What a Whole Slide Image Can Tell? Subtype-guided Masked Transformer for Pathological Image Captioning

Pathological captioning of Whole Slide Images (WSIs), though is essential in computer-aided pathological diagnosis, has rarely been studied due to the limitations in datasets and model training efficacy. In this paper, we propose a new paradigm Subtype-guided Masked Transformer (SGMT) for pathological captioning based on Transformers, which treats a WSI as a sequence of sparse patches and generates an overall caption sentence from the sequence. An accompanying subtype prediction is introduced into SGMT to guide the training process and enhance the captioning accuracy. We also present an Asymmetric Masked Mechansim approach to tackle the large size constraint of pathological image captioning, where the numbers of sequencing patches in SGMT are sampled differently in the training and inferring phases, respectively. Experiments on the PatchGastricADC22 dataset demonstrate that our approach effectively adapts to the task with a transformer-based model and achieves superior performance than traditional RNN-based methods. Our codes are to be made available for further research and development

Truncated Total Least Squares Method with a Practical Truncation Parameter Choice Scheme for Bioluminescence Tomography Inverse Problem

In bioluminescence tomography (BLT), reconstruction of internal bioluminescent source distribution from the surface optical signals is an ill-posed inverse problem. In real BLT experiment, apart from the measurement noise, the system errors caused by geometry mismatch, numerical discretization, and optical modeling approximations are also inevitable, which may lead to large errors in the reconstruction results. Most regularization techniques such as Tikhonov method only consider measurement noise, whereas the influences of system errors have not been investigated. In this paper, the truncated total least squares method (TTLS) is introduced into BLT reconstruction, in which both system errors and measurement noise are taken into account. Based on the modified generalized cross validation (MGCV) criterion and residual error minimization, a practical parameter-choice scheme referred to as improved GCV (IGCV) is proposed for TTLS. Numerical simulations with different noise levels and physical experiments demonstrate the effectiveness and potential of TTLS combined with IGCV for solving the BLT inverse problem

Comparing Single vs. Combined Cerebrospinal Fluid Parameters for Diagnosing Full-Term Neonatal Bacterial Meningitis

Objectives: To identify and compare the cerebrospinal fluid (CSF) parameters that predict the presence of neonatal bacterial meningitis using optimal cutoff values, and to derive and compare predictive profiles based on a combination of individual parameters for the same purpose.Study Design: The retrospective component of the Shanghai Neonate Meningitis Cohort included all term neonates who underwent lumbar puncture between 2000 and 2017. Those with severe neurological diseases, histories of ventricular drainage, or traumatic lumbar punctures were excluded. Reference ranges were determined for non-bacterial meningitis neonates based on the 5th, 25th, 50th, 75th, and 95th CSF parameter quantiles, and their relationships with age were calculated using generalized additive models that tested for linear relationships. The optimal cutoff value for each measured CSF parameter was calculated using receiver operating characteristic analysis and by deriving the Youden's index. Parameters with good diagnostic efficacies were combined to produce predictive profiles using logistic regression. The diagnostic efficacies of the single parameters and profiles were compared in neonates with confirmed bacterial meningitis.Results: White blood cells (WBCs) in CSF showed a higher diagnostic ability for neonatal bacterial meningitis than CSF protein, glucose, lactate dehydrogenase, or chloride. The sensitivity and specificity of the diagnostic cutoff value for WBCs (20 × 106/L) were 95.1 and 98.7%, respectively. Profiles based on CSF parameter combinations improved the specificities slightly to 99.0–99.7%. However, employing predictive profiles did not improve sensitivities, which remained at 95.1–96.0%.Conclusions: Profiles for predicting neonatal bacterial meningitis improve the sensitivity and specificity of diagnosis slightly, although not appreciably, compared to the single parameter of CSF WBC alone

Etiology and Clinical Features of Full-Term Neonatal Bacterial Meningitis: A Multicenter Retrospective Cohort Study

Objective: Neonatal bacterial meningitis is a severe infectious disease with a high risk of neurodevelopmental sequelae. The causative pathogens may be related to specific clinical features of the disease. Therefore, this study aimed at determining the pathogen-specific and clinical features of bacterial meningitis in full-term neonates.Methods: We enrolled neonates from the Shanghai Neonate Meningitis Cohort (2005–2017), which is a multicenter retrospective cohort that recruits almost all full-term neonates in Shanghai who underwent lumbar puncture. Patient history and clinical examination results were extracted from the computer-documented information systems of four hospitals. The trends of pathogen distribution were analyzed and differences in the clinical manifestations, treatment, and clinical outcomes at discharge were compared according to the causative pathogen. Logistic regression was used to evaluate the pathogen-specific risk of neurological complications.Results: In total, 518 cases of neonatal meningitis, including 189 proven cases, were included. Group B Streptococcus (GBS) and Escherichia coli (E. coli) were the leading pathogens in proven cases of early-onset and late-onset neonatal meningitis, respectively. The proportion of early-onset and late-onset GBS and late-onset E. coli meningitis cases increased gradually. GBS meningitis had the highest risk of neurological complications, whereas the overall incidence of hydrocephalus and brain abscess in E. coli was higher than that in GBS.Conclusions: Rates of neonatal GBS and E. coli meningitis were high in 2005–2017 in Shanghai, and the risk of neurological complications was also high. Therefore, active prevention, rational use of antibiotics, and continuous monitoring of GBS and E. coli in neonates should be initiated in Shanghai

CAMKs support development of acute myeloid leukemia.

BACKGROUND: We recently identified the human leukocyte immunoglobulin-like receptor B2 (LILRB2) and its mouse ortholog-paired Ig-like receptor (PirB) as receptors for several angiopoietin-like proteins (Angptls). We also demonstrated that PirB is important for the development of acute myeloid leukemia (AML), but exactly how an inhibitory receptor such as PirB can support cancer development is intriguing. RESULTS: Here, we showed that the activation of Ca (2+)/calmodulin-dependent protein kinases (CAMKs) is coupled with PirB signaling in AML cells. High expression of CAMKs is associated with a poor overall survival probability in patients with AML. Knockdown of CAMKI or CAMKIV decreased human acute leukemia development in vitro and in vivo. Mouse AML cells that are defective in PirB signaling had decreased activation of CAMKs, and the forced expression of CAMK partially rescued the PirB-defective phenotype in the MLL-AF9 AML mouse model. The inhibition of CAMK kinase activity or deletion of CAMKIV significantly slowed AML development and decreased the AML stem cell activity. We also found that CAMKIV acts through the phosphorylation of one of its well-known target (CREB) in AML cells. CONCLUSION: CAMKs are essential for the growth of human and mouse AML. The inhibition of CAMK signaling may become an effective strategy for treating leukemia

Risk of malignancy following exposure to Epstein-Barr Virus associated infectious mononucleosis: A nationwide population-based cohort study

PurposeEpstein-Barr virus (EBV) infection has been shown to contribute to oncogenesis and often causes acute clinical manifestation of Infectious mononucleosis (IM). It is unknown whether IM could increase the risk of subsequent malignancies. We aimed to evaluate the association of IM caused by EBV (EBV-IM) with overall and subtypes of malignancy in a large population-based cohort study.MethodsThis study included 1,419,407 individuals born in Denmark between 1973 and 2016 identified from national registers and 23,057 individuals had IM. The 5,394 of them had confirmed EBV-IM and they were birth date- and sex- matched (1:63) to 1,396,350 non-IM individuals. Cox regression was used to examine the associations of EBV-IM with malignancy.ResultsIndividuals with a history of confirmed EBV-IM had an 88% increased overall risk of malignancy (hazard ratio [HR]:1·88, 95% confidence interval [CI]: 1·42–2·49) and a five-fold risk of hematologic malignancies (HR 5·04, 95% CI: 3·07–8·25), compared to those without IM. Similar estimates were observed in the sibling analysis. The overall risk of malignancy was greater for EBV-IM with complications (HR 8·93, 95% CI: 3·35–23·81) than that for EBV-IM without complications (HR 1·35, 95% CI: 1·20–1·53). EBV-IM duration was related to increased risk of malignancy in a dose-response way. Notably, the significant elevated risk of overall malignancy was observed in the first two years after EBV-IM onset (rate ratio [RR] 4·44, 95% CI: 2·75–7·17) and attenuated thereafter.ConclusionEBV-IM was associated with an increased risk in malignancy, particularly hematologic malignancies and in the first two years following IM exposure. Our findings suggest an important time-window for early screening of the EBV-attributed malignancy

The cell motility modulator Slit2 is a potent inhibitor of platelet function.

Vascular injury and atherothrombosis involve vessel infiltration by inflammatory leukocytes, migration of medial vascular smooth muscle cells to the intimal layer, and ultimately acute thrombosis. A strategy to simultaneously target these pathological processes has yet to be identified. The secreted protein, Slit2, and its transmembrane receptor, Robo-1, repel neuronal migration in the developing central nervous system. More recently, it has been appreciated that Slit2 impairs chemotaxis of leukocytes and vascular smooth muscle cells toward diverse inflammatory attractants. The effects of Slit2 on platelet function and thrombus formation have never been explored. We detected Robo-1 expression in human and murine platelets and megakaryocytes and confirmed its presence via immunofluorescence microscopy and flow cytometry. In both static and shear microfluidic assays, Slit2 impaired platelet adhesion and spreading on diverse extracellular matrix substrates by suppressing activation of Akt. Slit2 also prevented platelet activation on exposure to ADP. In in vivo studies, Slit2 prolonged bleeding times in murine tail bleeding assays. Using intravital microscopy, we found that after mesenteric arteriolar and carotid artery injury, Slit2 delayed vessel occlusion time and prevented the stable formation of occlusive arteriolar thrombi. These data demonstrate that Slit2 is a powerful negative regulator of platelet function and thrombus formation. The ability to simultaneously block multiple events in vascular injury may allow Slit2 to effectively prevent and treat thrombotic disorders such as myocardial infarction and stroke

PathNarratives: Data annotation for pathological human-AI collaborative diagnosis

Pathology is the gold standard of clinical diagnosis. Artificial intelligence (AI) in pathology becomes a new trend, but it is still not widely used due to the lack of necessary explanations for pathologists to understand the rationale. Clinic-compliant explanations besides the diagnostic decision of pathological images are essential for AI model training to provide diagnostic suggestions assisting pathologists practice. In this study, we propose a new annotation form, PathNarratives, that includes a hierarchical decision-to-reason data structure, a narrative annotation process, and a multimodal interactive annotation tool. Following PathNarratives, we recruited 8 pathologist annotators to build a colorectal pathological dataset, CR-PathNarratives, containing 174 whole-slide images (WSIs). We further experiment on the dataset with classification and captioning tasks to explore the clinical scenarios of human-AI-collaborative pathological diagnosis. The classification tasks show that fine-grain prediction enhances the overall classification accuracy from 79.56 to 85.26%. In Human-AI collaboration experience, the trust and confidence scores from 8 pathologists raised from 3.88 to 4.63 with providing more details. Results show that the classification and captioning tasks achieve better results with reason labels, provide explainable clues for doctors to understand and make the final decision and thus can support a better experience of human-AI collaboration in pathological diagnosis. In the future, we plan to optimize the tools for the annotation process, and expand the datasets with more WSIs and covering more pathological domains

Core-sheath nanofibers as drug delivery system for thermoresponsive controlled release

In this work, a smart drug delivery system of core–sheath nanofiber is reported. The core-sheath nanofibers were prepared with thermoresponsive poly-(N-isopropylacrylamide) (PNIPAAm) (as core) and hydrophobic ethylcellulose (EC) (as sheath) by coaxial electrospinning. Analogous medicated fibers were prepared by loading with a model drug ketoprofen (KET). The fibers were cylindrical without phase separation and have visible core-sheath structure as shown by scanning and transmission electron microscopy. X-ray diffraction patterns demonstrated the drug with the amorphous physical form was present in the fiber matrix. Fourier transform infrared spectroscopy analysis was conducted, finding that there were significant intermolecular interactions between KET and the polymers. Water contact angle measurements proved that the core-sheath fibers from hydrophobic transformed into hydrophobic when the temperature reached the lower critical solution temperature. In vitro drug-release study of nanofibers with KET displayed that the coaxial nanofibers were able to synergistically combine the characteristics of the two polymers producing a temperature-sensitive drug delivery system with sustained release properties. In addition, they were established to be non-toxic and suitable for cell growth. These findings show that the core–sheath nanofiber is a potential candidate for controlling drug delivery system