Background/Objectives: This study aimed to develop and externally validate machine learning (ML) models for low-density lipoprotein cholesterol (LDL-C) estimation and compare their analytical and clinical performance with conventional formulas, particularly in individuals with elevated triglyceride (TG) levels. Methods: This retrospective study included 11,681 adults whose lipid profiles were retrieved using a laboratory information system. ML models (linear regression, random forest, support vector regression, and XGBoost) were developed using routine lipid parameters and evaluated using 10-fold cross-validation. Performance was assessed using the mean absolute error (MAE), root mean squared error (RMSE), bias, correlation, Bland-Altman agreement, and clinical classification according to LDL-C categories. Subgroup analyses were conducted across TG strata, with an emphasis on TG ≥ 400 mg/dL. Results: ML models generally demonstrated lower error and higher agreement with directly measured LDL-C levels than conventional formulas. XGBoost showed the best overall performance (MAE: 14.7 mg/dL; RMSE: 20.22 mg/dL; R2 = 0.780; r = 0.88) and the lowest deviation. The ML models also showed a higher clinical classification accuracy (up to 66%). Performance declined with increasing TG levels, particularly for conventional formulas, whereas ML models remained more stable, including patients with TG ≥ 400 mg/dL. External validation across independent cohorts and analytical platforms demonstrated stable performance of the XGBoost model and generally higher classification accuracy than conventional LDL-C estimation formulas. Conclusions: ML-based LDL-C estimation may represent a complementary alternative to conventional formulas, particularly in hypertriglyceridemic populations.

Tomographic volumetric additive manufacturing (TVAM) is an emerging 3D printing technology capable of producing complex structures in seconds. However, achieving reliable prints using TVAM requires sufficient light penetration throughout the print volume, which often limits the photoinitiator (PI) concentration that can be used. In (meth)acrylate-based photoresins, this constraint severely restricts achievable print size and quality due to oxygen inhibition. To address this challenge, a chemical strategy is demonstrated to control the oxygen inhibition period without compromising light penetration, using an amine, a thiol, and a phosphine additive as representative examples. Among these, N-methyldiethanolamine (MDEA) emerged as the most promising candidate, effectively reacting with non-reactive peroxy radicals to regenerate propagating radicals and sustain polymerization. Incorporating MDEA into a low-PI photoresin enabled high-resolution and large-volume printing in a custom-built TVAM system, achieving a root-mean-square surface deviation of 0.175 mm (≈2 pixels) and printable structure sizes up to 60 mm. These advances represent a 16-fold increase in print volume relative to the previous TVAM demonstrations and enable high-throughput fabrication of multiple complex parts without sacrificing print quality. This work establishes a scalable approach to overcoming oxygen inhibition in (meth)acrylate TVAM systems, unlocking new possibilities for large-volume, high-resolution additive manufacturing.

Physiological closed-loop controlled (PCLC) medical devices, such as those designed for blood pressure regulation, can be tested for safety and efficacy in real-world clinical settings. However, relying solely on limited animal and clinical studies may not capture the diverse range of physiological conditions. Credible mathematical models can complement these studies by allowing the testing of the device against simulated patient scenarios. This research involves the development and validation of a low-order lumped-parameter mathematical model of the cardiovascular system's response to fluid perturbation. The model takes rates of hemorrhage and fluid infusion as inputs and provides hematocrit and blood volume, heart rate, stroke volume, cardiac output and mean arterial blood pressure as outputs. The model was calibrated using data from 27 sheep subjects, and its predictive capability was evaluated through a leave-one-out cross-validation procedure, followed by independent validation using 12 swine subjects. Our findings showed small model calibration error against the training dataset, with the normalized root-mean-square error (NRMSE) less than 10% across all variables. The mathematical model and virtual patient cohort generation tool demonstrated a high level of predictive capability and successfully generated a sufficient number of subjects that closely resembled the test dataset. The average NRMSE for the best virtual subject, across two distinct samples of virtual subjects, was below 12.7% and 11.9% for the leave-one-out cross-validation and independent validation dataset. These findings suggest that the model and virtual cohort generator are suitable for simulating patient populations under fluid perturbation, indicating their potential value in PCLC medical device evaluation.

Root-knot nematodes (RKNs, Meloidogyne spp.) are some of the most economically important and common plant parasitic nematodes in North Carolina (NC) cropping systems. Soil samples collected from fields planted with crops rotated with sweetpotato (Ipomoea batatas [L.] Lam.) in 39 NC counties in 2015 to 2018 were processed at the NC Nematode Assay Laboratory. The occurrence of second-stage juvenile (J2) RKN populations was examined based on collection year, month, county, and previous planted crop. The highest number of RKN-positive samples originated from Cumberland (53%), Sampson (48%), and Johnston (48%) counties. The highest average RKN population density was detected in Sampson (147 J2/500 cm[3] of soil) and Nash (135 J2/500 cm[3] of soil) counties, while Wayne (7 J2/500 cm[3] of soil) and Greene (11 J2/500 cm[3] of soil) counties had the lowest average RKN population density. Meloidogyne enterolobii is a new invasive species that is impacting sweetpotato growers of NC. The host status of an NC population of M. enterolobii, the guava RKN, was determined by examining eggs per gram of fresh root (ER) and the final nematode egg population divided by the initial population egg count (reproductive factor, RF) in greenhouse experiments. This included 18 vegetable, field, and cover crops and weed species. The tomato 'Rutgers' was used as a susceptible control. Cabbage 'Stonehead', pepper 'Red Bull', and watermelon 'Charleston Gray' and 'Fascination' were hosts and had similar mean ER values to the positive control, ranging from 64 to 18,717. Among field crops, cotton, soybean 'P5018RX', and tobacco were hosts with ER values that ranged from 185 to 706. Members of the Poaceae family such as sweet corn (Zea mays) and sudangrass (Sorghum × drummondii) were nonhosts to M. enterolobii, and the mean ER values ranged from 1.85 to 7. The peanut 'Tifguard' and winter wheat (Triticum aestivum) also had lower ER values than the vegetable hosts. Growers should consider planting less susceptible hosts or nonhosts such as peanut, sudangrass, sweet corn, and winter wheat in 2- to 3-year crop rotations to lower populations of this invasive nematode.

Telogen effluvium is a form of nonscarring alopecia characterized by diffuse, often acute hair shedding.[1][2][3][4][5] Another form that is chronic with a more insidious onset also exists. Telogen effluvium is excessive shedding of resting or telogen hair after some metabolic stress, hormonal changes, or medication. Telogen hair is also known as club hair due to the shape of the root. In a normal healthy person's scalp, about 85% are anagen hair and 15% are telogen hair. Anagen hair are actively growing hair while telogen hair are resting hair. A few hairs may also be in catagen. A hair follicle usually grows anagen hair for almost four years, then rests for about four months. A new anagen hair begins to grow under the resting telogen hair and pushes it out. If there is some kind of stress to the body it can cause 70% of anagen hair to precipitate into the telogen phase thus causing hair loss.

Anagen effluvium is a form of nonscarring alopecia commonly associated with chemotherapy. In this disorder, affected anagen hairs suffer a toxic or inflammatory insult, resulting in fracture of the hair shaft.[1][2][3] Anagen effluvium is often referred to as chemotherapy-induced alopecia, as it can be triggered by antimetabolites, alkylating agents, and mitotic inhibitors administered as chemotherapeutic therapy. Shedding usually takes place within 14 days of administration of the offending drug, however, in many instances it is reversible, with hair regrowth occurring upon discontinuation of the offending agent. The hair shaft is commonly damaged, and tapered fractures of anagen hairs can be appreciated on trichoscopy. An understanding of the cyclical phases of hair growth and anatomy of the hair follicle is essential to understanding anagen effluvium. There are roughly 100,000 hairs on the scalp; any given hair is constantly cycling between three stages: anagen, catagen, and telogen. Anagen is a growth phase, lasting between 2 and 6 years with an average of 3 years. Approximately 90% of hairs taken from a normal scalp are anagen hairs. This is a period of epithelial proliferation, in which bulb matrix cells undergo mitosis and proliferation to form the hair shaft. Severe insult to the hair bulb or hair matrix in the form of medications, toxin exposure, or inflammation that causes a cessation of this mitotic activity can cause damage to the hair shaft resulting in breakage, and if the bulb is affected, complete hair loss. Catagen is a transitional phase between anagen and telogen, and in this phase, all growth ceases. Less than 1% of scalp hairs are in catagen at any given time. Telogen is a resting phase, lasting approximately 3 to 5 months, immediately before the hair falls out (teloptosis). Telogen effluvium, a separate entity, occurs when anagen hairs are prematurely shifted into the telogen phase and is triggered by medications, physical or psychological stressors, hospitalization, and pregnancy, among other causes. Kenogen is the lag phase between loss of telogen hair and the growth of new hair.[4][5][6]

Hair growth is cyclical, and follicles undergo corresponding phases of growth (anagen), involution (catagen), and quiescence (telogen).[1][2] Loose anagen hair syndrome (LAS) is a condition inherited in autosomal dominant fashion with incomplete penetrance or as sporadic cases. It is characterized by non-scarring alopecia with increased hair shedding due to poorly anchored anagen hairs. The disease presents most commonly in female children with diffuse thinning and textural changes characterized as unruly.[1] Hairs are easily and painlessly removed during daily activities and reproduced with a hair pull test. On light microscopy, a deformed anagen bulb, absent inner root sheath, and ruffled cuticle are present.[1][3] Histopathologic exam, although not a part of routine diagnosis, reveals premature and defective keratinization of the inner root sheath. Most cases resolve spontaneously, but topical minoxidil may be used as first-line therapy in infants and children.[1]

Tinea capitis is a fungal infection of the scalp hairs. Tinea capitis is also known as ringworm and herpes tonsurans infection.[1] It is caused primarily by the dermatophyte species Microsporum and Trichophyton. The fungi can penetrate the hair follicle outer root sheath and ultimately may invade the hair shaft. Clinically, tinea capitis divides into inflammatory and non-inflammatory types. The non-inflammatory type usually will not be complicated by scarring alopecia. The inflammatory type may result in a kerion (painful nodules with pus) as well as scarring alopecia.[2] Tinea capitis occurs primarily in children between 3 and 14 years of age, but it might affect any age group. It may also involve the eyelashes and eyebrows.

Patient safety education is a mandated Common Program Requirement of the Accreditation Council for Graduate Medical Education and for the Royal College of Physicians and Surgeons of Canada in all medical residency and fellowship programs. Although many hospitals and healthcare environments have general patient safety education tools for trainees, few to none focus on the unique training milieu of pathologists, including a mix of highly automated and manual error-prone processes, frequent multiplicity of events, and lack of direct patient relationships for error disclosure. We established a national Association of Pathology Chairs-Program Directors Section Workgroup focused on patient safety education for pathology trainees entitled Training Residents in Patient Safety (TRIPS). TRIPS included diverse representatives from across the United States, as well as representatives from pathology organizations including the American Board of Pathology, the American Society for Clinical Pathology, the United States and Canadian Academy of Pathology, the College of American Pathologists, and the Society to Improve Diagnosis in Medicine. Objectives of the workgroup included developing a standardized patient safety curriculum, designing teaching and assessment tools, and refining them with pilot sites. Here we report the establishment of TRIPS as well as data from national needs assessment of Program Directors across the country, who confirmed the need for a standardized patient safety curriculum.

Control of spotted-wing Drosophila, Drosophila suzukii, in small fruits emphasizes biological, cultural, and chemical approaches, whereas studies of host plant resistance as a form of genetic control are just getting underway. The identification of resistance patterns among genotypes of host plants whose fruit, leaves, roots, stems, or seeds are specifically targeted by an invasive pest is the first step in the development of an effective genetic control. Therefore, a detached fruit bioassay was developed to screen for D. suzukii oviposition and larval infestation within berries from 25 representative species and hybrids of wild and cultivated Vaccinium. Ten Vaccinium species showed strong resistance; among them, two wild diploids originating from within the fly's native range: V. myrtoides and V. bracteatum. Other resistant species came from the sections Pyxothamnus and Conchophyllum. They included New World V. consanguineum and V. floribundum. Large-cluster blueberry, V. amoenum, and three Floridian genotypes of related rabbiteye blueberry, V. virgatum, were the only hexaploids expressing strong resistance against D. suzukii. Most screened blueberry genotypes from managed lowbush and cultivated highbush types were susceptible to the flies' attacks (i.e., oviposition). Tetraploid blueberries tended to host the most eggs, whereas diploids and hexaploids harbored 50%-60% fewer eggs, on average. D. suzukii cannot lay eggs or complete development in the smallest, sweetest, and firmest diploid fruits. Likewise, certain genotypes of large-fruited tetraploid and hexaploid blueberry strongly curbed D. suzukii egg-laying and larval growth, indicating the possibility of heritable resistance operating against this invasive fly species.