Efficacy of antihypertensive treatment for target organ protection in patients with masked hypertension (ANTI-MASK): a multicentre, double-blind, placebo-controlled trial.

Background: Masked hypertension is associated with target organ damage (TOD) and adverse health outcomes, but whether antihypertensive treatment improves TOD in patients with masked hypertension is unproven. Methods: In this multicentre, randomised, double-blind, placebo-controlled trial at 15 Chinese hospitals, untreated outpatients aged 30-70 years with an office blood pressure (BP) of <140/<90 mm Hg and 24-h, daytime or nighttime ambulatory BP of ≥130/≥80, ≥135/≥85, or ≥120/≥70 mm Hg were enrolled. Patients had ≥1 sign of TOD: electrocardiographic left ventricular hypertrophy (LVH), brachial-ankle pulse wave velocity (baPWV) ≥1400 cm/s, or urinary albumin-to-creatinine ratio (ACR) ≥3.5 mg/mmol in women and ≥2.5 mg/mmol in men. Exclusion criteria included secondary hypertension, diabetic nephropathy, serum creatinine ≥176.8 µmol/L, and cardiovascular disease within 6 months of screening. After stratification for centre, sex and the presence of nighttime hypertension, eligible patients were randomly assigned (1:1) to receive antihypertensive treatment or placebo. Patients and investigators were masked to group assignment. Active treatment consisted of allisartan starting at 80 mg/day, to be increased to 160 mg/day at month 2, and to be combined with amlodipine 2.5 mg/day at month 4, if the ambulatory BP remained uncontrolled. Matching placebos were used likewise in the control group. The primary endpoint was the improvement of TOD, defined as normalisation of baPWV, ACR or LVH or a ≥20% reduction in baPWV or ACR over the 48-week follow-up. The intention-to-treat analysis included all randomised patients, the per-protocol analysis patients who fully adhered to the protocol, and the safety analysis all patients who received at least one dose of the study medication. This study is registered with ClinicalTrials.gov, NCT02893358. Findings: Between February 14, 2017, and October 31, 2020, 320 patients (43.1% women; mean age ± SD 53.7 ± 9.7 years) were enrolled. Baseline office and 24-h BP averaged 130 ± 6.0/81 ± 5.9 mm Hg and 136 ± 8.6/84 ± 6.1 mm Hg, and the prevalence of elevated baPWV, ACR and LVH were 97.5%, 12.5%, and 7.8%, respectively. The 24-h BP decreased on average (±SE) by 10.1 ± 0.9/6.4 ± 0.5 mm Hg in 153 patients on active treatment and by 1.3 ± 0.9/1.0 ± 0.5 mm Hg in 167 patients on placebo. Improvement of TOD occurred in 79 patients randomised to active treatment and in 49 patients on placebo: 51.6% (95% CI 43.7%, 59.5%) versus 29.3% (22.1, 36.5%; p < 0.0001). Per-protocol and subgroup analyses were confirmatory. Adverse events were generally mild and occurred in 38 (25.3%) and 43 (26.4%) patients randomised to active treatment and placebo, respectively (p = 0.83). Interpretation: Our results suggest that antihypertensive treatment improves TOD in patients with masked hypertension, highlighting the need of treatment. However, the long-term benefit in preventing cardiovascular complications still needs to be established. Funding: Salubris China.

Hypertension phenotypes and adverse pregnancy outcome-related office and ambulatory blood pressure thresholds during pregnancy: a retrospective cohort study.

Blood pressure (BP) phenotypes, as determined by the consistency between office BP (OBP) and ambulatory BP (ABP) measurements, enhance risk assessment during pregnancy. However, diagnostic criteria for hypertension in pregnancy are based on data from non-pregnant populations regarding long-term cardiovascular risks. This study aimed to identify adverse pregnancy outcomes (APOs; including maternal/fetal outcomes)-related BP thresholds to refine risk assessment in pregnant women. We analyzed 967 high-risk pregnant women who underwent simultaneous OBP and ABP measurements at an average gestational age of 29.6 ± 8.0 weeks. All hypertension phenotypes were associated with an increased risk of maternal and fetal outcomes, except white coat hypertension, which showed no association with fetal outcomes. Using an XGBoost algorithm, the receiver operating characteristic (ROC) curve-derived daytime diastolic BP (DBP) thresholds of 81.5 mmHg for maternal and 82.5 mmHg for fetal outcomes were identified as the BP parameters most strongly linked to APOs. Incorporating these thresholds into the BP phenotype-based model improved the area under the curve for APOs and the net reclassification index for maternal and fetal outcomes. Decision curve analysis demonstrated a consistent positive net benefit after incorporating BP thresholds into the phenotype-based model for maternal and composite outcomes. In conclusion, in a Chinese pregnancy cohort, we identified daytime DBP as the most influential parameter for APOs, significantly enhancing the predictive performance of BP phenotype-based models. This study underscores the importance of ABP monitoring in high-risk pregnancies and the need for further research to establish optimal BP monitoring criteria for pregnancy.

Deblurring masked image modeling for ultrasound image analysis.

Recently, large pretrained vision foundation models based on masked image modeling (MIM) have attracted unprecedented attention and achieved remarkable performance across various tasks. However, the study of MIM for ultrasound imaging remains relatively unexplored, and most importantly, current MIM approaches fail to account for the gap between natural images and ultrasound, as well as the intrinsic imaging characteristics of the ultrasound modality, such as the high noise-to-signal ratio. In this paper, motivated by the unique high noise-to-signal ratio property in ultrasound, we propose a deblurring MIM approach specialized to ultrasound, which incorporates a deblurring task into the pretraining proxy task. The incorporation of deblurring facilitates the pretraining to better recover the subtle details within ultrasound images that are vital for subsequent downstream analysis. Furthermore, we employ a multi-scale hierarchical encoder to extract both local and global contextual cues for improved performance, especially on pixel-wise tasks such as segmentation. We conduct extensive experiments involving 280,000 ultrasound images for the pretraining and evaluate the downstream transfer performance of the pretrained model on various disease diagnoses (nodule, Hashimoto's thyroiditis) and task types (classification, segmentation). The experimental results demonstrate the efficacy of the proposed deblurring MIM, achieving state-of-the-art performance across a wide range of downstream tasks and datasets. Overall, our work highlights the potential of deblurring MIM for ultrasound image analysis, presenting an ultrasound-specific vision foundation model.

Masked phenomenon: renal and cardiovascular complications; review and updates.

BACKGROUND: In the in-clinic blood pressure (BP) recording setting, a sizable number of individuals with normal BP and approximately 30% of patients with chronic renal disease (CKD) exhibit elevated outpatient BP records. These individuals are known as masked hypertension (MHTN), and when they are on antihypertensive medications, but their BP is not controlled, they are called masked uncontrolled hypertension (MUHTN). The masked phenomenon (MP) (MHTN and MUHTN) increases susceptibility to end-organ damage (a two-fold greater risk for cardiovascular events and kidney dysfunction). The potential extension of the observed benefits of MP therapy, including a reduction in end-organ damage, remains questionable. AIM AND METHODS: This review aims to study the diagnostic methodology, epidemiology, pathophysiology, and significance of MP management in end-organs, especially the kidneys, cardiovascular system, and outcomes. To achieve the purposes of this non-systematic comprehensive review, PubMed, Google, and Google Scholar were searched using keywords, texts, and phrases such as masked phenomenon, CKD and HTN, HTN types, HTN definition, CKD progression, masked HTN, MHTN, masked uncontrolled HTN, CKD onset, and cardiovascular system and MHTN. We restricted the search process to the last ten years to search for the latest updates. CONCLUSION: MHTN is a variant of HTN that can be missed if medical professionals are unaware of it. Early detection by ambulatory or home BP recording in susceptible individuals reduces end-organ damage and progresses to sustained HTN. Adherence to the available recommendations when dealing with masked phenomena is justifiable; however, further studies and recommendation updates are required.

Blood pressure tells us how much force the heart exerts on the blood vessels as it pumps blood. Normal blood pressure should be 120/80 mmHg, which generally decreases when a person is sleeping or sitting. High blood pressure or hypertension occurs when the blood pressure is too high. Hidden or masked hypertension (MH) is a type of high blood pressure. Masked hypertension was described as having high blood pressure readings even though the doctor's office or in-clinic showed normal blood pressure readings.This review aimed to teach people about various kinds of high blood pressure, focusing on hidden (masked) hypertension and how to recognise it, as well as its consequences, treatment, and new information.

Reading language of the eyes in female depression.

Aberrations in non-verbal social cognition have been reported to coincide with major depressive disorder. Yet little is known about the role of the eyes. To fill this gap, the present study explores whether and, if so, how reading language of the eyes is altered in depression. For this purpose, patients and person-by-person matched typically developing individuals were administered the Emotions in Masked Faces task and Reading the Mind in the Eyes Test, modified, both of which contained a comparable amount of visual information available. For achieving group homogeneity, we set a focus on females as major depressive disorder displays a gender-specific profile. The findings show that facial masks selectively affect inferring emotions: recognition of sadness and anger are more heavily compromised in major depressive disorder as compared with typically developing controls, whereas the recognition of fear, happiness, and neutral expressions remains unhindered. Disgust, the forgotten emotion of psychiatry, is the least recognizable emotion in both groups. On the Reading the Mind in the Eyes Test patients exhibit lower accuracy on positive expressions than their typically developing peers, but do not differ on negative items. In both depressive and typically developing individuals, the ability to recognize emotions behind a mask and performance on the Reading the Mind in the Eyes Test are linked to each other in processing speed, but not recognition accuracy. The outcome provides a blueprint for understanding the complexities of reading language of the eyes within and beyond the COVID-19 pandemic.

Instantaneous phase of rhythmic behaviour under volitional control.

The phase of signals representing cyclic behavioural patterns provides valuable information for understanding the mechanisms driving the observed behaviours. Methods usually adopted to estimate the phase, which are based on projecting the signal onto the complex plane, have strict requirements on its frequency content, which limits their application. To overcome these limitations, input signals can be processed using band-pass filters or decomposition techniques. In this paper, we briefly review these approaches and propose a new one. Our approach is based on the principles of Empirical Mode Decomposition (EMD), but unlike EMD, it does not aim to decompose the input signal. This avoids the many problems that can occur when extracting a signal's components one by one. The proposed approach estimates the phase of experimental signals that have one main oscillatory component modulated by slower activity and perturbed by weak, sparse, or random activity at faster time scales. We illustrate how our approach works by estimating the phase dynamics of synthetic signals and real-world signals representing knee angles during flexion/extension activity, heel height during gait, and the activity of different organs involved in speech production.

Neural mechanism underlying preview effects and masked priming effects in visual word processing.

Two classic experimental paradigms - masked repetition priming and the boundary paradigm - have played a pivotal role in understanding the process of visual word recognition. Traditionally, these paradigms have been employed by different communities of researchers, with their own long-standing research traditions. Nevertheless, a review of the literature suggests that the brain-electric correlates of word processing established with both paradigms may show interesting similarities, in particular with regard to the location, timing, and direction of N1 and N250 effects. However, as of yet, no direct comparison has been undertaken between the two paradigms. In the current study, we used combined eye-tracking/EEG to perform such a within-subject comparison using the same materials (single Chinese characters) as stimuli. To facilitate direct comparisons, we used a simplified version of the boundary paradigm - the single word boundary paradigm. Our results show the typical early repetition effects of N1 and N250 for both paradigms. However, repetition effects in N250 (i.e., a reduced negativity following identical-word primes/previews as compared to different-word primes/previews) were larger with the single word boundary paradigm than with masked priming. For N1 effects, repetition effects were similar across the two paradigms, showing a larger N1 after repetitions as compared to alternations. Therefore, the results indicate that at the neural level, a briefly presented and masked foveal prime produces qualitatively similar facilitatory effects on visual word recognition as a parafoveal preview before a single saccade, although such effects appear to be stronger in the latter case.

The Potential of Multi-Screening Methods and Omics Technologies to Detect Both Regulated and Emerging Mycotoxins in Different Matrices.

Mycotoxins are well-known secondary metabolites produced by several fungi that grow and occur in different crops during both pre-harvest and post-harvest conditions. The contamination and occurrence of mycotoxins currently represent some of the major issues in the entire agri-food system. The quantification of mycotoxins in different feeds and foodstuffs is extremely difficult because of the low concentration ranges; therefore, both sample collection and preparation are essential to providing accurate detection and reliable quantification. Currently, several analytical methods are available for the detection of mycotoxins in both feed and food products, and liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) represents the most reliable instrumental approach. In particular, the fast development of high-throughput methods has made it possible to screen and analyze, in the same analytical run and with high accuracy, multiple mycotoxins, such as those regulated, masked, or modified, and emerging ones. Therefore, the aim of this review is to provide an overview of the state of the art of mycotoxins occurrence, health-related concerns, and analyses, discussing the need to perform multi-screening approaches combined with omics technologies to simultaneously analyze several mycotoxins in different feed and food matrices. This approach is expected to provide more comprehensive information about the profile and distribution of emerging mycotoxins, thus enhancing the understanding of their co-occurrence and impact on the entire production chain.

Exercise blood pressure, cardiorespiratory fitness, fatness and cardiovascular risk in children and adolescents.

Cardiovascular disease remains the leading cause of mortality on a global scale. Individuals who possess risk factors for cardiovascular disease, such as high blood pressure (BP) and obesity, face an elevated risk of experiencing organ-specific pathophysiological changes. This damage includes pathophysiological changes in the heart and peripheral vascular systems, such as ventricular hypertrophy, arterial stiffening, and vascular narrowing and stenosis. Consequently, these damages are associated with an increased risk of developing severe cardiovascular outcomes including stroke, myocardial infarction, heart failure, and coronary heart disease. Among all the risk factors associated with cardiovascular disease, high blood pressure emerges as the most prominent. However, conventional resting BP measurement methods such as auscultatory or oscillometric methods may fail to identify many individuals with asymptomatic high BP. Recently, exercise BP has emerged as a valuable diagnostic tool for identifying real (high) blood pressure levels and assessing underlying cardiovascular risk, in addition to resting BP measurements in adults. Furthermore, numerous established factors, such as low cardiorespiratory fitness and high body fatness, have been confirmed to contribute to exercise BP and the associated cardiovascular risk. Modifying these factors may help reduce high exercise BP and, consequently, alleviate the burden of cardiovascular disease. A significant body of evidence has demonstrated cardiovascular disease in later life have their origins in early life. Children and adolescents with these cardiovascular risk factors also possess a greater propensity to develop cardiovascular diseases later in life. Nevertheless, the majority of previous studies on the clinical utility of exercise BP have been conducted in middle-to-older aged populations, often with pre-existing clinical conditions. Therefore, there is a need to investigate further of the factors influencing exercise BP in adolescence and its association with cardiovascular risk in early life. Our previously published work showed that exercise BP is a potential useful method to detect adolescents with increased cardiovascular risk. Children and adolescents with cardiovascular risk factors are more likely to develop cardiovascular diseases later in life. However, previous studies on the clinical utility of exercise BP have largely focused on middle-to-older aged populations with pre-existing clinical conditions. Therefore, there is a need to investigate further the factors influencing exercise BP in adolescence and its association with future cardiovascular risk. Our previous studies, which focused on exercise BP measured at submaximal intensity, have shown that exercise BP is a potentially useful method for identifying adolescents at increased cardiovascular risk. Our previous findings suggest that improving cardio-respiratory fitness and reducing body fatness may help to reduce the risk of developing cardiovascular disease and improve overall cardiovascular health. These findings have important implications for the development of effective prevention and early detection strategies, which can contribute to improved public health outcomes.

Masked Translation Priming Effects for Chinese-English-Japanese Triple Cognates in Lexical Decision Tasks.

Previous research has demonstrated cognate translation priming effects in masked priming lexical decision tasks (LDTs) even when a bilingual's two languages have different scripts. Because those effect sizes are normally larger than with noncognates, the effects have been partially attributed to the impact of prime-target phonological similarity. The present research extended that work by examining priming effects when using triple different-script cognates, i.e., /ka1 feɪ1/-coffee-コーヒー/KoRhiR/. Specifically, masked cognate priming effects were examined in six different priming directions (i.e., L1↔L2, L1↔L3, and L2↔L3) for Chinese-English-Japanese trilinguals using LDTs. Significant priming effects were observed only when the primes were from the stronger language. This asymmetric pattern suggests that the phonological similarity of cognate primes only facilitates the processing of different-script triple cognates to the extent that the processing of the prime is robust enough to make phonology available before target processing is finished.

Rapid identification of medicinal plants via visual feature-based deep learning.

BACKGROUND: Traditional Chinese Medicinal Plants (CMPs) hold a significant and core status for the healthcare system and cultural heritage in China. It has been practiced and refined with a history of exceeding thousands of years for health-protective affection and clinical treatment in China. It plays an indispensable role in the traditional health landscape and modern medical care. It is important to accurately identify CMPs for avoiding the affected clinical safety and medication efficacy by the different processed conditions and cultivation environment confusion. RESULTS: In this study, we utilize a self-developed device to obtain high-resolution data. Furthermore, we constructed a visual multi-varieties CMPs image dataset. Firstly, a random local data enhancement preprocessing method is proposed to enrich the feature representation for imbalanced data by random cropping and random shadowing. Then, a novel hybrid supervised pre-training network is proposed to expand the integration of global features within Masked Autoencoders (MAE) by incorporating a parallel classification branch. It can effectively enhance the feature capture capabilities by integrating global features and local details. Besides, the newly designed losses are proposed to strengthen the training efficiency and improve the learning capacity, based on reconstruction loss and classification loss. CONCLUSIONS: Extensive experiments are performed on our dataset as well as the public dataset. Experimental results demonstrate that our method achieves the best performance among the state-of-the-art methods, highlighting the advantages of efficient implementation of plant technology and having good prospects for real-world applications.

Evaluation of the efficacy and safety of remazolam in tooth extraction surgery: A randomized, single-blind, multi-center clinical trial.

BACKGROUND: Dental extraction or tooth extraction is a common clinical radical treatment surgery. OBJECTIVE: To explore the efficacy and safety of remimazolam in tooth extraction surgery in a randomized, single-blind, multi-center clinical trial. METHOD: Patients who underwent tooth extraction surgery at Jinan Stomatological Hospital from April 2022 to March 2023 were selected as the research subjects, and they were divided into a control group and an observation group using the random arrangement table method. The patients in the control group were anesthetized with midazolam, and the patients in the observation group were anesthetized with remimazolam. Collect the general demographic data of the patients, use the propensity score matching method (PSM) to balance the baseline data of the two groups, and use t-test, chi-square test, and analysis of variance to compare the hemodynamics, anesthesia maintenance period indicators, and alertness/Sedation scores and occurrence of adverse reactions. RESULT: PSM matching was performed according to a 1:1 ratio, and 40 patients were included in the observation and control groups. There was no statistical significance in the baseline data of the two groups. Compared with T0, the hemodynamic indexes of both groups of patients increased at T1, T2, T3, T4, and T5 (P< 0.05), but the indexes at T0 and T2 were the same. The same (P> 0.05), and the indicators of the observation group at T1, T3, T4, and T5 were higher than those of the control group (P< 0.05); the administration time of the two groups of patients was the same (P> 0.05), but the observation group The recovery time and onset of effect were shorter than those in the control group (P< 0.05); at T0, the clinical behavior scores of the two groups of patients were the same (P> 0.05), and at T1, the scores of the observation group were lower than those of the control group (P< 0.05); at T0 and T1, the alertness/sedation scores of the patients in the observation group were lower than those in the control group, but at T2, the scores of the patients in the observation group were higher than those in the control group (P< 0.05); the total clinical adverse reactions of the patients in the observation group were The incidence rate (5.00%) was lower than that of the control group (30.00%) (P< 0.05). CONCLUSION: The use of remimazolam during tooth extraction can stabilize the patient's hemodynamics, shorten the recovery and onset time, stabilize the patient's behavior, have an excellent soothing effect, have fewer adverse reactions, and be safer, so it is worthy of use.

Prevalence of masked hypertension in attended versus unattended office blood pressure measurement.

There is a controversial debate regarding whether unattended blood pressure (BP) measurement should be regarded as the new gold standard of office BP measurement. Unattended BP measurement eliminates the white-coat effect and reduces external influences on the patient. On the other hand, it might underestimate real-life BP. The present study compares the prevalence of masked hypertension using attended versus unattended office BP measurements. We performed a cross-sectional study on 213 patients in a general practitioner's outpatient clinic and compared attended and unattended office BP with 24h-ambulatory BP monitoring (24h-ABPM). Masked hypertension was defined as pressure ≥135/85 mmHg in daytime ABPM with office systolic BP < 140/90 mmHg. Median attended and unattended office BPs were 140/86 and 134/80 mmHg with a median 24h-BP of 129/79 mmHg and daytime ABP of 133/82 mmHg. The number of patients with masked hypertension was 45/213 (21.2%) using unattended and 23/213 (10.8%) using attended office BP measurements (p < .0001). Bland-Altman analysis revealed a 7.4 mmHg systolic and 6.2 mmHg diastolic bias between the attended versus unattended office BP, and two systolic and -1.7 mmHg diastolic biases between the unattended office BP and daytime ambulatory BP. In linear regression analysis, an unattended office BP of 134 mmHg corresponded to 140 mmHg in attended BP measurement. Using a cut-off of 135/85 mmHg instead of 140/90 mmHg in unattended office BP measurement, the rate of masked hypertension was 26/213 (12.2%). Thus, unattended office BP measurement results in a substantial increase in the prevalence of masked hypertension using the traditional definition of hypertension. The present findings suggest that it might be reasonable to use a definition of 135/85 mmHg.

CryoMAE: Few-Shot Cryo-EM Particle Picking with Masked Autoencoders.

Cryo-electron microscopy (cryo-EM) emerges as a pivotal technology for determining the architecture of cells, viruses, and protein assemblies at near-atomic resolution. Traditional particle picking, a key step in cryo-EM, struggles with manual effort and automated methods' sensitivity to low signal-to-noise ratio (SNR) and varied particle orientations. Furthermore, existing neural network (NN)-based approaches often require extensive labeled datasets, limiting their practicality. To overcome these obstacles, we introduce cryoMAE, a novel approach based on few-shot learning that harnesses the capabilities of Masked Autoencoders (MAE) to enable efficient selection of single particles in cryo-EM images. Contrary to conventional NN-based techniques, cryoMAE requires only a minimal set of positive particle images for training yet demonstrates high performance in particle detection. Furthermore, the implementation of a self-cross similarity loss ensures distinct features for particle and background regions, thereby enhancing the discrimination capability of cryoMAE. Experiments on large-scale cryo-EM datasets show that cryoMAE outperforms existing state-of-the-art (SOTA) methods, improving 3D reconstruction resolution by up to 22.4%.

MAN-C: A masked autoencoder neural cryptography based encryption scheme for CT scan images.

Sharing medical images securely is very important towards keeping patients' data confidential. In this paper we propose MAN-C: a Masked Autoencoder Neural Cryptography based encryption scheme for sharing medical images. The proposed technique builds upon recently proposed masked autoencoders. In the original paper, the masked autoencoders are used as scalable self-supervised learners for computer vision which reconstruct portions of originally patched images. Here, the facility to obfuscate portions of input image and the ability to reconstruct original images is used an encryption-decryption scheme. In the final form, masked autoencoders are combined with neural cryptography consisting of a tree parity machine and Shamir Scheme for secret image sharing. The proposed technique MAN-C helps to recover the loss in image due to noise during secret sharing of image.•Uses recently proposed masked autoencoders, originally designed as scalable self-supervised learners for computer vision, in an encryption-decryption setup.•Combines autoencoders with neural cryptography - the advantage our proposed approach offers over existing technique is that (i) Neural cryptography is a new type of public key cryptography that is not based on number theory, requires less computing time and memory and is non-deterministic in nature, (ii) masked auto-encoders provide additional level of obfuscation through their deep learning architecture.•The proposed scheme was evaluated on dataset consisting of CT scans made public by The Cancer Imaging Archive (TCIA). The proposed method produces better RMSE values between the input the encrypted image and comparable correlation values between the input and the output image with respect to the existing techniques.

GMIM: Self-supervised pre-training for 3D medical image segmentation with adaptive and hierarchical masked image modeling.

Self-supervised pre-training and fully supervised fine-tuning paradigms have received much attention to solve the data annotation problem in deep learning fields. Compared with traditional pre-training on large natural image datasets, medical self-supervised learning methods learn rich representations derived from unlabeled data itself thus avoiding the distribution shift between different image domains. However, nowadays state-of-the-art medical pre-training methods were specifically designed for downstream tasks making them less flexible and difficult to apply to new tasks. In this paper, we propose grid mask image modeling, a flexible and general self-supervised method to pre-train medical vision transformers for 3D medical image segmentation. Our goal is to guide networks to learn the correlations between organs and tissues by reconstructing original images based on partial observations. The relationships are consistent within the human body and invariant to disease type or imaging modality. To achieve this, we design a Siamese framework consisting of an online branch and a target branch. An adaptive and hierarchical masking strategy is employed in the online branch to (1) learn the boundaries or small contextual mutation regions within images; (2) to learn high-level semantic representations from deeper layers of the multiscale encoder. In addition, the target branch provides representations for contrastive learning to further reduce representation redundancy. We evaluate our method through segmentation performance on two public datasets. The experimental results demonstrate our method outperforms other self-supervised methods. Codes are available at https://github.com/mobiletomb/Gmim.

Kidney Tumor Classification on CT images using Self-supervised Learning.

One of the most common diseases affecting society around the world is kidney tumor. The risk of kidney disease increases due to reasons such as consumption of ready-made food and bad habits. Early diagnosis of kidney tumors is essential for effective treatment, reducing side effects, and reducing the number of deaths. With the development of computer-aided diagnostic methods, the need for accurate renal tumor classification is also increasing. Because traditional methods based on manual detection are time-consuming, boring, and costly, high-accuracy tests can be performed faster and at a lower cost with deep learning (DL) methods in kidney tumor detection (KTD). Among the current challenges regarding artificial intelligence-assisted KTD, obtaining more precise programming information and the capacity to group with high accuracy make clinical determination more vital and bring it to an important point for current treatment in KTD prediction. This encourages us to propose a more effective DL model that can effectively assist specialist physicians in the diagnosis of kidney tumors. In this way, the workload of radiologists can be alleviated and errors in clinical diagnoses that may occur due to the complex structure of the kidney can be prevented. A large amount of data is needed during the training of the developed methods. Although various studies have been conducted to reduce the amount of data with feature selection techniques, these techniques provide little improvement in the classification accuracy rate. In this paper, a masked autoencoder (MAE) is proposed for KTD, which can produce effective results on datasets containing some samples and can be directly fine-tuned and pre-trained. Self-supervised learning (SSL) is achieved through self-distillation (SD), which can be reintroduced into the configuration loss calculation using masked patches. The SD loss on the decoder and encoder outputs' latent representation is calculated operating SSLSD-KTD. The encoder obtains local attention, while the decoder transfers its global attention to calculate losses. The SSLSD-KTD method reached 98.04 % classification accuracy on the KAUH-kidney dataset, including 8400 samples, and 82.14 % on the CT-kidney dataset, containing 840 samples. By adding more external information to the SSLSD-KTD method with transfer learning, accuracy results of 99.82 % and 95.24 % were obtained on the same datasets. Experimental results have shown that the SSLSD-KTD method can effectively extract kidney tumor features with limited data and can be an aid or even an alternative for radiologists in decision-making in the diagnosis of the disease.

A Conditionally Activated Cytosol-Penetrating Antibody for TME-Dependent Intracellular Cargo Delivery.

Currently, therapeutic and diagnostic applications of antibodies are primarily limited to cell surface-exposed and extracellular proteins. However, research has been conducted on cell-penetrating peptides (CPP), as well as cytosol-penetrating antibodies, to overcome these limitations. In this context, a heparin sulfate proteoglycan (HSPG)-binding antibody was serendipitously discovered, which eventually localizes to the cytosol of target cells. Functional characterization revealed that the tested antibody has beneficial cytosol-penetrating capabilities and can deliver cargo proteins (up to 70 kDa) to the cytosol. To achieve tumor-specific cell targeting and cargo delivery through conditional activation of the cell-penetrating antibody in the tumor microenvironment, a single-chain Fc fragment (scFv) and a VL domain were isolated as masking units. Several in vitro assays demonstrated that fusing the masking protein with a cleavable linker to the cell penetration antibody results in the inactivation of antibody cell binding and internalization. Removal of the mask via MMP-9 protease cleavage, a protease that is frequently overexpressed in the tumor microenvironment (TME), led to complete regeneration of binding and cytosol-penetrating capabilities. Masked and conditionally activated cytosol-penetrating antibodies have the potential to serve as a modular platform for delivering protein cargoes addressing intracellular targets in tumor cells.

Prognostic Effect of Masked Morning Hypertension in Chinese Inpatients With Non-dialysis Chronic Kidney Disease: A Multicenter Retrospective Study.

BACKGROUND: This study aimed to elucidate the prognostic role of Masked Morning Hypertension (MMH) in non-dialysis-dependent chronic kidney disease (NDD-CKD). METHODS: 2,130 NDD-CKD patients of the inpatient department were categorized into four blood pressure (BP) groups: clinical normotension (CH-), clinical hypertension (CH+) with morning hypertension (MH+), and without MH+ (MH-) respectively. The correlation between these four BP types and the primary (all-cause mortality) and secondary endpoints (cardio-cerebrovascular disease [CVD] and end-stage kidney disease [ESKD]) was analyzed. RESULTS: The prevalence of MH and MMH were 47.4% and 14.98%, respectively. Morning hypertension independently increased the risk of all-cause mortality (P = 0.004) and CVD (P < 0.001) but not ESKD (P = 0.092). Masked morning hypertension was associated with heightened all-cause mortality (HR = 4.22, 95% CI = 1.31-13.59; P = 0.02) and CVD events (HR = 5.14, 95% CI = 1.37-19.23; P = 0.02), with no significant association with ESKD (HR = 1.18, 95% CI = 0.65-2.15; P = 0.60). When considering non-CVD deaths as a competing risk factor, a high cumulative incidence of CVD events was observed in the MMH group (HR = 5.16, 95% CI = 1.39-19.08). CONCLUSIONS: MMH is an independent risk factor for all-cause mortality and combined cardiovascular and cerebrovascular events in NDD-CKD patients, underscoring its prognostic significance. This highlights the need for comprehensive management of MH in this population.