Is postmastectomy radiotherapy necessary for breast cancer patients with clinically node-positive downstaging to ypN0 after neoadjuvant chemotherapy?

PURPOSE: The significance of postmastectomy radiotherapy (PMRT) in breast cancer patients who initially have clinically node-positive (cN +) status but achieve downstaging to ypN0 following neoadjuvant chemotherapy (NAC) remains uncertain. This study aims to assess the impact of PMRT in this patient subset. METHODS: Patients were enrolled from West China Hospital, Sichuan University from 2008 to 2019. Overall survival (OS), Locoregional recurrence-free survival (LRFS), distant metastasis-free survival (DMFS), and breast cancer-specific survival (BCSS) were estimated using the Kaplan-Meier method and assessed with the log-rank test. The impact of PMRT was further analyzed by the Cox proportional hazards model. Propensity score matching (PSM) was performed to reduce the selection bias. RESULTS: Of the 333 eligible patients, 189 (56.8%) received PMRT, and 144 (43.2%) did not. At a median follow-up period of 71 months, the five-year LRFS, DMFS, BCSS, and OS rates were 99.1%, 93.4%, 96.4%, and 94.3% for the entire cohort, respectively. Additionally, the 5-year LRFS, DMFS, BCSS, and OS rates were 98.9%, 93.8%, 96.7%, and 94.5% with PMRT and 99.2%, 91.3%, 94.9%, and 92.0% without PMRT, respectively (all p-values not statistically significant). After multivariate analysis, PMRT was not a significant risk factor for any of the endpoints. When further stratified by stage, PMRT did not show any survival benefit for patients with stage II-III diseases. CONCLUSION: In the context of comprehensive treatments, PMRT might be exempted in ypN0 breast cancer patients. Further large-scale, randomized controlled studies are required to investigate the significance of PMRT in this patient subset.

DTI-MR fingerprinting for rapid high-resolution whole-brain T1 , T2 , proton density, ADC, and fractional anisotropy mapping.

PURPOSE: This study aims to develop a high-efficiency and high-resolution 3D imaging approach for simultaneous mapping of multiple key tissue parameters for routine brain imaging, including T1 , T2 , proton density (PD), ADC, and fractional anisotropy (FA). The proposed method is intended for pushing routine clinical brain imaging from weighted imaging to quantitative imaging and can also be particularly useful for diffusion-relaxometry studies, which typically suffer from lengthy acquisition time. METHODS: To address challenges associated with diffusion weighting, such as shot-to-shot phase variation and low SNR, we integrated several innovative data acquisition and reconstruction techniques. Specifically, we used M1-compensated diffusion gradients, cardiac gating, and navigators to mitigate phase variations caused by cardiac motion. We also introduced a data-driven pre-pulse gradient to cancel out eddy currents induced by diffusion gradients. Additionally, to enhance image quality within a limited acquisition time, we proposed a data-sharing joint reconstruction approach coupled with a corresponding sequence design. RESULTS: The phantom and in vivo studies indicated that the T1 and T2 values measured by the proposed method are consistent with a conventional MR fingerprinting sequence and the diffusion results (including diffusivity, ADC, and FA) are consistent with the spin-echo EPI DWI sequence. CONCLUSION: The proposed method can achieve whole-brain T1 , T2 , diffusivity, ADC, and FA maps at 1-mm isotropic resolution within 10 min, providing a powerful tool for investigating the microstructural properties of brain tissue, with potential applications in clinical and research settings.

Metabolic engineering of "last-line antibiotic" colistin in Paenibacillus polymyxa.

Colistin, also known as polymyxin E, is a lipopeptide antibiotic used to treat infections caused by multidrug-resistant gram-negative bacteria. It is considered a "last-line antibiotic", but its clinical development is hindered by low titer and impurities resulting from the presence of diverse homologs in microbial fermentation. To ensure consistent pharmaceutical activity and kinetics, it is crucial to have high-purity colistin active pharmaceutical ingredient (API) in the pharmaceutical industry. This study focused on the metabolic engineering of a natural colistin producer strain to produce colistin with a high titer and purity. Guided by genome mining, we identified Paenibacillus polymyxa ATCC 842 as a natural colistin producer capable of generating a high proportion of colistin A. By systematically inactivating seven non-essential biosynthetic gene clusters (BGCs) of peptide metabolites that might compete precursors with colistin or inhibit colistin production, we created an engineered strain, P14, which exhibited an 82% increase in colistin titer and effectively eliminated metabolite impurities such as tridecaptin, paenibacillin, and paenilan. Additionally, we engineered the L-2,4-diaminobutyric acid (L-2,4-DABA) pathway to further enhance colistin production, resulting in the engineered strain P19, which boosted a remarkable colistin titer of 649.3 mg/L - a 269% improvement compared to the original strain. By concurrently feeding L-isoleucine and L-leucine, we successfully produced high-purity colistin A, constituting 88% of the total colistin products. This study highlights the potential of metabolic engineering in improving the titer and purity of lipopeptide antibiotics in the non-model strain, making them more suitable for clinical use. These findings indicate that efficiently producing colistin API in high purity directly from fermentation can now be achieved in a straightforward manner.

Development and Validation of a Clinical Prediction Model for Diagnosing Mycoplasma Infections in Gynecological Patients.

BACKGROUND: In adult females, mycoplasma infection is common and challenging to diagnose. This study aimed to use retrospective laboratory data to construct a nomogram for predicting the mycoplasma infection of individuals with probable urogenital tract mycoplasma infection. METHODS: A total of 2,859 patients with suspected urogenital tract mycoplasma infection were retrospectively enrolled in this study. Demographics and routine examinations of leucorrhea were used to develop a nomogram for predicting mycoplasma infection. The least absolute shrinkage and selection operator (LASSO) method was applied to filter variables and select predictors, and multivariable logistic regression was used to construct a nomogram. The discriminatory ability of the model was determined by calculating the area under the curve (AUC). The performance and clinical utility of the nomogram were generated by using Harrell's concordance index, calibration curve, and decision curve analysis (DCA). RESULTS: By using the LASSO regression method, seven variables (age, white blood cell, epithetical cell, cleanliness, candidiasis vaginalis, sialidases, and leukocyte esterase) were chosen, and a nomogram was constructed using these variables. The prediction nomogram (0.676, 95% CI: 0.611 - 0.744) demonstrated a satisfactory performance. The prediction model's AUC was 0.679 (95% CI: 0.660 - 0.691). Furthermore, the DCA showed a good clinical net benefit based on the mycoplasma infection nomogram. CONCLUSIONS: A nomogram was created in this study, which included seven demographic and clinical characteristics of female patients. The nomogram could be of great value for the diagnosis of mycoplasma infection.

Insights into myopic choroidal neovascularization based on quantitative proteomics analysis of the aqueous humor.

BACKGROUND: Previous studies on the biomarkers of pathologic myopia choroidal neovascularization (pmCNV) development merely detected limited types of proteins and provide a meagre illustration of the underlying pathways. Hence, a landscape of protein changes in the aqueous humor (AH) of pmCNV patients is lacking. Here, to explore the potential mechanisms and biomarkers of pmCNV, we analyzed the clinical data and protein profile among atrophic (A) lesions, tractional lesions (T) and neovascular (N) lesions in myopic patients based on the ATN grading system for myopic maculopathy (MM). RESULTS: After investigating demographic data of our patients, a correlation was found between A and N lesions (R = 0.5753, P < 0.0001). Accordingly, groups were divided into patients without MM, patients with myopic atrophic maculopathy (MAM), and patients with pmCNV (N2a lesion). In proteomics analysis, the increased protein level of GFAP and complement-associated molecules in AH samples of the 3 groups also indicated that MAM and pmCNV shared similar characteristics. The GO enrichment and KEGG pathway analysis were performed, which mapped that differential expressed proteins mainly engaged in JAK-STAT pathway between the pmCNV group and two controls. Furthermore, we identified several potential biomarkers for pmCNV, including FCN3, GFAP, EGFR, SFRP3, PPP2R1A, SLIT2, and CD248. CONCLUSIONS: Atrophic lesions under pathologic myopic conditions demonstrated similarities to neovascularization development. Potential biomarkers including GFAP were associated with the pathogenesis of pmCNV. In summary, our study provides new insights for further research on pmCNV development.

In Situ Confining Citric Acid-Derived Carbon Dots for Full-Color Room-Temperature Phosphorescence.

Room-temperature phosphorescence has received much attention owing to its potential applications in information encryption and bioelectronics. However, the preparation of full-color single-component-derived phosphorescent materials remains a challenge. Herein, a facile in situ confining strategy is proposed to achieve full-color phosphorescent carbon dots (CDs) through rapid microwave-assisted carbonization of citric acid in NaOH. By tuning the mass ratio of citric acid and NaOH, the obtained CDs exhibit tunable phosphorescence wavelengths ranging from 483 to 635 nm and alterable lifetimes from 58 to 389 ms with a synthesis yield of up to 83.7% (>30 g per synthesis). Theoretical calculations and experimental results confirm that the formation of high-density ionic bonds between cations and CDs leads to efficient afterglow emission via the dissociation of CD arrangement, and the evolution of the aggregation state of CDs results in redshifted phosphorescence. These findings provide a strategy for the synthesis of new insights into achieving and manipulating room-temperature phosphorescent CDs, and prospect their applications in labeling and information encryption.

Multi-readout DWI with a reduced FOV for studying the coupling between diffusion and T 2 * relaxation in the prostate.

PURPOSE: To develop a DWI sequence with multiple readout echo-trains in a single shot (multi-readout DWI) over a reduced FOV, and to demonstrate its ability to achieve high data acquisition efficiency in the study of coupling between diffusion and relaxation in the human prostate. METHODS: The proposed multi-readout DWI sequence plays out multiple EPI readout echo-trains after a Stejskal-Tanner diffusion preparation module. Each EPI readout echo-train corresponded to a distinct effective TE. To maintain a high spatial resolution with a relatively short echo-train for each readout, a 2D RF pulse was used to limit the FOV. Experiments were performed on the prostate of six healthy subjects to acquire a set of images with three b values (0, 500, and 1000 s/mm2 ) and three TEs (63.0, 78.8, and 94.6 ms), producing three ADC maps at different TEs and three T 2 * $$ {T}_2^{\ast } $$ maps at different b values. RESULTS: Multi-readout DWI enabled a threefold acceleration without compromising the spatial resolution when compared with a conventional single-readout sequence. Images with three b values and three TEs were obtained in 3 min 40 s with an adequate SNR (≥ 26.9). The ADC values (1.45 ± 0.13, 1.52 ± 0.14, and 1.58 ± 0.15  µm 2 / ms $$ {\upmu \mathrm{m}}^2/\mathrm{ms} $$ ; P < 0.01) exhibited an increasing trend as TEs increased (63.0 ms, 78.8 ms, and 94.6 ms), whereas T 2 * $$ {T}_2^{\ast } $$ values (74.78 ± 13.21, 63.21 ± 7.84, and 56.61 ± 5.05 ms; P < 0.01) decreases as the b values increased (0, 500, and 1000 s/mm2 ). CONCLUSION: The multi-readout DWI sequence over a reduced FOV provides a time-efficient technique to study the coupling between diffusion and relaxation times.

Hybrid Spin and Anomalous Spin-Momentum Locking in Surface Elastic Waves.

Transverse spin of surface waves is a universal phenomenon which has recently attracted significant attention in optics and acoustics. It appears in gravity water waves, surface plasmon polaritons, surface acoustic waves, and exhibits remarkable intrinsic spin-momentum locking, which has found useful applications for efficient spin-direction couplers. Here we demonstrate, both theoretically and experimentally, that the transverse spin of surface elastic (Rayleigh) waves has an anomalous sign near the surface, opposite to that in the case of electromagnetic, sound, or water surface waves. This anomalous sign appears due to the hybrid (neither transverse nor longitudinal) nature of elastic surface waves. Furthermore, we show that this sign anomaly can be employed for the selective spin-controlled excitation of symmetric and antisymmetric Lamb modes propagating in opposite directions in an elastic plate. Our results pave the way for spin-controlled manipulation of elastic waves and can be important for a variety of areas, from phononic spin-based devices to seismic waves.

P16INK4a Upregulation Mediated by SIX6 Defines Retinal Ganglion Cell Pathogenesis in Glaucoma.

Glaucoma, a blinding neurodegenerative disease, whose risk factors include elevated intraocular pressure (IOP), age, and genetics, is characterized by accelerated and progressive retinal ganglion cell (RGC) death. Despite decades of research, the mechanism of RGC death in glaucoma is still unknown. Here, we demonstrate that the genetic effect of the SIX6 risk variant (rs33912345, His141Asn) is enhanced by another major POAG risk gene, p16INK4a (cyclin-dependent kinase inhibitor 2A, isoform INK4a). We further show that the upregulation of homozygous SIX6 risk alleles (CC) leads to an increase in p16INK4a expression, with subsequent cellular senescence, as evidenced in a mouse model of elevated IOP and in human POAG eyes. Our data indicate that SIX6 and/or IOP promotes POAG by directly increasing p16INK4a expression, leading to RGC senescence in adult human retinas. Our study provides important insights linking genetic susceptibility to the underlying mechanism of RGC death and provides a unified theory of glaucoma pathogenesis.

Multilevel synergically controlling wavefront correction of a high-power slab laser system.

We present a multilevel synergically controlling wavefront correction method that can apply in a slab laser system. To fully utilize the response frequency and the stroke of actuators of the single deformable mirror (DM), we design a set of multilevel wavefront correction devices to reduce the root-mean square of wavefront aberration before the DM. As the wavefront of slab geometry solid-state lasers mainly consists of fourth and longitudinally distributed aberration, such as 5th, 9th, and 14th orders of Legendre polynomials. We design a precompensating level of the aberration with a slow-drift mirror, fast-steer mirror, one-dimensional adjustable slab-aberration compensator, and beam-shaping system to reduce these orders of wavefront aberration with low spatial resolution and large stroke. As the controlling bandwidth of different devices is diverse, the coupling oscillation between the precompensating level and adaptive optics (AO) level occurs, then we develop the multilevel synergically control to address the coupling. With the precompensating level, the experimental result shows the residual wavefront aberration of the slab laser is compensated well by the AO level effectively within the compensating capability. We clean up a 9.8 kW slab laser system with the beam quality ß of far-field focus spots improved from 17.71 to 2.24 times the diffraction limit.

An automatic and accurate deep learning-based neuroimaging pipeline for the neonatal brain.

BACKGROUND: Accurate segmentation of neonatal brain tissues and structures is crucial for studying normal development and diagnosing early neurodevelopmental disorders. However, there is a lack of an end-to-end pipeline for automated segmentation and imaging analysis of the normal and abnormal neonatal brain. OBJECTIVE: To develop and validate a deep learning-based pipeline for neonatal brain segmentation and analysis of structural magnetic resonance images (MRI). MATERIALS AND METHODS: Two cohorts were enrolled in the study, including cohort 1 (582 neonates from the developing Human Connectome Project) and cohort 2 (37 neonates imaged using a 3.0-tesla MRI scanner in our hospital).We developed a deep leaning-based architecture capable of brain segmentation into 9 tissues and 87 structures. Then, extensive validations were performed for accuracy, effectiveness, robustness and generality of the pipeline. Furthermore, regional volume and cortical surface estimation were measured through in-house bash script implemented in FSL (Oxford Centre for Functional MRI of the Brain Software Library) to ensure reliability of the pipeline. Dice similarity score (DSC), the 95th percentile Hausdorff distance (H95) and intraclass correlation coefficient (ICC) were calculated to assess the quality of our pipeline. Finally, we finetuned and validated our pipeline on 2-dimensional thick-slice MRI in cohorts 1 and 2. RESULTS: The deep learning-based model showed excellent performance for neonatal brain tissue and structural segmentation, with the best DSC and the 95th percentile Hausdorff distance (H95) of 0.96 and 0.99 mm, respectively. In terms of regional volume and cortical surface analysis, our model showed good agreement with ground truth. The ICC values for the regional volume were all above 0.80. Considering the thick-slice image pipeline, the same trend was observed for brain segmentation and analysis. The best DSC and H95 were 0.92 and 3.00 mm, respectively. The regional volumes and surface curvature had ICC values just below 0.80. CONCLUSIONS: We propose an automatic, accurate, stable and reliable pipeline for neonatal brain segmentation and analysis from thin and thick structural MRI. The external validation showed very good reproducibility of the pipeline.

Bacterial Cytochrome P450 Catalyzed Post-translational Macrocyclization of Ribosomal Peptides.

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a fascinating group of natural products that exhibit diverse structural features and bioactivities. P450-catalyzed RiPPs stand out as a unique but underexplored family. Herein, we introduce a rule-based genome mining strategy that harnesses the intrinsic biosynthetic principles of RiPPs, including the co-occurrence and co-conservation of precursors and P450s and interactions between them, successfully facilitating the identification of diverse P450-catalyzed RiPPs. Intensive BGC characterization revealed four new P450s, KstB, ScnB, MciB, and SgrB, that can catalyze the formation of Trp-Trp-Tyr (one C-C and two C-N bonds), Tyr-Trp (C-C bond), Trp-Trp (C-N bond), and His-His (ether bond) crosslinks, respectively, within three or four residues. KstB, ScnB, and MciB could accept non-native precursors, suggesting they could be promising starting templates for bioengineering to construct macrocycles. Our study highlights the potential of P450s to expand the chemical diversity of strained macrocyclic peptides and the range of biocatalytic tools available for peptide macrocyclization.

Three-dimensional reduced field-of-view imaging (3D-rFOVI).

PURPOSE: This study aimed at developing a 3D reduced field-of-view imaging (3D-rFOVI) technique using a 2D radiofrequency (RF) pulse, and demonstrating its ability to achieve isotropic high spatial resolution and reduced image distortion in echo planar imaging (EPI). METHODS: The proposed 3D-rFOVI technique takes advantage of a 2D RF pulse to excite a slab along the conventional slice-selection direction (i.e., z-direction) while limiting the spatial extent along the phase-encoded direction (i.e., y-direction) within the slab. The slab is phase-encoded in both through-slab and in-slab phase-encoded directions. The 3D-rFOVI technique was implemented at 3T in gradient-echo and spin-echo EPI pulse sequences for functional MRI (fMRI) and diffusion-weighted imaging (DWI), respectively. 3D-rFOVI experiments were performed on a phantom and human brain to illustrate image distortion reduction, as well as isotropic high spatial resolution, in comparison with 3D full-FOV imaging. RESULTS: In both the phantom and the human brain, image voxel dislocation was substantially reduced by 3D-rFOVI when compared with full-FOV imaging. In the fMRI experiment with visual stimulation, 3D isotropic spatial resolution of (2 × 2 × 2 mm3 ) was achieved with an adequate signal-to-noise ratio (81.5) and blood oxygen level-dependent (BOLD) contrast (2.5%). In the DWI experiment, diffusion-weighted brain images with an isotropic resolution of (1 × 1 × 1 mm3 ) was obtained without appreciable image distortion. CONCLUSION: This study indicates that 3D-rFOVI is a viable approach to 3D neuroimaging over a zoomed region.

Gradient-echo-train-based sub-millisecond periodic event encoded dynamic imaging with random (k, t)-space undersampling: k-t get-SPEEDI.

PURPOSE: The gradient-echo-train-based Sub-millisecond Periodic Event Encoded Dynamic Imaging (get-SPEEDI) technique provides ultrahigh temporal resolutions (∼0.6 ms) for detecting rapid physiological activities, but its practical adoption can be hampered by long scan times. This study aimed at developing a more efficient variant of get-SPEEDI for reducing the scan time without degrading temporal resolution or image quality. METHODS: The proposed pulse sequence, named k-t get-SPEEDI, accelerated get-SPEEDI acquisition by undersampling the k-space phase-encoding lines semi-randomly. At each time frame, k-space was fully sampled in the central region whereas randomly undersampled in the outer regions. A time-series of images was reconstructed using an algorithm based on the joint partial separability and sparsity constraints. To demonstrate the performance of k-t get-SPEEDI, images of human aortic valve opening and closing were acquired with 0.6-ms temporal resolution and compared with those from conventional get-SPEEDI. RESULTS: k-t get-SPEEDI achieved a 2-fold scan time reduction over the conventional get-SPEEDI (from ∼6 to ∼3 min), while achieving comparable SNRs and contrast-to-noise ratio (CNRs) for visualizing the dynamic process of aortic valve: SNR/CNR ≈$$ \approx $$ 70/38 vs. 73/39 in the k-t and conventional get-SPEEDI scans, respectively. The time courses of aortic valve area also matched well between these two sequences with a correlation coefficient of 0.86. CONCLUSIONS: The k-t get-SPEEDI pulse sequence was able to half the scan time without compromising the image quality and ultrahigh temporal resolution. Additional scan time reduction may also be possible, facilitating in vivo adoptions of SPEEDI techniques.

In-plane simultaneous multisegment imaging using a 2D RF pulse.

PURPOSE: To develop an in-plane simultaneous multisegment (IP-SMS) imaging technique using a 2D-RF pulse and to demonstrate its ability to achieve high spatial resolution in EPI while reducing image distortion. METHODS: The proposed IP-SMS technique takes advantage of periodic replicates of the excitation profile of a 2D-RF pulse to simultaneously excite multiple segments within a slice. These segments were acquired over a reduced FOV and separated using a joint GRAPPA reconstruction by leveraging virtual coils that combined the physical coil sensitivity and 2D-RF pulse spatial response. Two excitations were used with complementary spatial response profiles to adequately cover a full FOV, producing a full-FOV image that had the benefits of reduced FOV with high spatial resolution and reduced distortion. The IP-SMS technique was implemented in a diffusion-weighted single-shot EPI sequence. Experimental demonstrations were performed on a phantom and healthy human brain. RESULTS: In the phantom experiment, IP-SMS enabled a four-fold acceleration using an eight-channel coil without causing residual aliasing artifacts. In the human brain experiment, diffusion-weighted images with high in-plane resolution (1 × 1 mm2 ) and substantially reduced image distortion were obtained in all imaging planes in comparison with a commercial diffusion-weighted EPI sequence. The capability of IP-SMS for contiguous whole-brain coverage was also demonstrated. CONCLUSION: The proposed IP-SMS technique can realize the benefits of reduced-FOV imaging while achieving a full-FOV coverage with good image quality and time efficiency.

Elastic Valley Spin Controlled Chiral Coupling in Topological Valley Phononic Crystals.

Distinct from the phononic valley pseudospin, the real physical spin of elastic waves adds a novel tool kit capable of envisaging the valley-spin physics of topological valley phononic crystals from a local viewpoint. Here, we report the observation of local elastic valley spin as well as the hidden elastic spin-valley locking mechanism overlooked before. We demonstrate that the selective one-way routing of valley phonon states along the topological interface can be reversed by imposing the elastic spin metasource at different interface locations with opposite valley-spin correspondence. We unveil the physical mechanism of selective directionality as the elastic spin controlled chiral coupling of valley phonon states, through both analytical theory and experimental measurement of the opposite local elastic spin density at different interface locations for different transport directions. The elastic spin of valley topological edge phonons can be extended to other topological states and offers new tool to explore topological metamaterials.

Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma.

OBJECTIVES: To evaluate the feasibility of high b-value diffusion-weighted imaging (DWI) for distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC) and low- from high-grade bladder urothelial carcinoma using a fractional-order calculus (FROC) model as well as a combination of FROC DWI and bi-parametric Vesical Imaging-Reporting and Data System (VI-RADS). METHODS: Fifty-eight participants with bladder urothelial carcinoma were included in this IRB-approved prospective study. Diffusion-weighted images, acquired with 16 b-values (0-3600 s/mm2), were analyzed using the FROC model. Three FROC parameters, D, ß, and µ, were used for delineating NMIBC from MIBC and for tumor grading. A receiver operating characteristic (ROC) analysis was performed based on the individual FROC parameters and their combinations, followed by comparisons with apparent diffusion coefficient (ADC) and bi-parametric VI-RADS based on T2-weighted images and DWI. RESULTS: D and µ were significantly lower in the MIBC group than in the NMIBC group (p = 0.001 for each), and D, ß, and µ all exhibited significantly lower values in the high- than in the low-grade tumors (p ≤ 0.011). The combination of D, ß, and µ produced the highest specificity (85%), accuracy (78%), and the area under the ROC curve (AUC, 0.782) for distinguishing NMIBC and MIBC, and the best sensitivity (89%), specificity (86%), accuracy (88%), and AUC (0.892) for tumor grading, all of which outperformed the ADC. The combination of FROC parameters with bi-parametric VI-RADS improved the AUC from 0.859 to 0.931. CONCLUSIONS: High b-value DWI with a FROC model is useful in distinguishing NMIBC from MIBC and grading bladder tumors. KEY POINTS: • Diffusion parameters derived from a FROC diffusion model may differentiate NMIBC from MIBC and low- from high-grade bladder urothelial carcinomas. • Under the condition of a moderate sample size, higher AUCs were achieved by the FROC parameters D (0.842) and µ (0.857) than ADC (0.804) for bladder tumor grading with p ≤ 0.046. • The combination of the three diffusion parameters from the FROC model can improve the specificity over ADC (85% versus 67%, p = 0.031) for distinguishing NMIBC and MIBC and enhance the performance of bi-parametric VI-RADS.

Combining quantitative susceptibility mapping to radiomics in diagnosing Parkinson's disease and assessing cognitive impairment.

OBJECTIVE: To explore whether magnetic susceptibility value (MSV) and radiomics features of the nigrostriatal system could be used as imaging markers for diagnosing Parkinson's disease (PD) and its related cognitive impairment (CI). METHODS: A total of 104 PD patients and 45 age-sex-matched healthy controls (HCs) underwent quantitative susceptibility mapping (QSM). The former completed Hoehn-Yahr Stage and Montreal Cognitive Assessment (MoCA). The patients were divided into several subgroups according to disease stages, courses, and MoCA scores. The ROI was subdivided into the substantia nigra (SN), head of caudate nucleus (HCN), and putamen. The MSVs and radiomics features were obtained from QSM. The multivariable logistic regression (MLR) and support vector machine (SVM) models were constructed to diagnose PD. The correlations between MSVs, radiomics features, and MoCA scores were evaluated. RESULTS: The MSVs in bilateral SN pars compacta (SNc) of PD patients were higher than those of the HCs (p < 0.001). There were differences in some radiomics features between the two groups (p < 0.05). The MSVs of the right SNc and the radiomics features of the right SN had the highest area under the curve (AUC), respectively. The comprehensive MLR model (0.90) and SVM model (0.95) revealed better classification performance than MSVs (p < 0.05) in diagnosing PD. The MSVs from the HCN were negatively correlated with MoCA scores in PD subgroups. There were correlations between radiomics features and MoCA scores in PD patients. CONCLUSIONS: Radiomics features and MSVs of the nigrostriatal system from QSM could have crucial role in diagnosing PD and assessing CI. KEY POINTS: • The MLR and the SVM models have excellent diagnostic performance in the diagnosis of PD. • A PD diagnostic nomogram, created based on MSV and the radiomics scores of SVM model, is very convenient for clinical use. • The radiomics features of the nigrostriatal system based on QSM help to evaluate the cognitive impairment in PD patients.

Lens regeneration using endogenous stem cells with gain of visual function.

The repair and regeneration of tissues using endogenous stem cells represents an ultimate goal in regenerative medicine. To our knowledge, human lens regeneration has not yet been demonstrated. Currently, the only treatment for cataracts, the leading cause of blindness worldwide, is to extract the cataractous lens and implant an artificial intraocular lens. However, this procedure poses notable risks of complications. Here we isolate lens epithelial stem/progenitor cells (LECs) in mammals and show that Pax6 and Bmi1 are required for LEC renewal. We design a surgical method of cataract removal that preserves endogenous LECs and achieves functional lens regeneration in rabbits and macaques, as well as in human infants with cataracts. Our method differs conceptually from current practice, as it preserves endogenous LECs and their natural environment maximally, and regenerates lenses with visual function. Our approach demonstrates a novel treatment strategy for cataracts and provides a new paradigm for tissue regeneration using endogenous stem cells.

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations.

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.