, and F as well as subtype E, for which no full sequence was previously available. High levels of recombination were observed. Fourteen individuals (18%) showed evidence of infection with multiple KSHV variants (from two to four unique genomes). Twenty-six comparisons of sequences, obtained from various sampling sites including PBMC, tissue biopsies, oral fluids, and effusions in the same participants, identified near complete genome conservation between different biological compartments. Polymorphisms were identified in coding and non-coding regions, including indels in the K3 and K15 genes and sequence inversions here reported for the first time. One such polymorphism in KSHV ORF46, specific to the KSHV K1 subtype E2, encoded a mutation in the leucine loop extension of the uracil DNA glycosylase that results in alteration of biochemical functions of this protein. This confirms that KSHV sequence variations can have functional consequences warranting further investigation. This study represents the largest and most diverse analysis of KSHV genome sequences to date among individuals with KAD and provides important new information on global KSHV genomics.

Clinical Results of Primary Repair Versus Reconstruction of the Anterior Cruciate Ligament: A Systematic Review and Meta-analysis of Contemporary Trials.

Background: Primary anterior cruciate ligament (ACL) repair has gained renewed interest in select centers for patients with proximal or midsubstance ACL tears. Therefore, it is important to reassess contemporary clinical outcomes of ACL repair to determine whether a clinical benefit exists over the gold standard of ACL reconstruction (ACLR). Purpose: To (1) perform a meta-analysis of comparative trials to determine whether differences in clinical outcomes and adverse events exist between ACL repair versus ACLR and (2) synthesize the midterm outcomes of available trials. Study Design: Systematic review; Level of evidence, 3. Methods: The PubMed, OVID/Medline, and Cochrane databases were queried in August 2023 for prospective and retrospective clinical trials comparing ACL repair and ACLR. Data pertaining to tear location, surgical technique, adverse events, and clinical outcome measures were recorded. DerSimonian-Laird random-effects models were constructed to quantitatively evaluate the association between ACL repair/ACLR, adverse events, and clinical outcomes. A subanalysis of minimum 5-year outcomes was performed. Results: Twelve studies (893 patients; 464 ACLR and 429 ACL repair) were included. Random-effects models demonstrated a higher relative risk (RR) of recurrent instability/clinical failure (RR = 1.64; 95% confidence interval [CI], 1.04-2.57; P = .032), revision ACLR (RR = 1.63; 95% CI, 1.03-2.59; P = .039), and hardware removal (RR = 4.94; 95% CI, 2.10-11.61; P = .0003) in patients who underwent primary ACL repair versus ACLR. The RR of reoperations and complications (knee-related) were not significantly different between groups. No significant differences were observed when comparing patient-reported outcome scores. In studies with minimum 5-year outcomes, no significant differences in adverse events or Lysholm scores were observed. Conclusion: In contemporary comparative trials of ACL repair versus ACLR, the RR of clinical failure, revision surgery due to ACL rerupture, and hardware removal was greater for primary ACL repair compared with ACLR. There were no observed differences in patient-reported outcome scores, reoperations, or knee-related complications between approaches. In the limited literature reporting on minimum 5-year outcomes, significant differences in adverse events or the International Knee Documentation Committee score were not observed.

ChatGPT-4 Performs Clinical Information Retrieval Tasks Using Consistently More Trustworthy Resources Than Does Google Search for Queries Concerning the Latarjet Procedure.

PURPOSE: To assess the ability of ChatGPT-4, an automated Chatbot powered by artificial intelligence, to answer common patient questions concerning the Latarjet procedure for patients with anterior shoulder instability and compare this performance with Google Search Engine. METHODS: Using previously validated methods, a Google search was first performed using the query "Latarjet." Subsequently, the top 10 frequently asked questions (FAQs) and associated sources were extracted. ChatGPT-4 was then prompted to provide the top 10 FAQs and answers concerning the procedure. This process was repeated to identify additional FAQs requiring discrete-numeric answers to allow for a comparison between ChatGPT-4 and Google. Discrete, numeric answers were subsequently assessed for accuracy on the basis of the clinical judgment of 2 fellowship-trained sports medicine surgeons who were blinded to search platform. RESULTS: Mean (± standard deviation) accuracy to numeric-based answers was 2.9 ± 0.9 for ChatGPT-4 versus 2.5 ± 1.4 for Google (P = .65). ChatGPT-4 derived information for answers only from academic sources, which was significantly different from Google Search Engine (P = .003), which used only 30% academic sources and websites from individual surgeons (50%) and larger medical practices (20%). For general FAQs, 40% of FAQs were found to be identical when comparing ChatGPT-4 and Google Search Engine. In terms of sources used to answer these questions, ChatGPT-4 again used 100% academic resources, whereas Google Search Engine used 60% academic resources, 20% surgeon personal websites, and 20% medical practices (P = .087). CONCLUSIONS: ChatGPT-4 demonstrated the ability to provide accurate and reliable information about the Latarjet procedure in response to patient queries, using multiple academic sources in all cases. This was in contrast to Google Search Engine, which more frequently used single-surgeon and large medical practice websites. Despite differences in the resources accessed to perform information retrieval tasks, the clinical relevance and accuracy of information provided did not significantly differ between ChatGPT-4 and Google Search Engine. CLINICAL RELEVANCE: Commercially available large language models (LLMs), such as ChatGPT-4, can perform diverse information retrieval tasks on-demand. An important medical information retrieval application for LLMs consists of the ability to provide comprehensive, relevant, and accurate information for various use cases such as investigation about a recently diagnosed medical condition or procedure. Understanding the performance and abilities of LLMs for use cases has important implications for deployment within health care settings.

Global Aphasia Secondary to Bilateral Thalamic Hyperintensities Post-cardiac Arrest.

Thalamic aphasia is thought to occur secondary to disruptions in the cortico-subcortical connections. Although rare, thalamic aphasia is a well-known phenomenon that usually presents with primarily lexical-semantic deficits with preservation of comprehension and repetition. Global aphasia secondary to thalamic injury is extremely rare, with only a few case reports of patients with left thalamic hemorrhages. The prognosis for thalamic aphasia is generally good, with most patients showing little to no symptoms after days or weeks. However, global thalamic aphasia carries a more guarded prognosis with limited recovery months after injury. Here, we report a case of global thalamic aphasia secondary to bilateral thalamic damage post-cardiac arrest.

The Large Language Model ChatGPT-4 Exhibits Excellent Triage Capabilities and Diagnostic Performance for Patients Presenting With Various Causes of Knee Pain.

PURPOSE: To provide a proof-of-concept analysis of the appropriateness and performance of ChatGPT-4 to triage, synthesize differential diagnoses, and generate treatment plans concerning common presentations of knee pain. METHODS: Twenty knee complaints warranting triage and expanded scenarios were input into ChatGPT-4, with memory cleared prior to each new input to mitigate bias. For the 10 triage complaints, ChatGPT-4 was asked to generate a differential diagnosis that was graded for accuracy and suitability in comparison to a differential created by 2 orthopaedic sports medicine physicians. For the 10 clinical scenarios, ChatGPT-4 was prompted to provide treatment guidance for the patient, which was again graded. To test the higher-order capabilities of ChatGPT-4, further inquiry into these specific management recommendations was performed and graded. RESULTS: All ChatGPT-4 diagnoses were deemed appropriate within the spectrum of potential pathologies on a differential. The top diagnosis on the differential was identical between surgeons and ChatGPT-4 for 70% of scenarios, and the top diagnosis provided by the surgeon appeared as either the first or second diagnosis in 90% of scenarios. Overall, 16 of 30 diagnoses (53.3%) in the differential were identical. When provided with 10 expanded vignettes with a single diagnosis, the accuracy of ChatGPT-4 increased to 100%, with the suitability of management graded as appropriate in 90% of cases. Specific information pertaining to conservative management, surgical approaches, and related treatments was appropriate and accurate in 100% of cases. CONCLUSIONS: ChatGPT-4 provided clinically reasonable diagnoses to triage patient complaints of knee pain due to various underlying conditions that were generally consistent with differentials provided by sports medicine physicians. Diagnostic performance was enhanced when providing additional information, allowing ChatGPT-4 to reach high predictive accuracy for recommendations concerning management and treatment options. However, ChatGPT-4 may show clinically important error rates for diagnosis depending on prompting strategy and information provided; therefore, further refinements are necessary prior to implementation into clinical workflows. CLINICAL RELEVANCE: Although ChatGPT-4 is increasingly being used by patients for health information, the potential for ChatGPT-4 to serve as a clinical support tool is unclear. In this study, we found that ChatGPT-4 was frequently able to diagnose and triage knee complaints appropriately as rated by sports medicine surgeons, suggesting that it may eventually be a useful clinical support tool.

Influence of an Intrinsically Disordered Region on Protein Domains Revealed by NMR-Based Electrostatic Potential Measurements.

Many human proteins possess intrinsically disordered regions containing consecutive aspartate or glutamate residues ("D/E repeats"). Approximately half of them are DNA/RNA-binding proteins. In this study, using nuclear magnetic resonance (NMR) spectroscopy, we investigated the electrostatic properties of D/E repeats and their influence on folded domains within the same protein. Local electrostatic potentials were directly measured for the HMGB1 protein, its isolated D/E repeats, and DNA-binding domains by NMR. The data provide quantitative information about the electrostatic interactions between distinct segments of HMGB1. Due to the interactions between the D/E repeats and the DNA-binding domains, local electrostatic potentials of the DNA-binding domains within the full-length HMGB1 protein were largely negative despite the presence of many positively charged residues. Our NMR data on counterions and electrostatic potentials show that the D/E repeats and DNA have similar electrostatic properties and compete for the DNA-binding domains. The competition promotes dissociation of the protein-DNA complex and influences the molecular behavior of the HMGB1 protein. These effects may be general among the DNA/RNA-binding proteins with D/E repeats.

Assembly and Disassembly of Supramolecular Hypervalent Iodine Macrocycles via Anion Coordination.

This study explores the dynamic self-assembly and disassembly of hypervalent iodine-based macrocycles (HIMs) guided by secondary bonding interactions. The reversible disassembly and reassembly of HIMs are facilitated through anion binding via the addition of tetrabutylammonium (TBA) salts or removal of the anion by the addition of silver nitrate. The association constants for HIM monomers with TBA(Cl) and TBA(Br) are calculated and show a correlation with the strength of the iodine-anion bond. A unique tetracoordinate hypervalent iodine-based compound was identified as the disassembled monomer. Last, the study reveals the dynamic bonding nature of these macrocycles in solution, allowing for rearrangement and participation in dynamic bonding chemistry.

Refocusing the Military Health System to support Role 4 definitive care in future large-scale combat operations.

ABSTRACT: The last 20 years of sustained combat operations during the Global War on Terror generated significant advancements in combat casualty care. Improvements in point-of-injury care, en route care, and forward surgical care appropriately aligned with the survival, evacuation, and return to duty needs of the small-scale unconventional conflict. However, casualty numbers in large-scale combat operations have brought into focus the critical need for modernized casualty receiving and convalescence: Role 4 definitive care. Historically, World War II was the most recent conflict in which the United States fought in multiple operational theaters, with hundreds of thousands of combat casualties returned to the continental United States. These numbers necessitated the establishment of a "Zone of the Interior," which integrated military and civilian health care networks for definitive treatment and rehabilitation of casualties. Current security threats demand refocusing and bolstering the Military Health System's definitive care capabilities to maximize its force regeneration capacity in a similar fashion. Medical force generation, medical force sustainment and readiness, and integrated casualty care capabilities are three pillars that must be developed for Military Health System readiness of Role 4 definitive care in future large-scale contingencies against near-peer/peer adversaries.

Rotational spectroscopy of methyl tert-butyl ether with a new Ka band chirped-pulse Fourier transform microwave spectrometer.

Chirped-pulse Fourier transform microwave (CP-FTMW) spectroscopy is a powerful tool for performing broadband gas-phase rotational spectroscopy, and its applications include discovery of new molecules, complex mixture analysis, and exploration of fundamental molecular physics. Here we report the development of a new Ka band (26.5-40 GHz) CP-FTMW spectrometer that is equipped with a pulsed supersonic expansion source and a heated reservoir for low-volatility samples. The spectrometer is built around a 150 W traveling wave tube amplifier and has an instantaneous bandwidth that covers the entire Ka band spectral range. To test the performance of the spectrometer, the rotational spectrum of methyl tert-butyl ether (MTBE), a former gasoline additive and environmental pollutant, has been measured for the first time in this spectral range. Over 1000 spectroscopic transitions have been measured and assigned to the vibrational ground state and a newly-identified torsionally excited state; all transitions were fit using the XIAM program to a root-mean-square deviation of 22 kHz. The spectrum displays internal rotation splitting, nominally forbidden transitions, and an intriguing axis-switching effect between the ground and torsionally excited state that is a consequence of MTBE's extreme near-prolate nature. Finally, the sensitivity of the spectrometer enabled detection of all singly-substituted 13C and 18O isotopologues in natural abundance. This set of isotopic spectra allowed for a partial r0 structure involving the heavy atoms to be derived, resolving a structural discrepancy in the literature between previous microwave and electron diffraction measurements.

What Does the Military Health System Need to Support Future Combat Operations? Lessons from Aeromedical Evacuations from 2008 to 2020.

INTRODUCTION: Aeromedical evacuations from the past few decades have yielded massive amounts of data that may inform the Military Health System (MHS) on patient needs, specifically for understanding the inpatient and outpatient needs of evacuees. In this study, we evaluate inpatient and outpatient trends based on aeromedical evacuation data from recent conflicts. We anticipate that evacuations requiring MHS inpatient beds are primarily trauma-related and necessitate an increased need for inpatient trauma care. MATERIALS AND METHODS: We conducted a descriptive analysis of aeromedical evacuations using the U.S. Transportation Command Regulating and Command & Control Evacuation System database. We queried the database for aeromedical evacuations originating from the U.S. EUCOM and ending in the CONUS, from January 1, 2008 to June 4, 2020. With the resultant data, evacuee demographics were characterized by gender, age, active duty (AD) versus non-AD, and branch of service. Following this, the proportion of battle injury to disease and non-battle injury was categorized by both patient age ranges and year. Additionally, evacuations were stratified by their ICD codes, as well as the primary specialty responsible for care. Lastly, evacuations were categorized by inpatient and outpatient care status. RESULTS: The final dataset yielded 32,485 unique patients. The majority of evacuees were male (86.9%) with a mean age of 29.0 ± 9.6 years. Evacuees were primarily AD Military (96.7%), with the majority of those personnel being in the Army (70.2%). The total number of evacuations steadily increased from 2008 (n = 3,703) until a peak in 2010 (n = 4,929), which was also the peak year for battle injury (n = 1,472). Battle injury was also most prevalent in the 21 to 24 age group (24.7%) and declined in older age groups. Regarding diagnoses, the leading categories were injury/poisoning (33.1%), psychiatric (28.1%), and musculoskeletal (12.1%). As for specialty care of evacuees, psychiatry received the largest share of total evacuations (28.1%), followed by orthopedic surgery (22.7%) and general surgery (8.6%). Looking at proportions of inpatient and outpatient care, the majority of evacuees required outpatient care (65.6%) with a sizable minority requiring inpatient care (34.4%). Inpatient evacuations peaked in 2010 (n = 2,013), accounting for 40.8% of all evacuations that year. Orthopedic surgery had the largest share of inpatient evacuations (27.3%), followed by psychiatry (21.5%) and general surgery (18.2%). As for outpatient care, the specialties with the largest proportion of outpatient evacuations were psychiatry (33.6%), orthopedic surgery (20.3%), and neurology (9.8%). CONCLUSIONS: The results of this study reveal what the MHS can expect in future conflicts. Most evacuations are for psychiatric-/injury-/musculoskeletal-related diagnoses, typically requiring care by psychiatrists, orthopedic surgeons, or general surgeons. Outpatient care is important, though it is critical to bolster inpatient care requirements as future conflicts may bring extensive numbers of inpatient casualties. The MHS should program and plan resources accordingly, planning for the care of surgical/injured and psychiatric patients.

Combination of Counterion Size and Doping Concentration Determines the Electronic and Thermoelectric Properties of Semiconducting Polymers.

In both chemical and electrochemical doping of organic semiconductors (OSCs), a counterion, either from the electrolyte or ionized dopant, balances the charge introduced to the OSC. Despite the large influence of this counterion on OSC optical and electronic response, there remains substantial debate on how a fundamental parameter, ion size, impacts these properties. This work resolves much of this debate by accounting for two doping regimes. In the low-doping regime, the Coulomb binding energies between charge carriers on the OSC and the counterions are significant, and larger counterions lead to decreased Coulomb interactions, more delocalized charge carriers, and higher electrical conductivities. In the high-doping regime, the Coulomb binding energies become negligible due to the increased dielectric constant of the films and a smoothing of the energy landscape; thereby, the electrical conductivities depend primarily on the extent of morphological disorder in the OSC. Moreover, in regioregular poly(3-hexylthiophene), rr-P3HT, smaller counterions lead to greater bipolaron concentrations in the low-doping regime due to the increased Coulomb interactions. Emphasizing the impact of the counterion size, it is shown that larger counterions can lead to increased thermoelectric power factors for rr-P3HT.

Pannexin 1 dysregulation in Duchenne muscular dystrophy and its exacerbation of dystrophic features in mdx mice.

BACKGROUND: Duchenne muscular dystrophy (DMD) is associated with impaired muscle regeneration, progressive muscle weakness, damage, and wasting. While the cause of DMD is an X-linked loss of function mutation in the gene encoding dystrophin, the exact mechanisms that perpetuate the disease progression are unknown. Our laboratory has demonstrated that pannexin 1 (Panx1 in rodents; PANX1 in humans) is critical for the development, strength, and regeneration of male skeletal muscle. In normal skeletal muscle, Panx1 is part of a multiprotein complex with dystrophin. We and others have previously shown that Panx1 levels and channel activity are dysregulated in various mouse models of DMD. METHODS: We utilized myoblast cell lines derived from DMD patients to assess PANX1 expression and function. To investigate how Panx1 dysregulation contributes to DMD, we generated a dystrophic (mdx) mouse model that lacks Panx1 (Panx1-/-/mdx). In depth characterization of this model included histological analysis, as well as locomotor, and physiological tests such as muscle force and grip strength assessments. RESULTS: Here, we demonstrate that PANX1 levels and channel function are reduced in patient-derived DMD myoblast cell lines. Panx1-/-/mdx mice have a significantly reduced lifespan, and decreased body weight due to lean mass loss. Their tibialis anterior were more affected than their soleus muscles and displayed reduced mass, myofiber loss, increased centrally nucleated myofibers, and a lower number of muscle stem cells compared to that of Panx1+/+/mdx mice. These detrimental effects were associated with muscle and locomotor functional impairments. In vitro, PANX1 overexpression in patient-derived DMD myoblasts improved their differentiation and fusion. CONCLUSIONS: Collectively, our findings suggest that PANX1/Panx1 dysregulation in DMD exacerbates several aspects of the disease. Moreover, our results suggest a potential therapeutic benefit to increasing PANX1 levels in dystrophic muscles.

Artificial Intelligence for Clinically Meaningful Outcome Prediction in Orthopedic Research: Current Applications and Limitations.

PURPOSE OF REVIEW: Patient-reported outcome measures (PROM) play a critical role in evaluating the success of treatment interventions for musculoskeletal conditions. However, predicting which patients will benefit from treatment interventions is complex and influenced by a multitude of factors. Artificial intelligence (AI) may better anticipate the propensity to achieve clinically meaningful outcomes through leveraging complex predictive analytics that allow for personalized medicine. This article provides a contemporary review of current applications of AI developed to predict clinically significant outcome (CSO) achievement after musculoskeletal treatment interventions. RECENT FINDINGS: The highest volume of literature exists in the subspecialties of total joint arthroplasty, spine, and sports medicine, with only three studies identified in the remaining orthopedic subspecialties combined. Performance is widely variable across models, with most studies only reporting discrimination as a performance metric. Given the complexity inherent in predictive modeling for this task, including data availability, data handling, model architecture, and outcome selection, studies vary widely in their methodology and results. Importantly, the majority of studies have not been externally validated or demonstrate important methodological limitations, precluding their implementation into clinical settings. A substantial body of literature has accumulated demonstrating variable internal validity, limited scope, and low potential for clinical deployment. The majority of studies attempt to predict the MCID-the lowest bar of clinical achievement. Though a small proportion of models demonstrate promise and highlight the utility of AI, important methodological limitations need to be addressed moving forward to leverage AI-based applications for clinical deployment.

An update on endometriosis biomarkers.

Endometriosis is a debilitating gynecologic disorder characterized by chronic pelvic pain, pelvic adhesions and infertility. The gold standard diagnostic modality is histologically by tissue biopsy, although it can be diagnosed empirically if symptoms improve with medical treatment. A delayed diagnosis of endometriosis often leads to a significant impairment in quality of life and work productivity; hence, significant morbidity has been shown to bear a detrimental impact on society and the economy. The ongoing novel investigation into biomarkers for diagnostic or prognostic evaluation of endometriosis may aid in earlier detection, and thereby, improve patient quality-of-life as well as minimize morbidity. Currently, no single biomarker has been validated for endometriosis; however, there are emerging data on the utility of microRNA for diagnosis and prognosis of disease activity. In this brief review, we will identify and categorize the novel biomarkers for endometriosis.