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The quality of sleep affects the patient’s health, along with the observation of vital life signs such as body temperature and sweat in sleep, is essential in the monitoring of sleep as well as clinical diagnosis. However, traditional methods in recording physiological change amidst sleep is difficult without being intrusive. The smart pillow is developed to provide a relatively easy way to observe one’s sleep condition, employing temperature and humidity sensors by implanting them inside the pillow in strategic positions. With the patient’s head on the pillow, the roles of sensors are identified as main, auxiliary or environmental temperature, based on the differences of value from three temperature sensors, thus the pattern of sleep can be extracted by statistical analysis, and the body temperature is inferred by a specially designed Fuzzy Logic System if the head-on position is stable for more than 15 min. Night sweat is reported on data from the humidity sensor. Therefore, a cloud-based health-sensing system is built in the smart pillow to collect and analyze data. Experiments from various individuals prove that statistical and inferred results reflect normal and abnormal conditions of sleep accurately. The daily sleeping information of patients from the pillow is helpful in the decision-making of diagnoses and treatment, and users can change their habits of sleep gradually by observing the data with their health professional.

Matrix metalloprotease type 9 (MMP-9) has been functionally implicated in VEGF activation, the induction and maintenance of chronic angiogenesis, and early stage tumor growth in a number of mouse models of cancer. In this article, we have identified two inflammatory cell types that are major sources of MMP-9 in the angiogenic stages of pancreatic islet carcinogenesis that unfold in RIP1-Tag2 transgenic mice. MMP-9-expressing neutrophils were predominantly found inside angiogenic islet dysplasias and tumors, whereas MMP-9-expressing macrophages were localized along the periphery of such lesions. Transient depletion of neutrophils significantly suppressed VEGF:VEGF-receptor association, a signature of MMP-9 activity, and markedly reduced the frequency of initial angiogenic switching in dysplasias. Thus infiltrating neutrophils can play a crucial role in activating angiogenesis in a previously quiescent tissue vasculature during the early stages of carcinogenesis.

Objectives Non-contrast computed tomography of the brain (NCCTB) is commonly used to detect intracranial pathology but is subject to interpretation errors. Machine learning can augment clinical decision-making and improve NCCTB scan interpretation. This retrospective detection accuracy study assessed the performance of radiologists assisted by a deep learning model and compared the standalone performance of the model with that of unassisted radiologists. Methods A deep learning model was trained on 212,484 NCCTB scans drawn from a private radiology group in Australia. Scans from inpatient, outpatient, and emergency settings were included. Scan inclusion criteria were age ≥ 18 years and series slice thickness ≤ 1.5 mm. Thirty-two radiologists reviewed 2848 scans with and without the assistance of the deep learning system and rated their confidence in the presence of each finding using a 7-point scale. Differences in AUC and Matthews correlation coefficient (MCC) were calculated using a ground-truth gold standard. Results The model demonstrated an average area under the receiver operating characteristic curve (AUC) of 0.93 across 144 NCCTB findings and significantly improved radiologist interpretation performance. Assisted and unassisted radiologists demonstrated an average AUC of 0.79 and 0.73 across 22 grouped parent findings and 0.72 and 0.68 across 189 child findings, respectively. When assisted by the model, radiologist AUC was significantly improved for 91 findings (158 findings were non-inferior), and reading time was significantly reduced. Conclusions The assistance of a comprehensive deep learning model significantly improved radiologist detection accuracy across a wide range of clinical findings and demonstrated the potential to improve NCCTB interpretation. Clinical relevance statement This study evaluated a comprehensive CT brain deep learning model, which performed strongly, improved the performance of radiologists, and reduced interpretation time. The model may reduce errors, improve efficiency, facilitate triage, and better enable the delivery of timely patient care. Key Points • This study demonstrated that the use of a comprehensive deep learning system assisted radiologists in the detection of a wide range of abnormalities on non-contrast brain computed tomography scans. • The deep learning model demonstrated an average area under the receiver operating characteristic curve of 0.93 across 144 findings and significantly improved radiologist interpretation performance. • The assistance of the comprehensive deep learning model significantly reduced the time required for radiologists to interpret computed tomography scans of the brain.

Respiratory syncytial virus (RSV) and influenza are among the most important causes of severe respiratory disease worldwide. Despite the clinical need, barriers to developing reliably effective vaccines against these viruses have remained firmly in place for decades. Overcoming these hurdles requires better understanding of human immunity and the strategies by which these pathogens evade it. Although superficially similar, the virology and host response to RSV and influenza are strikingly distinct. Influenza induces robust strain-specific immunity following natural infection, although protection by current vaccines is short-lived. In contrast, even strain-specific protection is incomplete after RSV and there are currently no licensed RSV vaccines. Although animal models have been critical for developing a fundamental understanding of antiviral immunity, extrapolating to human disease has been problematic. It is only with recent translational advances (such as controlled human infection models and high-dimensional technologies) that the mechanisms responsible for differences in protection against RSV compared to influenza have begun to be elucidated in the human context. Influenza infection elicits high-affinity IgA in the respiratory tract and virus-specific IgG, which correlates with protection. Long-lived influenza-specific T cells have also been shown to ameliorate disease. This robust immunity promotes rapid emergence of antigenic variants leading to immune escape. RSV differs markedly, as reinfection with similar strains occurs despite natural infection inducing high levels of antibody against conserved antigens. The immunomodulatory mechanisms of RSV are thus highly effective in inhibiting long-term protection, with disturbance of type I interferon signaling, antigen presentation and chemokine-induced inflammation possibly all contributing. These lead to widespread effects on adaptive immunity with impaired B cell memory and reduced T cell generation and functionality. Here, we discuss the differences in clinical outcome and immune response following influenza and RSV. Specifically, we focus on differences in their recognition by innate immunity; the strategies used by each virus to evade these early immune responses; and effects across the innate-adaptive interface that may prevent long-lived memory generation. Thus, by comparing these globally important pathogens, we highlight mechanisms by which optimal antiviral immunity may be better induced and discuss the potential for these insights to inform novel vaccines.

In POLLUX, daratumumab (D) plus lenalidomide/dexamethasone (Rd) reduced the risk of disease progression or death by 63% and increased the overall response rate (ORR) versus Rd in relapsed/refractory multiple myeloma (RRMM). Updated efficacy and safety after >3 years of follow-up are presented. Patients (N = 569) with ≥1 prior line received Rd (lenalidomide, 25 mg, on Days 1–21 of each 28-day cycle; dexamethasone, 40 mg, weekly) ± daratumumab at the approved dosing schedule. Minimal residual disease (MRD) was assessed by next-generation sequencing. After 44.3 months median follow-up, D-Rd prolonged progression-free survival (PFS) in the intent-to-treat population (median 44.5 vs 17.5 months; HR, 0.44; 95% CI, 0.35–0.55; P < 0.0001) and in patient subgroups. D-Rd demonstrated higher ORR (92.9 vs 76.4%; P < 0.0001) and deeper responses, including complete response or better (56.6 vs 23.2%; P < 0.0001) and MRD negativity (10–5; 30.4 vs 5.3%; P < 0.0001). Median time to next therapy was prolonged with D-Rd (50.6 vs 23.1 months; HR, 0.39; 95% CI, 0.31–0.50; P < 0.0001). Median PFS on subsequent line of therapy (PFS2) was not reached with D-Rd versus 31.7 months with Rd (HR, 0.53; 95% CI, 0.42–0.68; P < 0.0001). No new safety concerns were reported. These data support using D-Rd in patients with RRMM after first relapse.

Resting and activated subpopulations of CD4 + CD25 + CD127 lo T regulatory cells (Treg) and CD4 + CD25 + CD127 + effector T cells in MS patients and in healthy individuals were compared. Peripheral blood mononuclear cells isolated using Ficoll Hypaque were stained with monoclonal antibodies and analysed by flow cytometer. CD45RA and Foxp3 expression within CD4 + cells and in CD4 + CD25 + CD127 lo T cells identified Population I; CD45RA + Foxp3 + , Population II; CD45RA − Foxp3 hi and Population III; CD45RA − Foxp3 + cells. Effector CD4 + CD127 + T cells were subdivided into Population IV; memory /effector CD45RA − CD25 − Foxp3 − and Population V; effector naïve CD45RA + CD25 − Foxp3 − CCR7 + and terminally differentiated RA + (TEMRA) effector memory cells. Chemokine receptor staining identified CXCR3 + Th1-like Treg, CCR6 + Th17-like Treg and CCR7 + resting Treg. Resting Treg (Population I) were reduced in MS patients, both in untreated and treated MS compared to healthy donors. Activated/memory Treg (Population II) were significantly increased in MS patients compared to healthy donors. Activated effector CD4 + (Population IV) were increased and the naïve/ TEMRA CD4 + (Population V) were decreased in MS compared to HD. Expression of CCR7 was mainly in Population I, whereas expression of CCR6 and CXCR3 was greatest in Populations II and intermediate in Population III. In MS, CCR6 + Treg were lower in Population III. This study found MS is associated with significant shifts in CD4 + T cells subpopulations. MS patients had lower resting CD4 + CD25 + CD45RA + CCR7 + Treg than healthy donors while activated CD4 + CD25 hi CD45RA − Foxp3 hi Treg were increased in MS patients even before treatment. Some MS patients had reduced CCR6 + Th17-like Treg, which may contribute to the activity of MS.

The transmission of tuberculosis is complex. Necessary factors include a source case with respiratory disease that has developed sufficiently for Mycobacterium tuberculosis to be present in the airways. Viable bacilli must then be released as an aerosol via the respiratory tract of the source case. This is presumed to occur predominantly by coughing but may also happen by other means. Airborne bacilli must be capable of surviving in the external environment before inhalation into a new potential host—steps influenced by ambient conditions and crowding and by M. tuberculosis itself. Innate and adaptive host defenses will then influence whether new infection results; a process that is difficult to study owing to a paucity of animal models and an inability to measure infection directly. This review offers an overview of these steps and highlights the many gaps in knowledge that remain.

This study aimed to construct consolidated and updated ultrasonographic fetal biometry and estimated fetal weight (EFW) references for the Hong Kong Chinese population and evaluate the extent of under- and overdiagnosis of small-for-gestational-age (SGA) and large-for-gestational-age (LGA) using these new references. Fetal biometry and EFW references were constructed using the Generalised Additive Model for Location, Scale, and Shape, based on data from 1679 singleton pregnancies in non-smoking Chinese women. Ultrasound scans were performed at 12 to 40 weeks of gestation to measure biparietal diameter, head circumference, abdominal circumference (AC), and femur length, following standardised protocols. The rates of SGA and LGA diagnoses using the existing and updated Hong Kong fetal biometry references were compared in an independent cohort of 10 229 pregnancies. The median number of scans per gestational week between 20 and 39 weeks was 75 (interquartile range=67-83). Compared with existing references, the new AC reference would significantly (P<0.001) increase the proportions of SGA fetuses with AC measurements at <3rd and <10th percentiles from 1.7% and 6.1% to 3.4% and 10.0%, respectively. Conversely, it would significantly decrease (P<0.001) the proportions of LGA fetuses with AC at >90th and >97th percentiles from 15.0% and 4.9% to 11.5% and 3.5%, respectively. Adoption of the new references, particularly for AC, may lead to increased identification of SGA cases and decreased identification of LGA cases. The proportions of these cases will be more consistent with their intended diagnostic thresholds. Further studies are needed to determine how these references impact pregnancy outcomes.

Background Plasmablasts and plasma cells play a key role in many autoimmune diseases, such as rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). This study was undertaken to evaluate the potential of targeting CD38 as a plasma cell/plasmablast depletion mechanism by daratumumab in the treatment of patients with RA and SLE. Methods RNA-sequencing analysis of synovial biopsies from various stages of RA disease progression, flow cytometry analysis of peripheral blood mononuclear cells (PBMC) from patients with RA or SLE and healthy donors, immunohistochemistry assessment (IHC) of synovial biopsies from patients with early RA, and ex vivo immune cell depletion assays using daratumumab (an anti-CD38 monoclonal antibody) were used to assess CD38 as a therapeutic target. Results We demonstrated that the plasma cell/plasmablast-related genes CD38 , XBP1 , IRF4 , PRDM1 , IGJ and TNFSF13B are significantly up-regulated in synovial biopsies from patients with arthralgia, undifferentiated arthritis (UA), early RA and established RA as compared to healthy controls and control patients with osteoarthritis. In addition, the highest CD38 expression was observed on plasma cells and plasmablasts compared to natural killer (NK) cells, classical dendritic cells (DCs), plasmacytoid DCs (pDCs) and T cells, in blood from healthy controls and patients with SLE and RA. Furthermore, IHC showed CD38 staining in the same region as CD3 and CD138 staining in synovial tissue biopsies from patients with early RA. Most importantly, our data show for the first time that daratumumab effectively depletes plasma cells/plasmablasts in PBMC from patients with SLE and RA in a dose-dependent manner ex vivo. Conclusion These results indicate that CD38 may be a potential target for RA disease interception and daratumumab should be evaluated clinically for the treatment of both RA and SLE.

We have previously shown that broadly neutralizing antibodies reactive to the conserved stem region of the influenza virus hemagglutinin (HA) were generated in people infected with the 2009 pandemic H1N1 strain. Such antibodies are rarely seen in humans following infection or vaccination with seasonal influenza virus strains. However, the important question remained whether the inactivated 2009 pandemic H1N1 vaccine, like the infection, could also induce these broadly neutralizing antibodies. To address this question, we analyzed B-cell responses in 24 healthy adults immunized with the pandemic vaccine in 2009. In all cases, we found a rapid, predominantly IgG-producing vaccine-specific plasmablast response. Strikingly, the majority (25 of 28) of HA-specific monoclonal antibodies generated from the vaccine-specific plasmablasts neutralized more than one influenza strain and exhibited high levels of somatic hypermutation, suggesting they were derived from recall of B-cell memory. Indeed, memory B cells that recognized the 2009 pandemic H1N1 HA were detectable before vaccination not only in this cohort but also in samples obtained before the emergence of the pandemic strain. Three antibodies demonstrated extremely broad cross-reactivity and were found to bind the HA stem. Furthermore, one stem-reactive antibody recognized not only H1 and H5, but also H3 influenza viruses. This exceptional cross-reactivity indicates that antibodies capable of neutralizing most influenza subtypes might indeed be elicited by vaccination. The challenge now is to improve upon this result and design influenza vaccines that can elicit these broadly cross-reactive antibodies at sufficiently high levels to provide heterosubtypic protection.