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Jungsang Kim,1,2,* Ju-Hyun Lee,3,* Dongbin Jeong,4 Taekyung Lim,4 Sangwoo Jung,4 Kwongil Paeng,4 Sangyoup Lee,4 Hyunki Cho,4 Seungyoup Lee,4 Ikdu Kim,4 Byungsoo Kang,5,6 Jae Hyo Kim,7 Hongmin Chu,8 Museok Hong4 1Department of Preventive Medicine, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea; 2Daeat Korean Medicine Clinic, Suwon, Kyunggi-do, Republic of Korea; 3Department of Medical Support, Imsil-Gun Medical Center, Imsil, Jeollabuk-do, Republic of Korea; 4Rodam Korean Medical Clinic Network, Seoul, Republic of Korea; 5Daeat Korean Medicine Hospital, Seoul, Republic of Korea; 6Gachon University, Seongnam-si, Gyeonggi-do, Republic of Korea; 7Department of Meridian & Acupoint, College of Korean Medicine, Wonkwang University, Iksan-si, Jeollabuk-do, Republic of Korea; 8Korean Medicine Convergence Research Information Center for Stroke, College of Korean Medicine, Wonkwang University, Gwangju, Republic of Korea*These authors contributed equally to this workCorrespondence: Hongmin Chu, Korean Medicine Convergence Research Information Center for Stroke, College of Korean Medicine, Wonkwang University, Hoejaero 1140-23, Republic of Korea, Email hongminchu2@gmail.com Museok Hong, Department of Korean Internal Medicine, College of Korean Medicine, Wonkwang University, 460, Iksan-daero, Iksan-si, Jeollabuk-do, Republic of Korea, Email hongbar21@hanmail.netPurpose: This study is a retrospective, multicenter research designed to report the efficacy of Korean medicine subcision therapies in scar treatment.Patients and Methods: Charts and photographs of 29 patients who received subcision treatment between May 2016 and June 2020 in four scar treatment network clinics were analyzed. The Qualitative Global Acne Scarring Grade System (QGASC) and the Stony Brook Scar Evaluation Scale (SBSES) were used to objectively measure scar scores.Results: Except for 4 patients whose GASGS and SBSES scores remained unchanged, most patients’ scars showed improvement from Visit 2 to about Visit 8. Furthermore, the degree of change for both scales was found to be statistically significant.Conclusion: Subcision therapy using acupuncture has been found to be an effective treatment for scar, with statistically significant improvements in patients’ SBSES and QGASC scores.Keywords: scar, Korean medicine, subcision, acupuncture

A gas chromatographic-mass spectrometric (GC-MS) method for the determination of ketoprofen, a non-steroidal anti-inflammatory drug (NSAID), in horse urine by selected ion monitoring (SIM) mode is described. Urine samples (2 mL) were extracted by liquid–liquid extraction with diethyl ether. The residues were then evaporated, derivatized and injected into the GC-MS system. Validation of the GC-MS method in the SIM mode using flurbiprofen as the internal standard (IS) included linearity studies (10–10 000 ng/mL), recovery (95%) and limit of quantitation (LOQ) (10 ng/mL). The response was linear, with a correlation coefficient (0.9998) for ketoprofen. When applied to horse urine samples, the present method allowed detection of ketoprofen up to 16 days in FULL SCAN mode after a topical application of 1.1 g of ketoprofen in a gel formulation. [ABSTRACT FROM AUTHOR]

A method for the determination of fluoride by reversed-phase, high-performance liquid chromatography (RP-HPLC) is described. Fluoride, La3+ and alizarin complexone form F-La3+-alizarin complexone ternary complex, which is separated from the matrix on a RP, Ultrasphere C18 column (250 × 4.6 mm, 5 μm) using methanol-water (19:81, v/v) mobile phase at 1.00 mL min−1; detection at 568 nm. The calibration graph was linear from 1.0–150 ng mL−1 for fluoride with a correlation coefficient: 0.9993 ( n=6). The detection limit was 0.2 ng mL−1. The method was successfully applied to the determination of fluoride in river and tap water. Recovery was: 94–102%, RSD in the range: 1.9 –3.6%. [ABSTRACT FROM AUTHOR]

Purpose: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/interobserver bias and intratumor heterogeneity. We developed an artificial intelligence (AI)-powered analyzer to assess TPS for the prediction of immune checkpoint inhibitor (ICI) response in advanced non-small cell lung cancer (NSCLC)., Materials and Methods: The AI analyzer was trained with 393,565 tumor cells annotated by board-certified pathologists for PD-L1 expression in 802 whole-slide images (WSIs) stained by 22C3 pharmDx immunohistochemistry. The clinical performance of the analyzer was validated in an external cohort of 430 WSIs from patients with NSCLC. Three pathologists performed annotations of this external cohort, and their consensus TPS was compared with AI-based TPS., Results: In comparing PD-L1 TPS assessed by AI analyzer and by pathologists, a significant positive correlation was observed (Spearman coefficient = 0.925; P < .001). The concordance of TPS between AI analyzer and pathologists according to TPS ≥50%, 1%-49%, and <1% was 85.7%, 89.3%, and 52.4%, respectively. In median progression-free survival (PFS), AI-based TPS predicted prognosis in the TPS 1%-49% or TPS <1% group better than the pathologist's reading, with the TPS ≥50% group as a reference (hazard ratio [HR], 1.49 [95% CI, 1.19 to 1.86] v HR, 1.36 [95% CI, 1.08 to 1.71] for TPS 1%-49% group, and HR, 2.38 [95% CI, 1.69 to 3.35] v HR, 1.62 [95% CI, 1.23 to 2.13] for TPS <1% group)., Conclusion: PD-L1 TPS assessed by AI analyzer correlates with that of pathologists, with clinical performance also being comparable when referenced to PFS. The AI model can accurately predict tumor response and PFS of ICI in advanced NSCLC via assessment of PD-L1 TPS.

This study investigated the segmental dynamics of polymers near polymer-polymer interfaces by probing the rotation of polymer-tethered fluorescent molecules using imaging rotational fluorescence correlation microscopy. Multilayered films were utilized to provide spatial selectivity relative to different polymer-polymer interfaces. In the experimental setup, for the overlayer polymer, polystyrene (PS) was employed and a 15 nm-thick probe-containing layer was placed ≈25 nm apart from different underlayer polymers with glass transition temperatures (Tg) either lower or higher than that of PS. The underlayer of poly-n-butyl methacrylate had 72 K lower Tg than that of PS, whereas polymethyl methacrylate and polysulfone had 22 and 81 K higher Tg, respectively, than that of PS. Two key dynamic features of the glass transition, the non-Arrhenius temperature dependence and stretched relaxation, were examined to study the influence of soft and hard confinements on the segmental dynamics of the overlayer polymer near the polymer-polymer interfaces. Although complications exist in the probing location owing to the diffusion of the polymer-tethered probe during the annealing protocol to consolidate the multilayers, the results suggest that either the segmental dynamics of the polymer near the polymer-polymer interface do not change owing to the soft and hard confinements or the interfacial perturbation is very short ranged., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Metal-organic frameworks (MOFs) based on Cu-benzene tricarboxylate (CuBTC) are widely used for gas storage and removal applications. However, they readily lose their crystal structures under humid conditions, limiting their practical applications. This structural decomposition reduces the specific surface area, gas adsorption capability, and recyclability of CuBTC considerably. In this study, a stable MOF against water exposure was designed based on FeBTC nanoparticle-covered CuBTC (FeCuBTC). A simple one-pot solvothermal process that enables the epitaxial growth of FeBTC on the CuBTC surface was proposed. Structural and morphological analyses after water exposure revealed that the water stability of FeCuBTC was better than that of CuBTC, which completely lost its crystallinity. This observed improvement in the water stability of the synthesized MOF proved to be beneficial for the adsorption of formaldehyde under humid conditions. The proposed strategy herein is simple yet highly effective in the design of hetero-bimetallic MOFs with considerably improved water resistance and extended applicability for environmental remediation processes., Competing Interests: The authors declare no competing financial interest., (© 2023 The Authors. Published by American Chemical Society.)

Background: Enrichment of tumor-infiltrating lymphocytes (TIL) in the tumor microenvironment (TME) is a reliable biomarker of immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC). Phenotyping through computed tomography (CT) radiomics has the overcome the limitations of tissue-based assessment, including for TIL analysis. Here, we assess TIL enrichment objectively using an artificial intelligence-powered TIL analysis in hematoxylin and eosin (H&E) image and analyze its association with quantitative radiomic features (RFs). Clinical significance of the selected RFs is then validated in the independent NSCLC patients who received ICI., Methods: In the training cohort containing both tumor tissue samples and corresponding CT images obtained within 1 month, we extracted 86 RFs from the CT images. The TIL enrichment score (TILes) was defined as the fraction of tissue area with high intra-tumoral or stromal TIL density divided by the whole TME area, as measured on an H&E slide. From the corresponding CT images, the least absolute shrinkage and selection operator model was then developed using features that were significantly associated with TIL enrichment. The CT model was applied to CT images from the validation cohort, which included NSCLC patients who received ICI monotherapy., Results: A total of 220 NSCLC samples were included in the training cohort. After filtering the RFs, two features, gray level variance (coefficient 1.71 x 10 -3 ) and large area low gray level emphasis (coefficient -2.48 x 10 -5 ), were included in the model. The two features were both computed from the size-zone matrix, which has strength in reflecting intralesional texture heterogeneity. In the validation cohort, the patients with high predicted TILes (≥ median) had significantly prolonged progression-free survival compared to those with low predicted TILes (median 4.0 months [95% CI 2.2-5.7] versus 2.1 months [95% CI 1.6-3.1], p = 0.002). Patients who experienced a response to ICI or stable disease with ICI had higher predicted TILes compared with the patients who experienced progressive disease as the best response (p = 0.001, p = 0.036, respectively). Predicted TILes was significantly associated with progression-free survival independent of PD-L1 status., Conclusions: In this CT radiomics model, predicted TILes was significantly associated with ICI outcomes in NSCLC patients. Analyzing TME through radiomics may overcome the limitations of tissue-based analysis and assist clinical decisions regarding ICI., Competing Interests: JR, JP, and C-YO are employed by Lunit. S-HL receives honoraria from AstraZeneca/MedImmune, Roche, and Merck; takes consulting or advisory role at AstraZeneca, Roche, Merck, and Pfizer; receives research funding from Merck; and receives travel, accommodations and expenses from Novartis. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Park, Jeong, Choi, Oh, Kim, Ryu, Paeng, Lee, Ock and Lee.)

We demonstrate an approach to examine the local segmental dynamics of a polymer near the interface of an inorganic filler by observing the rotational dynamics of the fluorescent probe at the chain ends of polymer brushes grafted onto the surface of the filler particles. Localization of the fluorescent probe was realized by designing and synthesizing fluorophore-tethered polystyrene (PS) brushes anchored on the surface of silica particles of controlled sizes. Fluorophore-functionalized telechelic PS with an azide functionality at the other chain end was achieved via a combination of atom transfer radical polymerization and post-polymerization modification. The azide-bearing PS chains were tethered to alkyne-functionalized particles via copper-catalyzed cycloaddition reaction. The molecular weight of the grafted polymer chains was controlled to be less than the critical entanglement molecular weight, and the chain density was controlled to be low enough so that the observed dynamics was not perturbed by the polymer brush conformation and brush-matrix polymer entanglement. The polymer dynamics near the surface of the particles at low concentrations was closely examined in the bulk film geometry by employing imaging rotational fluorescence correlation microscopy (irFCM). The observed polymer dynamics near the interface were not altered in the inorganic/polymer composite geometry when the surface did not have favorable interaction with the matrix polymer. The presented rational design of the chemical route and examination of local dynamics highlight a feasible approach to construct material systems with high complexities towards a deeper understanding of composite materials., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Myungwoong Kim reports financial support was provided by National Research Foundation of Korea. Keewook Paeng reports financial support was provided by National Research Foundation of Korea., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The rotational dynamics of fluorescent probes of different sizes in glass-forming materials were examined to correlate the time distribution and length scale of the dynamic heterogeneity (ξ het ). As the size of the probe increased, the temperature dependence of the rotation correlation time (τ c ) shifted to longer times, and from this shift, the length scale associated with the glass transition (ξ α ) was estimated through the Debye-Stokes-Einstein (DSE) relationship and the length scale of the probe (ξ sDFT ) estimated from quantum mechanical calculations. The estimated ξ α values roughly matched with ξ het obtained from calorimetric analysis but were considerably smaller than those deduced from 4D NMR, boson peak, and four-point dynamic susceptibility measurements but with a similar trend of decrease in the length scale upon the increase in the stretching exponent (β) of the system. Because β of the glass formers represents the time distribution of the system, and τ c is related to the weighted average of the distribution, the length-scale distribution of the glass transition can be deduced by adopting the DSE relationship and assuming ξ α is the weighted average of this distribution at the glass transition temperature. In such a case, the upper bound of the length scale and trend matches the experimentally obtained ξ het from 4D NMR, boson peak, and four-point dynamic susceptibility measurements. Furthermore, at a given temperature, as the probe size increased, the β value reported by the probe increased, whereas the temperature dependence of β, which strongly correlates with the fragility of the system, was independent of the probe size.

Despite the importance of tumor-infiltrating lymphocytes (TIL) and PD-L1 expression to the immune checkpoint inhibitor (ICI) response, a comprehensive assessment of these biomarkers has not yet been conducted in neuroendocrine neoplasm (NEN). We collected 218 NENs from multiple organs, including 190 low/intermediate-grade NENs and 28 high-grade NENs. TIL distribution was derived from Lunit SCOPE IO, an artificial intelligence (AI)-powered hematoxylin and eosin (H&E) analyzer, as developed from 17,849 whole slide images. The proportion of intra-tumoral TIL-high cases was significantly higher in high-grade NEN (75.0% vs. 46.3%, p = 0.008). The proportion of PD-L1 combined positive score (CPS) ≥ 1 case was higher in high-grade NEN (85.7% vs. 33.2%, p < 0.001). The PD-L1 CPS ≥ 1 group showed higher intra-tumoral, stromal, and combined TIL densities, compared to the CPS < 1 group (7.13 vs. 2.95, p < 0.001; 200.9 vs. 120.5, p < 0.001; 86.7 vs. 56.1, p = 0.004). A significant correlation was observed between TIL density and PD-L1 CPS (r = 0.37, p < 0.001 for intra-tumoral TIL; r = 0.24, p = 0.002 for stromal TIL and combined TIL). AI-powered TIL analysis reveals that intra-tumoral TIL density is significantly higher in high-grade NEN, and PD-L1 CPS has a positive correlation with TIL densities, thus showing its value as predictive biomarkers for ICI response in NEN., Competing Interests: H-G. C., S.I.C., W.J., J.S., G.P., J.M., M.M., H.S., M.M., M.K., S.P., K.P., D.Y., and C.-Y.O. were/are employees of Lunit Inc. Other authors disclosed no relevant relationships.

Polymer networks generally consist of an ensemble of single chains. However, understanding how chain conformation affects the structure and properties of polymer networks remains a challenge for optimizing their functionality. Here, we present the fabrication and comparative study of a polymer network composed of collapsed self-entangled chains (intrachain entangled network) and a standard polymer network in which random-coil chains are entangled with each other (interchain entangled network). For poly(methyl methacrylate) thin films composed of these networks, we coupled solvent vapor swelling and single-molecule tracking techniques to examine the anomalies in the dynamics of a small-molecular probe included in the system. We demonstrate that when compared to the interchain entangled network the intrachain one exhibits a more substantial structural heterogeneity, particularly under highly crowded conditions. This network also exhibits physical compactness, which keeps the heterogeneous network structure frozen over time and impedes network plasticization through solvent uptake by the film.

Background: Manual evaluation of programmed death ligand 1 (PD-L1) tumour proportion score (TPS) by pathologists is associated with interobserver bias., Objective: This study explored the role of artificial intelligence (AI)-powered TPS analyser in minimisation of interobserver variation and enhancement of therapeutic response prediction., Methods: A prototype model of an AI-powered TPS analyser was developed with a total of 802 non-small cell lung cancer (NSCLC) whole-slide images. Three independent board-certified pathologists labelled PD-L1 TPS in an external cohort of 479 NSCLC slides. For cases of disagreement between each pathologist and the AI model, the pathologists were asked to revise the TPS grade (<1%, 1%-49% and ≥50%) with AI assistance. The concordance rates among the pathologists with or without AI assistance and the effect of the AI-assisted revision on clinical outcome upon immune checkpoint inhibitor (ICI) treatment were evaluated., Results: Without AI assistance, pathologists concordantly classified TPS in 81.4% of the cases. They revised their initial interpretation by using the AI model for the disagreement cases between the pathologist and the AI model (N = 91, 93 and 107 for each pathologist). The overall concordance rate among the pathologists was increased to 90.2% after the AI assistance (P < 0.001). A reduction in hazard ratio for overall survival and progression-free survival upon ICI treatment was identified in the TPS subgroups after the AI-assisted TPS revision., Conclusion: The AI-powered TPS analyser assistance improves the pathologists' consensus of reading and prediction of the therapeutic response, raising a possibility of standardised approach for the accurate interpretation., Competing Interests: Conflict of interest statement S.I.C., S.S., K.P., D.Y., W.J. and C.-Y.O. are employed by Lunit Inc. and has stock/stock options in Lunit Inc., and M.M., S.P., S.P. and B.J.A. are employed by Lunit Inc. No other disclosures were reported. The AI model in the study is a prototype model, and the model has developed for academic interest, not for commercialisation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Rotational-translational decoupling, in which translational motion is apparently enhanced over rotational motion in violation of Stokes-Einstein (SE) and Debye-Stokes-Einstein (DSE) predictions, has been observed in materials near their glass transition temperatures (T g ). This has been posited to result from ensemble averaging in the context of dynamic heterogeneity. In this work, ensemble and single molecule experiments are performed in parallel on a fluorescent probe in high molecular weight polystyrene near its T g . Ensemble results show decoupling onset at approximately 1.15T g , increasing to over three orders of magnitude at T g . Single molecule measurements also show a high degree of decoupling, with typical molecules at T g showing translational diffusion coefficients nearly 400 times higher than expected from SE/DSE predictions. At the single molecule level, higher degree of breakdown is associated with particularly mobile molecules and anisotropic trajectories, providing support for anomalous diffusion as a critical driver of rotational-translational decoupling and SE/DSE breakdown., (© 2022. The Author(s).)

Purpose: Biomarkers on the basis of tumor-infiltrating lymphocytes (TIL) are potentially valuable in predicting the effectiveness of immune checkpoint inhibitors (ICI). However, clinical application remains challenging because of methodologic limitations and laborious process involved in spatial analysis of TIL distribution in whole-slide images (WSI)., Methods: We have developed an artificial intelligence (AI)-powered WSI analyzer of TIL in the tumor microenvironment that can define three immune phenotypes (IPs): inflamed, immune-excluded, and immune-desert. These IPs were correlated with tumor response to ICI and survival in two independent cohorts of patients with advanced non-small-cell lung cancer (NSCLC)., Results: Inflamed IP correlated with enrichment in local immune cytolytic activity, higher response rate, and prolonged progression-free survival compared with patients with immune-excluded or immune-desert phenotypes. At the WSI level, there was significant positive correlation between tumor proportion score (TPS) as determined by the AI model and control TPS analyzed by pathologists ( P < .001). Overall, 44.0% of tumors were inflamed, 37.1% were immune-excluded, and 18.9% were immune-desert. Incidence of inflamed IP in patients with programmed death ligand-1 TPS at < 1%, 1%-49%, and ≥ 50% was 31.7%, 42.5%, and 56.8%, respectively. Median progression-free survival and overall survival were, respectively, 4.1 months and 24.8 months with inflamed IP, 2.2 months and 14.0 months with immune-excluded IP, and 2.4 months and 10.6 months with immune-desert IP., Conclusion: The AI-powered spatial analysis of TIL correlated with tumor response and progression-free survival of ICI in advanced NSCLC. This is potentially a supplementary biomarker to TPS as determined by a pathologist., Competing Interests: Sehhoon ParkStock and Other Ownership Interests: Lunit Chan-Young OckEmployment: LunitLeadership: LunitStock and Other Ownership Interests: Lunit, Medpacto, Y-BiologicsConsulting or Advisory Role: Medpacto, Y-Biologics, Idience Sergio PereiraEmployment: LunitStock and Other Ownership Interests: Lunit Seonwook ParkEmployment: LunitStock and Other Ownership Interests: LunitResearch Funding: Lunit Minuk MaEmployment: LunitStock and Other Ownership Interests: Lunit Seunghwan ShinEmployment: LunitStock and Other Ownership Interests: Lunit Jaehong AumEmployment: LunitStock and Other Ownership Interests: Lunit Kyunghyun PaengEmployment: LunitLeadership: LunitStock and Other Ownership Interests: Lunit Donggeun YooEmployment: LunitLeadership: LunitStock and Other Ownership Interests: LunitPatents, Royalties, Other Intellectual Property: Having several patents about medical AI developments in Lunit Inc Se Hyun KimConsulting or Advisory Role: Ono Pharmaceutical Jin Seok AhnHonoraria: Pfizer, Roche, BC World, Yuhan, Hanmi, Novartis, JW Pharmaceutical, Amgen, Boehringer IngelheimConsulting or Advisory Role: Bixink, Bayer, Yooyoung Pharmaceutical Co Ltd, Pharmbio Korea, Vifor Pharma Myung-Ju AhnHonoraria: AstraZeneca, Lilly, MSD, TakedaConsulting or Advisory Role: AstraZeneca, Boehringer Ingelheim, Lilly, MSD, Takeda, Alpha Pharmaceutical Keunchil ParkConsulting or Advisory Role: AstraZeneca, Lilly, Ono Pharmaceutical, Bristol Myers Squibb, MSD, Merck KGaA, AbbVie, Daiichi Sankyo, Boehringer Ingelheim, JNJ, Geinus, IMBdxSpeakers' Bureau: Boehringer IngelheimResearch Funding: AstraZeneca, MSD Oncology Sang Yong SongEmployment: AstraZeneca/MedImmuneLeadership: AstraZeneca/MedImmuneStock and Other Ownership Interests: AstraZeneca/MedImmune Yung-Jue BangConsulting or Advisory Role: BeiGene, Green Cross, Merck Serono, AstraZeneca/MedImmune, Novartis, MSD Oncology, Hanmi, Genentech/Roche, Daiichi Sankyo, Astellas Pharma, Bristol Myers Squibb, Samyang, Alexo TherapeuticsResearch Funding: AstraZeneca/MedImmune (Inst), Novartis (Inst), Genentech/Roche (Inst), MSD (Inst), Merck Serono (Inst), Bayer (Inst), GlaxoSmithKline (Inst), Bristol Myers Squibb (Inst), Pfizer (Inst), Lilly (Inst), Ono Pharmaceutical (Inst), Taiho Pharmaceutical (Inst), Takeda (Inst), BeiGene (Inst), Curis (Inst), GC Pharma (Inst), Daiichi Sankyo (Inst), Astellas Pharma (Inst), Genexine (Inst) Yoon-La ChoiResearch Funding: Bayer Tony S. MokEmployment: The Chinese University of Hong KongLeadership: Sanomics Limited, AstraZeneca, Hutchison China Meditech, Aurora Tele-Oncology Platform, LunitStock and Other Ownership Interests: Sanomics Limited, Hutchison China Meditech, Aurora Tele-Oncology PlatformHonoraria: AstraZeneca, Alpha Biopharma, ACEA Pharmaceutical Research, Amgen, Amoy Diagnostics, BeiGene, Boehringer Ingelheim, Bristol Myers Squibb, Daiichi Sankyo/UCB Japan, Fishawack Facilitate, InMed, Lilly, Merck Sharp & Dohme, Novartis, Origimed, Pfizer, Prime Oncology, Roche, Sanofi Aventis GmbH, Taiho Pharmaceutical, Takeda, Lucence Health Inc, Medscape, P. Permanyer SL, PeerVoice, Physicans' Education Resource, Research to Practice, Shanghai BeBirds Translation & Consulting Co, Liangyihui Network Technology Co., LtdConsulting or Advisory Role: AbbVie, ACEA Pharmaceutical Research, Alpha Biopharma, Amgen, Amoy Diagnostics, AstraZeneca, BeiGene, Berry Oncology, Boehringer Ingelheim, Blueprint Medicines, Bristol Myers Squibb, CStone Pharmaceuticals, Curio Science, Daiichi Sankyo/UCB Japan, Eisai, Fishawack Facilitate, Gritstone Oncology, Guardant Health, Hengrui Therapeutics, Ignyta, Incyte, Inivata, IQvia, Lilly, Loxo, Lunit, Merck Serono, Merck Sharp & Dohme, Mirati Therapeutics, Novartis, Pfizer, Puma Biotechnology, Roche, SFJ Pharmaceuticals Group, Takeda, Vertex, Yuhan, Qiming Development (HK) LtdResearch Funding: AstraZeneca (Inst), Boehringer Ingelheim (Inst), Pfizer (Inst), Novartis (Inst), SFJ Pharmaceuticals Group (Inst), Roche (Inst), Merck Sharp & Dohme (Inst), Bristol Myers Squibb (Inst), Xcovery (Inst), G1 Therapeutics (Inst), Merck Serono (Inst), Takeda (Inst) Se-Hoon LeeHonoraria: AstraZeneca/MedImmune, Roche, Bristol Myers Squibb, MerckConsulting or Advisory Role: AstraZeneca, Bristol Myers Squibb, RocheResearch Funding: MerckTravel, Accommodations, Expenses: NovartisNo other potential conflicts of interest were reported.

The tumor microenvironment can be classified into three immune phenotypes: inflamed, immune excluded, and immune-desert. Immunotherapy efficacy has been shown to vary by phenotype; yet, the mechanisms are poorly understood and demand further investigation. This study unveils the mechanisms using an artificial intelligence-powered software called Lunit SCOPE. Artificial intelligence was used to classify 965 samples of non-small-cell lung carcinoma from The Cancer Genome Atlas into the three immune phenotypes. The immune and mutational profiles that shape each phenotype using xCell, gene set enrichment analysis with RNA-sequencing data, and cBioportal were described. In the inflamed subtype, which showed higher cytolytic score, the enriched pathways were generally associated with immune response and immune-related cell types were highly expressed. In the immune excluded subtype, enriched glycolysis, fatty acid, and cholesterol metabolism pathways were observed. The KRAS mutation, BRAF mutation, and MET splicing variant were mostly observed in the inflamed subtype. The two prominent mutations found in the immune excluded subtype were EGFR and PIK3CA mutations. This study is the first to report the distinct immunologic and mutational landscapes of immune phenotypes, and demonstrates the biological relevance of the classification. In light of these findings, the study offers insights into potential treatment options tailored to each immune phenotype., (Copyright © 2022 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

We hypothesized that a deep-learning algorithm using HE images might be capable of predicting the benefits of adjuvant chemotherapy in cancer patients. HE slides were retrospectively collected from 1343 de-identified breast cancer patients at the Samsung Medical Center and used to develop the Lunit SCOPE algorithm. Lunit SCOPE was trained to predict the recurrence using the 21-gene assay (Oncotype DX) and histological parameters. The risk prediction model predicted the Oncotype DX score > 25 and the recurrence survival of the prognosis validation cohort and TCGA cohorts. The most important predictive variable was the mitotic cells in the cancer epithelium. Of the 363 patients who did not receive adjuvant therapy, 104 predicted high risk had a significantly lower survival rate. The top-300 genes highly correlated with the predicted risk were enriched for cell cycle, nuclear division, and cell division. From the Oncotype DX genes, the predicted risk was positively correlated with proliferation-associated genes and negatively correlated with prognostic genes from the estrogen category. An integrative analysis using Lunit SCOPE predicted the risk of cancer recurrence and the early-stage hormone receptor-positive breast cancer patients who would benefit from adjuvant chemotherapy., (© 2021. The Author(s).)

Objective: To assess the efficacy of three mechanical decontamination methods in four types of commercially available implants., Material and Methods: Ninety-six implants of four commercial brands with different designs (regarding thread depth and thread pitch) were soaked in a surrogate biofilm (ink) and air-dried. Circumferential standardized peri-implant defects with 6 mm in depth and 1.55 mm in width were custom-made with a 3D printer. Stained implants were inserted in the defects and instrumented with three different methods: a titanium brush (TNB), a metallic ultrasonic tip (IST) and an air abrasive (PF). Standardized photographs were taken vertically to the implant axis (flat view), and with angulations of 60° (upper view) and 120° (lower view) to the implant long axis. The percentage of residual stain (PRS) was calculated with the image analysis software. Scanning electron microscope evaluations were performed on the buccal aspect of the implants at the central level of the defect., Results: The efficacy of PF was significantly inferior to the TNB and IST in all implant designs, while there were no significant differences between TNB and IST. IST showed significantly higher PRS in the implant with the highest thread pitch, while the TNB had the highest PRS in the implant with a marked reverse buttress-thread design. The micro-thread design had the lowest values of PRS for all decontamination methods. The apically facing threads represented the areas with highest PRS for all implant designs and decontamination methods., Conclusion: Thread geometry influenced the access of the decontamination devices and in turn its efficacy. Implants with lower thread pitch and thread depth values appeared to have less residual staining., Clinical Relevance: Clinicians must be aware of the importance of thread geometry in the decontamination efficacy.

Background: The mitotic count in breast carcinoma is an important prognostic marker. Unfortunately substantial inter- and intra-laboratory variation exists when pathologists manually count mitotic figures. Artificial intelligence (AI) coupled with whole slide imaging offers a potential solution to this problem. The aim of this study was to accordingly critique an AI tool developed to quantify mitotic figures in whole slide images of invasive breast ductal carcinoma., Methods: A representative H&E slide from 320 breast invasive ductal carcinoma cases was scanned at 40x magnification. Ten expert pathologists from two academic medical centers labeled mitotic figures in whole slide images to train and validate an AI algorithm to detect and count mitoses. Thereafter, 24 readers of varying expertise were asked to count mitotic figures with and without AI support in 140 high-power fields derived from a separate dataset. Their accuracy and efficiency of performing these tasks were calculated and statistical comparisons performed., Results: For each experience level the accuracy, precision and sensitivity of counting mitoses by users improved with AI support. There were 21 readers (87.5%) that identified more mitoses using AI support and 13 reviewers (54.2%) that decreased the quantity of falsely flagged mitoses with AI. More time was spent on this task for most participants when not provided with AI support. AI assistance resulted in an overall time savings of 27.8%., Conclusions: This study demonstrates that pathology end-users were more accurate and efficient at quantifying mitotic figures in digital images of invasive breast carcinoma with the aid of AI. Higher inter-pathologist agreement with AI assistance suggests that such algorithms can also help standardize practice. Not surprisingly, there is much enthusiasm in pathology regarding the prospect of using AI in routine practice to perform mundane tasks such as counting mitoses.

We demonstrate effective functionalization chemistry for cellulose nanofiber modification using thiol functionality. Electrospun cellulose acetate nanofibers were deacetylated to obtain cellulose nanofibers, which were modified further to incorporate thiol on their surface by the esterification of hydroxyl groups with 3,3'-dithiodipropionic acid and further reductive cleavage of the disulfide bond. The thiol functionality was highly versatile to bring simple and efficient chemical reactions to attain (i) Ag nanoparticle-adsorbed cellulose nanofibers by Ag ion reduction at surface, (ii) various amine (primary amine and quaternary amine) functionalized cellulose nanofibers by Michael addition, and (iii) complex polymer functionalized cellulose nanofibers by a radical-based thiol-ene reaction, under mild conditions, i.e. in any reaction media, at room temperature, and under ambient atmosphere, evidenced by a variety of characterization methods including a quantitative analysis with X-ray photoemission spectroscopy. These scalable thiol-based chemistries should offer a new generation of well-tailored cellulose nanofiber materials with complex inorganic, organic, and polymeric functionalities, potentially expanding to functionalized surfaces of other carbohydrate-based materials to achieve the desired properties., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

How tethered probes report dynamics of host polymers near the glass transition was investigated by changing the length of the flexible linkers and the number of tethering points via imaging rotational fluorescence correlation microscopy and compared with free probes of different sizes. The results show that tethering did not alter the temperature-dependence of polymer dynamics and the shape of the correlation decay reported by the probe; however, the rotation slowed down up to ≈1 decade when both ends of the probe were restricted with short alkyl chain linkers. Upon comparison with the bigger free probe, the mechanism of the slowdown was attributed to the restricted motion upon tethering for tethered probes compared to averaging over different regions of the dynamic heterogeneity for the bigger probe. If the size of the probe was comparable to that of the dynamic heterogeneity of the system, tethered probes accurately report dynamics relevant to glass transition, regardless of tethering conditions.

Objective: To evaluate in vitro the changes in implant surface topography and roughness of commercial implants after instrumentation with five decontamination protocols., Material and Methods: Seventy-two titanium implants with a sandblasted and acid-etched (SLA) surface were placed 5 mm supra-crestally. Five groups of twelve implants were instrumented with the following protocols: a metal scaler tip (SCAL), a thermoplastic scaler tip (PEEK), a round titanium brush (RBRU), a tufted brush with titanium bristles (TNBRU), and a glycine-based air-powder abrasive (GLYC). A sixth group with untreated implants was used as control. Scanning electron microscope and confocal laser scanning microscope were utilized to evaluate the changes in the implant surfaces., Results: The SCAL caused pronounced macroscopic alterations and damage of the implant surface, the PEEK left remnants of the plastic tip in the implant surface, and both titanium brush groups flattened the thread profile, while minimal alterations were observed in the GLYC. When compared to the control group, the roughness parameters (Sa) in the buccal aspect increased in the thread area of SCAL, and a minor reduction was observed in the PEEK while in the other groups, these values remained unchanged. In the valley areas, however the RBRU, TNBRU, and GLYC experienced a significant reduction (smoothening) indicating different accessibility of the decontamination protocols to the thread and valley. Similarly, the buccal aspects had more pronounced changes than those in the palatal aspect., Conclusion: Within the limitations of this in vitro investigation, the tested protocols induced different macroscopic alterations and surface roughness changes that varied in the thread and valley area., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor proliferation assessment by image analysis only focused on mitosis detection in predefined tumor regions. However, in a real-world scenario, automatic mitosis detection should be performed in whole-slide images (WSIs) and an automatic method should be able to produce a tumor proliferation score given a WSI as input. To address this, we organized the TUmor Proliferation Assessment Challenge 2016 (TUPAC16) on prediction of tumor proliferation scores from WSIs. The challenge dataset consisted of 500 training and 321 testing breast cancer histopathology WSIs. In order to ensure fair and independent evaluation, only the ground truth for the training dataset was provided to the challenge participants. The first task of the challenge was to predict mitotic scores, i.e., to reproduce the manual method of assessing tumor proliferation by a pathologist. The second task was to predict the gene expression based PAM50 proliferation scores from the WSI. The best performing automatic method for the first task achieved a quadratic-weighted Cohen's kappa score of κ = 0.567, 95% CI [0.464, 0.671] between the predicted scores and the ground truth. For the second task, the predictions of the top method had a Spearman's correlation coefficient of r = 0.617, 95% CI [0.581 0.651] with the ground truth. This was the first comparison study that investigated tumor proliferation assessment from WSIs. The achieved results are promising given the difficulty of the tasks and weakly-labeled nature of the ground truth. However, further research is needed to improve the practical utility of image analysis methods for this task., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Automated detection of cancer metastases in lymph nodes has the potential to improve the assessment of prognosis for patients. To enable fair comparison between the algorithms for this purpose, we set up the CAMELYON17 challenge in conjunction with the IEEE International Symposium on Biomedical Imaging 2017 Conference in Melbourne. Over 300 participants registered on the challenge website, of which 23 teams submitted a total of 37 algorithms before the initial deadline. Participants were provided with 899 whole-slide images (WSIs) for developing their algorithms. The developed algorithms were evaluated based on the test set encompassing 100 patients and 500 WSIs. The evaluation metric used was a quadratic weighted Cohen's kappa. We discuss the algorithmic details of the 10 best pre-conference and two post-conference submissions. All these participants used convolutional neural networks in combination with pre- and postprocessing steps. Algorithms differed mostly in neural network architecture, training strategy, and pre- and postprocessing methodology. Overall, the kappa metric ranged from 0.89 to -0.13 across all submissions. The best results were obtained with pre-trained architectures such as ResNet. Confusion matrix analysis revealed that all participants struggled with reliably identifying isolated tumor cells, the smallest type of metastasis, with detection rates below 40%. Qualitative inspection of the results of the top participants showed categories of false positives, such as nerves or contamination, which could be targeted for further optimization. Last, we show that simple combinations of the top algorithms result in higher kappa metric values than any algorithm individually, with 0.93 for the best combination.

Using extrinsic probes to study a host system relies on the probes' ability to accurately report the host properties under study. Probes have long been used to characterize dynamic heterogeneity, the phenomenon in which a liquid near its glass transition exhibits distinct dynamics as a function of time and position, with molecules within nanometers of each other exhibiting dynamics that may vary by orders of magnitude. The spatial and temporal characteristics of dynamic heterogeneity demand the selection of probes using stringent criteria on their size and dynamics. In this report, we study the dynamic heterogeneity of the prototypical molecular glass former o -terphenyl by investigating single molecule rotation of two perylene dicarboximide probe molecules that differ in size and comparing this to results obtained previously with the probe BODIPY268. It is found that a probe's ability to accurately report dynamic heterogeneity in o -terphenyl depends on whether the reported distribution of dynamics overlaps with the intrinsic dynamics of the host, which is naturally related to the width of the intrinsic dynamics and the magnitude of dynamical shift in probe dynamics relative to the host. We show that a probe that rotates ≈15 times more slowly than the intrinsic dynamics of the host o -terphenyl senses the slowest ≈5% of the full dynamic heterogeneity whereas one that rotates ≈65 times more slowly than the host fails to report dynamic heterogeneity of the host.