Hudson Institute

Laser resurfacing, with erbium-doped yttrium aluminum garnet (Erbium:YAG) lasers, is a leading treatment for photoaging owing to its relatively rapid healing profile. However, even with advanced technology, there remains a need for adjunctive topical treatments to enhance skin recovery, mitigate postprocedure pigmentation issues, and minimize postprocedure downtime. This randomized, evaluator-blinded, controlled study evaluated a regenerative cream's performance following laser treatment. The study utilized a mini-zone model on the volar forearms of healthy participants to compare the cream's efficacy against laser treatment alone. Clinical and instrumental assessments were utilized to assess the efficacy of the regenerative cream in accelerating skin healing post laser. Within 7days of treatment, the regenerative cream significantly improved skin hydration (76%, p < 0.05) and smoothness (10%, p < 0.05), reduced skin roughness, crusting/scaling (49%, p < 0.05), and visual skin uniformity (49%, p < 0.05), compared with laser treatment alone. In addition, the regenerative cream showed greater reduction in skin redness (-27%, p < 0.05) than laser alone at day 18 post laser. Moreover, the regenerative cream outperformed an anhydrous benchmark formula in hydration, skin smoothness, and roughness after just 7 days. These findings highlight the potential of the regenerative cream as a valuable addition to laser resurfacing procedures, promoting faster healing with improved aesthetic outcomes.

This study investigates the effect of overburden stress (effective confining stress) on liquefaction triggering using the largest cyclic test dataset ever applied to this crucial topic. The dataset includes 225 overburden stress correction factor (Kσ) values derived from a wide range of confining stresses, relative densities, and fine contents. Our analysis reveals that specimen preparation methods, particularly tamping and compaction, significantly affect Kσ values. Compaction stresses due to tamping and compaction induce an overconsolidation ratio that changes with confining pressure, which may produce a larger apparent effect of confining pressure on Kσ. We propose a new model for estimating Kσ for clean, normally consolidated sands, which shows less dependence on confining pressure and relative density than existing models. The effect of fines content on Kσ could not be isolated from other effects because fine-grained specimens in prior research were generally prepared using tamping and compaction methods. The proposed Kσ model is intended to isolate the effect of overburden stress, enabling its use in liquefaction triggering models where different effects are accounted for by distinct correction factors.

We describe a 42-year-old female with a past medical history significant for antiphospholipid syndrome (APS) who presented as a transfer to our facility for evaluation of stroke-like symptoms. She experienced acute onset dysarthria, left-sided weakness and a fixed rightward gaze preference. She was not a candidate for tenecteplase due to outpatient direct oral anticoagulant therapy. Computed tomography (CT) imaging of the head confirmed an acute infarct to the middle cerebral artery territory. She was taken for an emergent mechanical thrombectomy which she tolerated well. Repeat CT imaging ruled out hemorrhagic conversion. Transthoracic echocardiography revealed a 1.3 cm x 1.2 cm spherical mobile mass on the mitral valve, associated with a moderate to severe mitral regurgitation that was confirmed by transesophageal echocardiogram. The patient's respiratory status unfortunately declined and was consequently intubated. Blood cultures were negative and there was no history of intravenous drug use. The vegetation was considered marantic, representing nonbacterial thrombotic endocarditis (NBTE) secondary to APS and medication nonadherence. Cardiothoracic surgery offered surgical valve replacement after clinical recovery on an outpatient basis. She was subsequently extubated, transitioned to warfarin as recommended by hematology, weaned off supplemental oxygen, and discharged to inpatient rehab. Antiphospholipid syndrome is an autoimmune condition characterized by recurrent thrombosis and pregnancy morbidity, accompanied by the presence of antiphospholipid antibodies. A known complication of APS is NBTE and embolization of these vegetations contributes to the risk of thromboembolic events, such as stroke as seen in our patient. We discuss a multidisciplinary approach is imperative to ischemic stroke workup, particularly in the context of APS with developing catastrophic antiphospholipid syndrome. We also point out evidence suggesting direct oral anticoagulants are less effective than warfarin for thrombus prevention, however contemporary studies are limited.

We present the first mixed-method study to explore the experiences of Black, Asian and Minority Ethnic (BAME) students studying psychology in the UK. We co-created a survey with undergraduate student research assistants, which was completed by 195 students, of which 106 were from BAME backgrounds and 89 were from White backgrounds. All students were studying psychology as undergraduate or postgraduate students at two UK universities. Using the survey, we compared BAME and White students’ experiences and views about their curriculum, delivery of teaching, personal tutoring support, course resources, peer relationships, representation, course community, approaches to study, and their engagement. We found differences in how well represented students felt in the curriculum and amongst their peers according to university and ethnicity. Following the survey, 27 BAME students took part in focus group interviews. Using a thematic content analysis approach, these students reported category themes of issues with representation within the curriculum, pedagogy, and staff representation. Challenges in their sense of belonging to the department and university were also reported. The study indicates that all psychology students are calling for psychology departments to enhance their curriculum’s ethnic representation and anti-racist pedagogy. Meanwhile, BAME students are calling for efforts to enhance a sense of belonging and awareness of BAME-related issues amongst staff and their peers. This bolsters the importance of work to diversify the psychology curriculum and highlights the implications of a lack of diversity in future psychology careers and mental health support.

CXL.mem and the resulting memory pool are promising and gaining great attention. Unlike local memory, CXL DIMMs stay at the I/O subsystem, whose inferior performance can easily impact the processor pipeline and memory subsystem, yielding performance interference, hardware contention, obscure behaviors, and underutilized communication and computing resources. However, our community lacks a tool to understand and profile the CXL.mem protocol execution end-to-end between CPU and remote DIMM.

Summary Cancer immunotherapy has transformed cancer treatment by harnessing the immune system’s natural ability to recognize and eliminate tumor cells, offering an effective and less toxic alternative particularly suitable for pediatric patients. Advances such as immune checkpoint inhibitors targeting PD-1 and CTLA-4, successful adoptive cell therapies like CAR T-cell treatments, and innovative cancer vaccines have notably improved outcomes across various cancer types. Central to immunotherapy is antigen presentation, where tumor-derived peptides loaded onto the Major Histocompatibility Complex molecules facilitate immune recognition. Precise HLA typing is crucial, especially in pediatric cancer research, where cell lines serve as essential preclinical models. The Childhood Cancer Model Atlas (CCMA) initiative provides comprehensive profiling, including HLA typing and neoantigen predictions for 287 cancer cell lines. This publicly accessible resource enables researchers to better understand immune-cancer interactions, advance personalized immunotherapies, and develop targeted, less toxic treatments specifically beneficial for children with cancer.

Abstract. Technologies such as machine learning and deep learning are powering the discovery of meaningful patterns in Earth science big data. In the field of mineralogy, Mindat (“mindat.org”) is one of the largest databases. Although its front-end website is open and free, a machine interface for bulk data query and download had never been set up before 2022. Through a project called OpenMindat, an application programming interface (API) to enable open data query and access from Mindat was set up in 2023. To further lower the barrier between Mindat open data and geoscientists with limited coding skills, we developed an R package (OpenMindat v1.0.0) on top of the API. The Mindat API includes multiple data subjects such as geomaterials (e.g., rocks, minerals, synonyms, variety, mixture, and commodity), localities, and the IMA-approved (International Mineralogical Association) mineral list. The OpenMindat v1.0.0 package wraps the capabilities of the Mindat API and is designed to be user-friendly and extensible. In addition to providing functions for querying data subjects on the API, the package supports exporting data to various formats. In real-world applications, these functions only require minor coding for users to get desired datasets, and various other packages in the R environment can be used to analyze and visualize the data. The OpenMindat v1.0.0 package, which includes detailed tutorials and examples, is available on GitHub under the MIT license. The field of mineralogy and many other geoscience disciplines are facing opportunities enabled by open data. Various research topics such as mineral network analysis, mineral association rule mining, mineral ecology, mineral evolution, and critical minerals have already benefited from Mindat's open data efforts in recent years. We hope this R package can help accelerate those data-intensive studies and lead to more scientific discoveries.

The online version contains supplementary material available at 10.1007/s40203-025-00391-9.

Powered by data-driven knowledge discovery technologies such as machine learning and deep learning, increasingly exciting patterns are discovered in complex earth science big data. One of the world's most enormous treasure troves of mineral databases, Mindat ("mindat.org"), contains vast amounts of knowledge that are yet to be mined. Through a project called OpenMindat, an application programming interface (API) to enable open data query and access from Mindat had been set up. This paper presents an open-source R package (OpenMindat v1.0.0) to bridge the data highway, connecting users' overwhelming data needs, facilitating data-intensive query and access, unlocking novel insights, and enabling groundbreaking geoscience discoveries. The package was designed to be user-friendly and extensible. It exploits the capabilities of the Mindat API, including the data subjects of geomaterials (e.g., rocks, minerals, synonyms, variety, mixture, and commodity), localities, and the IMA (International Mineralogical Association)-approved mineral list. In addition to providing functions for querying those data subjects, the package supports exporting data to various formats such as CSV, JSON-LD, and TTL. In applications, these functions only require minor coding and provide invaluable convenience for users with limited R environment experience. The package is open on GitHub under the MIT license and with detailed tutorial documentation. The field of mineralogy and many other geoscience disciplines are facing the opportunities enabled by open data. Various research topics such as mineral network analysis, mineral association rule mining, mineral ecology, mineral evolution, and critical minerals have already benefited from Mindat's open data. We hope this R package will accelerate the process of those data-intensive studies and lead to more scientific discoveries. As machine learning and deep learning techniques thrive on their ability to discern intricate patterns and correlations, datadriven discoveries in geosciences yield more exciting results (