Improving diagnosis and outcome prediction of gastric cancer via multimodal learning using whole slide pathological images and gene expression.

For the diagnosis and outcome prediction of gastric cancer (GC), machine learning methods based on whole slide pathological images (WSIs) have shown promising performance and reduced the cost of manual analysis. Nevertheless, accurate prediction of GC outcome may rely on multiple modalities with complementary information, particularly gene expression data. Thus, there is a need to develop multimodal learning methods to enhance prediction performance. In this paper, we collect a dataset from Ruijin Hospital and propose a multimodal learning method for GC diagnosis and outcome prediction, called GaCaMML, which is featured by a cross-modal attention mechanism and Per-Slide training scheme. Additionally, we perform feature attribution analysis via integrated gradient (IG) to identify important input features. The proposed method improves prediction accuracy over the single-modal learning method on three tasks, i.e., survival prediction (by 4.9% on C-index), pathological stage classification (by 11.6% on accuracy), and lymph node classification (by 12.0% on accuracy). Especially, the Per-Slide strategy addresses the issue of a high WSI-to-patient ratio and leads to much better results compared with the Per-Person training scheme. For the interpretable analysis, we find that although WSIs dominate the prediction for most samples, there is still a substantial portion of samples whose prediction highly relies on gene expression information. This study demonstrates the great potential of multimodal learning in GC-related prediction tasks and investigates the contribution of WSIs and gene expression, respectively, which not only shows how the model makes a decision but also provides insights into the association between macroscopic pathological phenotypes and microscopic molecular features.

Artificial intelligence-based assessment of PD-L1 expression in diffuse large B cell lymphoma.

Diffuse large B cell lymphoma (DLBCL) is an aggressive blood cancer known for its rapid progression and high incidence. The growing use of immunohistochemistry (IHC) has significantly contributed to the detailed cell characterization, thereby playing a crucial role in guiding treatment strategies for DLBCL. In this study, we developed an AI-based image analysis approach for assessing PD-L1 expression in DLBCL patients. PD-L1 expression represents as a major biomarker for screening patients who can benefit from targeted immunotherapy interventions. In particular, we performed large-scale cell annotations in IHC slides, encompassing over 5101 tissue regions and 146,439 live cells. Extensive experiments in primary and validation cohorts demonstrated the defined quantitative rule helped overcome the difficulty of identifying specific cell types. In assessing data obtained from fine needle biopsies, experiments revealed that there was a higher level of agreement in the quantitative results between Artificial Intelligence (AI) algorithms and pathologists, as well as among pathologists themselves, in comparison to the data obtained from surgical specimens. We highlight that the AI-enabled analytics enhance the objectivity and interpretability of PD-L1 quantification to improve the targeted immunotherapy development in DLBCL patients.

Cascaded plastic optical fiber based SPR sensor for simultaneous measurement of refractive index and temperature.

A cascaded side-polish plastic optical fiber (POF) and FONTEX optical fiber based surface plasmon resonance (SPR) sensor is proposed for simultaneous measurement of refractive index (RI) and temperature. The side-polish POF and FONTEX optical fiber are connected by using the UV glue in a Teflon plastic tube. The SPR phenomenon can be excited at both of the side-polish region and the FONTEX fiber cladding. The polydimethylsiloxane (PDMS) is coated on the side-polish POF to get a temperature sensing channel. Due to the low RI sensitivity of the FONTEX optical fiber, the cascaded fiber sensor can obtain a broader RI measurement range with a low crosstalk. An RI sensitivity of 700 nm/RIU in the RI measurement range of 1.335-1.39 and a temperature sensitivity of -1.02 nm/°C measured in deionized water with a range of 20-60 °C are obtained. In addition, the cascaded POF based SPR sensor has potential application prospects in the field of biochemical sensing.

The genetic landscape of histologically transformed marginal zone lymphomas.

BACKGROUND: Marginal zone lymphomas (MZLs) comprise a diverse group of indolent lymphoproliferative disorders; however, some patients develop histologic transformation (HT) with rapid progression to aggressive lymphoma. METHODS: Forty-three MZLs with HT (HT-MZLs), 535 MZLs, and 174 de novo diffuse large B-cell lymphomas (DLBCLs) without rearrangements of MYC, BCL2, and BCL6 were collected. Among these, 22 HT-MZLs, 39 MZLs, and 174 DLBCLs were subjected to 148-gene targeted exome sequencing. The clinicopathologic features of patients who had HT-MZL and their genetic alterations were compared with those of patients who had MZLs and DLBCLs. RESULTS: All 43 HT-MZLs corresponded to DLBCLs. No HT-MZLs harbored BCL2 and MYC and/or BCL6 rearrangements. Bone marrow involvement and higher levels of lactate dehydrogenase were significantly more common in HT-MZLs than in MZLs. Furthermore, upregulated BCL6, MUM1, C-MYC, and Ki-67 expression was observed more frequently in HT-MZLs than in MZLs. TBL1XR1 was the most frequently altered gene (63.6%) in HT-MZLs, followed by CCND3 (31.8%), CARD11, ID3, and TP53 (22.7%). A trend toward worse progression-free survival in patients with TBL1XR1 mutations was observed. Compared with MZLs and non-germinal center B-cell (GCB) type DLBCLs, significantly higher frequencies of TBL1XR1 and ID3 mutations were identified in HT-MZLs. PIM1 mutations frequently occurred in DLBCLs and were significantly associated with TBL1XR1 mutations but were mutated less in HT-MZLs that had TBL1XR1 mutations. CONCLUSIONS: The current findings reveal the clinicopathologic and genetic features of HT-MZLs, suggesting that these tumors might constitute a group distinct from MZL and de novo non-GCB type DLBCL. TBL1XR1 mutations may be considered a predictor of HT in MZL.

Relay learning: a physically secure framework for clinical multi-site deep learning.

Big data serves as the cornerstone for constructing real-world deep learning systems across various domains. In medicine and healthcare, a single clinical site lacks sufficient data, thus necessitating the involvement of multiple sites. Unfortunately, concerns regarding data security and privacy hinder the sharing and reuse of data across sites. Existing approaches to multi-site clinical learning heavily depend on the security of the network firewall and system implementation. To address this issue, we propose Relay Learning, a secure deep-learning framework that physically isolates clinical data from external intruders while still leveraging the benefits of multi-site big data. We demonstrate the efficacy of Relay Learning in three medical tasks of different diseases and anatomical structures, including structure segmentation of retina fundus, mediastinum tumors diagnosis, and brain midline localization. We evaluate Relay Learning by comparing its performance to alternative solutions through multi-site validation and external validation. Incorporating a total of 41,038 medical images from 21 medical hosts, including 7 external hosts, with non-uniform distributions, we observe significant performance improvements with Relay Learning across all three tasks. Specifically, it achieves an average performance increase of 44.4%, 24.2%, and 36.7% for retinal fundus segmentation, mediastinum tumor diagnosis, and brain midline localization, respectively. Remarkably, Relay Learning even outperforms central learning on external test sets. In the meanwhile, Relay Learning keeps data sovereignty locally without cross-site network connections. We anticipate that Relay Learning will revolutionize clinical multi-site collaboration and reshape the landscape of healthcare in the future.

Semi-embedded slot waveguide electro-optic modulator.

Electro-optic modulators are essential devices on silicon photonic chips in modern optical communication networks. This paper presents a compact, low-loss electro-optic modulator. The modulation efficiency is greatly improved by embedding the lower half of the slot waveguide into the buried oxide layer and inserting graphene at the junction. The interaction of graphene with an optical field in a waveguide is studied using the finite element method. The functions of phase modulation and absorption modulation are realized by changing the gate voltage to change the chemical potential of graphene. The semi-embedded slot waveguide optical modulator has a length of 50 µm. After simulation verification, it can be used as an electro-absorption modulator and can achieve a modulation depth of 26.38 dB and an insertion loss of 0.60 dB. When used as an electro-refractive modulator, it can be realized with a linear change of phase from zero to π; the total insertion loss is only 0.59 dB. The modulator has a modulation bandwidth of 79.6 GHz, and the energy consumption as electro-absorption and electro-refraction modulation are 0.51 and 1.92 pj/bit, respectively. Compared with common electro-optic modulators, the electro-optic modulator designed in this paper has a higher modulation effect and also takes into account the advantages of low insertion loss and low energy consumption. This research is helpful for the design of higher-performance optical communication network devices.

SPP excitation and coupling mechanism based on micro/nano fibers.

A hot trend in the development of optoelectronic devices is how to use the principle of surface plasmon resonance to enhance the performance of integrated photonics devices and achieve miniaturization. This paper proposes an accompanying waveguide coupling structure of micro/nano fibers, which consists of two parallel-placed micro/nano fibers (MNFs) coated with a silver film in the waist region and infused with a refractive index matching oil. In the overlapping region, there exists a segment of surface plasmon polaritons (SPPs) coupling area. The excitation and coupling characteristics of SPPs are studied through numerical simulation. Optimal coupling enhancement configuration is obtained by studying variables such as spacing distance, coupling length, and metal film thickness. A comparison is made with the SPP intensity of a single MNF, showing a 220% increase in electric field intensity, demonstrating its excellent coupling effect. By using this coupling structure, exploration of SPPs excitation and coupling mechanisms is enhanced, and structures resembling interferometric devices can be designed, providing new insights for high-performance miniaturized devices.

Hollow-core pear-shaped conjoined-tube fiber with low loss in the ultraviolet band.

PCTF (pear-shaped conjoined-tube fiber) is presented as a new ultraviolet (UV) guiding fiber with low loss. Results indicate that two PCTFs have better properties than that of previous studies in the UV band. The total loss of two PCTFs is less than 1 dB/km, and its bandwidth exceeds 150 nm between 0.2 and 0.4 µm. Furthermore, PCTF's single-mode performance is very promising, as evidenced by the higher-order mode extinction ratio (HOMER) over 103. The fabrication tolerance is discussed in this paper and results show that the tolerance is good enough to fabricate by normal fiber drawing process. This fiber is promising in applications for nonlinear optics, ultrafast optics, high power laser, and quantum optics.

Multidimensional tunable graphene chiral metasurface based on coherent control.

The deep application of chiral metasurfaces requires higher flexibility. Herein, we propose a multidimensional tunable chiral graphene metasurface, which uses coherent control to obtain more than 0.8 circular conversion dichroism (CCD) at 2.4 THz as a transmission structure. Its operating frequency can be changed in the 1.3-2.4 THz range, while the amplitude has almost perfect modulation depth in the range of 0-0.8. The mechanism of differential absorption was analyzed through numerical simulation. The device designed is easy to obtain reverse CCD, which is used for unit layout and proves its advantages in near-field imaging. Our work has broadened the path for the development of chiral metasurfaces towards higher degrees of freedom.

Ultra-compact on-chip meta-waveguide phase modulator based on split ring magnetic resonance.

With the development of photonic integration technology, meta-waveguides have become a new research hotspot. They have broken through the theoretical diffraction limit by virtue of the strong electromagnetic manipulation ability of the metasurface and the strong electromagnetic field limitation and guidance ability of the waveguide. However, the reported meta-waveguides lack research on dynamic modulation. Therefore, we analyze the modulation effect of the metasurface on the optical field in the waveguide and design an ultra-compact on-chip meta-waveguide phase modulator using split ring magnetic resonance. It has a very short modulation length of only 3.65 µm, wide modulation bandwidth of 116.8 GHz, and low energy consumption of 263.49 fJ/bit. By optimizing the structure, the energy consumption can be further reduced to 90.69 fJ/bit. Meta-waveguides provide a promising method for the design of integrated photonic devices.

Nested micro-ring refractive index sensor based on a subwavelength grating waveguide and the Vernier effect.

In this paper, a nested micro-ring refractive index sensor based on a subwavelength grating waveguide and the Vernier effect is proposed. In this scheme, the nested micro-ring structure is combined with a subwavelength grating structure to enhance the contact area between the optical field and the analyte, and the wavelength offset is doubled through the Vernier effect. The proposed sensor can effectively increase sensing sensitivity, taking into account the improvement of the free spectral range. This structure enables the device to reach a sensitivity of 8030 nm/RIU near 1550 nm wavelength in a deionized water environment, with a detection limit of 5.659×10-5 RIU and free spectral range of 41.956 nm. The device suggested in this study has a greater reduced footprint than the conventional micro-ring resonant sensor, measuring just 35µm×25µm. Due to its high integration, high sensitivity, and large free spectral range compared to conventional micro-ring resonant sensors, such structures are of great value in biosensing and environmental monitoring.

Bright light treatment counteracts stress-induced sleep alterations in mice, via a visual circuit related to the rostromedial tegmental nucleus.

Light in the environment greatly impacts a variety of brain functions, including sleep. Clinical evidence suggests that bright light treatment has a beneficial effect on stress-related diseases. Although stress can alter sleep patterns, the effect of bright light treatment on stress-induced sleep alterations and the underlying mechanism are poorly understood. Here, we show that bright light treatment reduces the increase in nonrapid eye movement (NREM) sleep induced by chronic stress through a di-synaptic visual circuit consisting of the thalamic ventral lateral geniculate nucleus and intergeniculate leaflet (vLGN/IGL), lateral habenula (LHb), and rostromedial tegmental nucleus (RMTg). Specifically, chronic stress causes a marked increase in NREM sleep duration and a complementary decrease in wakefulness time in mice. Specific activation of RMTg-projecting LHb neurons or activation of RMTg neurons receiving direct LHb inputs mimics the effects of chronic stress on sleep patterns, while inhibition of RMTg-projecting LHb neurons or RMTg neurons receiving direct LHb inputs reduces the NREM sleep-promoting effects of chronic stress. Importantly, we demonstrate that bright light treatment reduces the NREM sleep-promoting effects of chronic stress through the vLGN/IGL-LHb-RMTg pathway. Together, our results provide a circuit mechanism underlying the effects of bright light treatment on sleep alterations induced by chronic stress.

Schwann cells regulate tumor cells and cancer-associated fibroblasts in the pancreatic ductal adenocarcinoma microenvironment.

Neuropathy is a feature more frequently observed in pancreatic ductal adenocarcinoma (PDAC) than other tumors. Schwann cells, the most prevalent cell type in peripheral nerves, migrate toward tumor cells and associate with poor prognosis in PDAC. To unveil the effects of Schwann cells on the neuro-stroma niche, here we perform single-cell RNA-sequencing and microarray-based spatial transcriptome analysis of PDAC tissues. Results suggest that Schwann cells may drive tumor cells and cancer-associated fibroblasts (CAFs) to more malignant subtypes: basal-like and inflammatory CAFs (iCAFs), respectively. Moreover, in vitro and in vivo assays demonstrate that Schwann cells enhance the proliferation and migration of PDAC cells via Midkine signaling and promote the switch of CAFs to iCAFs via interleukin-1α. Culture of tumor cells and CAFs with Schwann cells conditioned medium accelerates PDAC progression. Thus, we reveal that Schwann cells induce malignant subtypes of tumor cells and CAFs in the PDAC milieu.

Terahertz broadband tunable chiral metamirror based on VO2-metal hybrid structure.

Aiming at the problems of narrow working bandwidth, low efficiency, and complex structure of existing terahertz chiral absorption, we propose a chiral metamirror composed of C-shaped metal split ring and L-shaped vanadium dioxide (VO2). This chiral metamirror is composed of three layers of structure, a gold substrate at the bottom, the first polyethylene cyclic olefin copolymer (Topas) dielectric layer and VO2-metal hybrid structure as the top. Our theoretical results led us to show that this chiral metamirror has a circular dichroism (CD) value greater than 0.9 at 5.70 to 8.55 THz and has a maximum value of 0.942 at f = 7.18 THz. In addition, by adjusting the conductivity of VO2, the CD value can be continuously adjustable from 0 to 0.942, which means that the proposed chiral metamirror supports the free switching of the CD response between the on and off states, and the CD modulation depth exceeds 0.99 in the range of 3 to 10 THz. Moreover, we discuss the influence of structural parameters and the change of incident angle on the performance of the metamirror. Finally, we believe that the proposed chiral metamirror has important reference value in the terahertz range for constructing chiral light detectors, CD metamirrors, switchable chiral absorbers and spin-related systems. This work will provide a new idea for improving the terahertz chiral metamirror operating bandwidth and promote the development of terahertz broadband tunable chiral optical devices.

Adjustable strong circular dichroism based on a tricircular arc metasurface.

Circular dichroism has promising applications in biology, molecular chemistry, and other fields. The key to obtaining strong circular dichroism is to introduce symmetry breaking into the structure, which leads to a great difference in the response to different circularly polarized waves. Here, we propose a metasurface structure based on three circular arcs, which produces strong circular dichroism. The metasurface structure combines the split ring with the three circular arcs and increases the structural asymmetry by changing the relative torsional angle. The causes of the strong circular dichroism are analyzed in this paper, and the influence of metasurface parameters on it is discussed. According to the simulation data, the response of the proposed metasurface to different circularly polarized waves varies greatly, with absorption of up to 0.99 at 5.095 THz for a left-handed circularly polarized wave and a maximum circular dichroism of over 0.93. In addition, the incorporation of the phase change material vanadium dioxide on the structure allows flexible modulation of circular dichroism and modulation depths of up to 98.6%. The change of angle within a certain range has little effect on the structural performance. We believe that this flexible and angle robust chiral metasurface structure is suitable for complex reality, and large modulation depth is more practical.

Altered cytokeratin 5 expression in breast lobular myoepithelial cells.

AIMS: Cytokeratin 5 (CK5) is a surrogate maker of progenitor cells and early glandular and myoepithelial cells (MECs) in the breast, and CK5 expression in breast MECs varies from ducts to lobules, and from normal to diseased tissue. However, the mechanisms underlying immunophenotypic alterations of CK5 expression in MECs remain unclear. METHODS: CK5 expression in MECs of 20 normal breast samples, 58 ductal carcinoma in situ (DCIS; including 21 DCIS with extensive lobular involvement), 11 atypical ductal hyperplasia (ADH), 18 non-invasive lobular neoplasia consisting of 11 atypical lobular hyperplasia (ALH) and 7 lobular carcinoma in situ (LCIS), 20 cystic lobules and 10 usual ductal hyperplasia (UDH) involving lobules were observed to evaluate the effects of contact with benign hyperplastic or cancerous luminal cells and pressure of dilated glands on CK5 expression. RESULTS: CK5 expression in normal ductal MECs was exclusively positive, whereas most normal lobular MECs were negative. In DCIS, cancerous ducts were primarily surrounded by CK5-positive MECs (91.0%), as were lobular acini involved by DCIS (89.2%), while the remaining normal acini maintained CK5-negative. CK5-positive MECs were found in 57.5% of acini in ALH and were more prevalent in LCIS (70.7%). CK5 expression was occasionally positive in both cystic lobules (16.7%) and lobules involved by UDH (14.3%), while an increase of CK5-positive MECs was found in ADH (38.2%). CONCLUSIONS: These results suggest that CK5 expression in lobular MECs may be altered by contact with cancerous luminal cells rather than benign hyperplastic luminal cells or pressure from dilated glands.

Deep Double Incomplete Multi-View Multi-Label Learning With Incomplete Labels and Missing Views.

View missing and label missing are two challenging problems in the applications of multi-view multi-label classification scenery. In the past years, many efforts have been made to address the incomplete multi-view learning or incomplete multi-label learning problem. However, few works can simultaneously handle the challenging case with both the incomplete issues. In this article, we propose a new incomplete multi-view multi-label learning network to address this challenging issue. The proposed method is composed of four major parts: view-specific deep feature extraction network, weighted representation fusion module, classification module, and view-specific deep decoder network. By, respectively, integrating the view missing information and label missing information into the weighted fusion module and classification module, the proposed method can effectively reduce the negative influence caused by two such incomplete issues and sufficiently explore the available data and label information to obtain the most discriminative feature extractor and classifier. Furthermore, our method can be trained in both supervised and semi-supervised manners, which has important implications for flexible deployment. Experimental results on five benchmarks in supervised and semi-supervised cases demonstrate that the proposed method can greatly enhance the classification performance on the difficult incomplete multi-view multi-label classification tasks with missing labels and missing views.

Projective Incomplete Multi-View Clustering.

Due to the rapid development of multimedia technology and sensor technology, multi-view clustering (MVC) has become a research hotspot in machine learning, data mining, and other fields and has been developed significantly in the past decades. Compared with single-view clustering, MVC improves clustering performance by exploiting complementary and consistent information among different views. Such methods are all based on the assumption of complete views, which means that all the views of all the samples exist. It limits the application of MVC, because there are always missing views in practical situations. In recent years, many methods have been proposed to solve the incomplete MVC (IMVC) problem and a kind of popular method is based on matrix factorization (MF). However, such methods generally cannot deal with new samples and do not take into account the imbalance of information between different views. To address these two issues, we propose a new IMVC method, in which a novel and simple graph regularized projective consensus representation learning model is formulated for incomplete multi-view data clustering task. Compared with the existing methods, our method not only can obtain a set of projections to handle new samples but also can explore information of multiple views in a balanced way by learning the consensus representation in a unified low-dimensional subspace. In addition, a graph constraint is imposed on the consensus representation to mine the structural information inside the data. Experimental results on four datasets show that our method successfully accomplishes the IMVC task and obtain the best clustering performance most of the time. Our implementation is available at https://github.com/Dshijie/PIMVC.

Retinol dehydrogenase 10 reduction mediated retinol metabolism disorder promotes diabetic cardiomyopathy in male mice.

Diabetic cardiomyopathy is a primary myocardial injury induced by diabetes with complex pathogenesis. In this study, we identify disordered cardiac retinol metabolism in type 2 diabetic male mice and patients characterized by retinol overload, all-trans retinoic acid deficiency. By supplementing type 2 diabetic male mice with retinol or all-trans retinoic acid, we demonstrate that both cardiac retinol overload and all-trans retinoic acid deficiency promote diabetic cardiomyopathy. Mechanistically, by constructing cardiomyocyte-specific conditional retinol dehydrogenase 10-knockout male mice and overexpressing retinol dehydrogenase 10 in male type 2 diabetic mice via adeno-associated virus, we verify that the reduction in cardiac retinol dehydrogenase 10 is the initiating factor for cardiac retinol metabolism disorder and results in diabetic cardiomyopathy through lipotoxicity and ferroptosis. Therefore, we suggest that the reduction of cardiac retinol dehydrogenase 10 and its mediated disorder of cardiac retinol metabolism is a new mechanism underlying diabetic cardiomyopathy.

Actively tunable linear and circular dichroic metamirrors based on single-layer graphene.

Aiming at the problems of low efficiency, single function and complex structure of the existing dichroic metamirrors, the actively tunable linear and circular dichroic metamirrors based on single-layer graphene are proposed in this study. The designed metamirrors are mainly composed of the ion-gel, patterned graphene, polyimide, polysilicon and gold substrates. The anisotropy of the achiral structures can be used to realize circular dichroism (0.8) and linear dichroism (0.9) in two directions at the same time without functional switching. Additionally, the incidence angle of electromagnetic waves, rather than the structural chirality, is used to create the exceptionally strong dichroism. The proposed metamirrors not only increase the integration, but also reduce the angular dispersion and complexity of the structure. What's more, by changing the Fermi level of graphene, the CD function of the metamirrors can be tuned in the range of 0 - 0.8, and the LD function can be tuned in the range of 0.22 - 0.9. The designed metamirrors can achieve dual functions under a wide range of incident angles, and can be widely used in various fields such as terahertz imaging, biological detection, optical sensing, and spectrometry.