Browse Articles

Behavioral investigation of reactive and neoplastic lymphocytes in human lymph nodes in 4D

This study deals with a 4D investigation of lymphocytes in human tissue under reactive and neoplastic conditions. The immune system’s response to pathogens highly depends on cell interaction and movement, which makes it essential to analyze these dynamics. To achieve this, we observed cells and their movement in 4D. Human lymphoid tissue was examined, including 8 cases with 23 movies of hyperplastic tissue from the pharyngeal tonsil and 12 cases with 35 movies of lymphadenitis. Additionally, there were 4 cases involving 16 movies of marginal zone lymphoma (MZL), 3 cases with 19 movies of nodular lymphocyte predominant Hodgkin lymphoma (NLPHL), 3 cases with 6 movies of follicular lymphoma grade 1/2 (FL), and 2 cases with 10 movies of diffuse large B-cell lymphoma (DLBCL). We tracked the movement, analyzed the activity of B cells and PD1-positive T cells under reactive conditions, and compared the results to different types of lymphomas. In this study, CD20-positive B cells were examined in the context of CD35 staining. CD35 stains follicular dendritic cells (FDC), an indication for a germinal center, so we primarily analyzed B cells in the germinal center areas and partially in the immediate periphery. We categorized cells by defining track types (Low motion cells, Moving and turning in place, Long distance movement) to describe their movement pattern and action types (Passive cells, Interactive cells, Active cells) to describe their behavior and interactions. In neoplastic tissue, slower cellular dynamics and fewer interactions were observed compared to reactive tissue. This indicates differences in cellular behavior between reactive and neoplastic tissues, with a more dynamic cellular environment observed in reactive tissue.

Data-driven identification of key predictors of uncontrolled hypertension: A cross-sectional study

Uncontrolled hypertension (HTN) increases the risk of adverse health events. This study aimed to identify key predictors of uncontrolled HTN in 1,308 Mexican adults with a prior diagnosis of HTN who were undergoing pharmacological treatment. We utilized data from the 2022 National Health and Nutrition Survey and applied data-driven algorithms within an artificial intelligence framework to enhance predictive accuracy and interpretability. Specifically, we integrated Random Forest, XGBoost, LASSO regression, and SHAP analysis. Uncontrolled HTN was defined as systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 80 mmHg based on two readings. We applied LASSO regression to exclude unrelated factors and trained Random Forest and XGBoost algorithms to identify the most important predictors. The key contributors to model accuracy in Random Forest were years since HTN diagnosis (11.9), age (9.4), and source of medical care (4.6), while SHAP analysis in XGBoost further highlighted age (0.115) and source of medical care (0.065) as significant factors. When compared to a traditional logistic regression model, the data-driven approach demonstrated superior predictive performance, with Random Forest achieving an AUC of 0.75 (95% CI 0.72–0.77) versus logistic regression (AUC = 0.61, 95% CI 0.59–0.64). XGBoost exhibited lower predictive capacity (AUC = 0.54, 95% CI 0.49–0.60). These findings underscore the importance of age, duration since diagnosis, and source of medical care in predicting uncontrolled HTN. If replicated, this evidence can inform public health strategies to better target at-risk populations and optimize HTN management through data-driven interventions.

Promoter or inhibitor? The role played by housing prices on entrepreneurial vitality in China

This study delves into the time-varying causal relationship between housing prices (HP) and entrepreneurial vitality (EV) in China, employing a rolling-window sub-sample testing approach. The findings reveal that HP exerts both positive and negative influences on EV across different sub-samples. Specifically, when wealth effects dominate, HP positively impacts EV, acting as a promoter. Conversely, when substitution effects prevail, HP negatively affects EV, becoming an inhibitor. Additionally, EV consistently demonstrates a significant positive impact on HP across various sub-samples, indicating that EV serves as a predictor of HP trends. Given these complex and dynamic interactions, it is crucial for policymakers to carefully consider China’s entrepreneurial environment, financial constraints, and other relevant factors. Tailored policies for HP and EV should be designed based on distinct developmental stages to foster a balanced and sustainable economic environment.

Breast cancer classification based on the integration of diagnostic algorithms for calcifications and masses using a mixture of experts

Purpose To investigate the effectiveness of an integrated deep-learning (DL) algorithm, the Mixture of Radiological Findings Specific Experts (MoRFSE), in breast cancer classification by imitating the diagnostic decision-making process of radiologists. Methods A total of 2,764 mammographic images (1,462 breast cancer, 248 benign lesions, and 1,054 normal breast tissue) from the TOMPEI-CMMD were used. The MoRFSE comprises three DL models: a gate network for categorization (gNet) and two classification expert networks (cExp and mExp) specialized in capturing the distinct characteristics of calcifications and masses, respectively. This structure imitates radiologists’ comprehensive diagnostic process by applying distinct algorithms for different lesion types. The classification performance of MoRFSE was compared with the Conventional ResNet18 model. 5-fold cross-validation was used, and performance was assessed using the area under the receiver operating characteristic curve (AUC). DeLong’s test was performed to evaluate statistical significance. Results MoRFSE achieved a significantly higher AUC (0.9616) compared to Conventional ResNet18 (0.9577, p = 0.001348). Conclusion By integrating specialized algorithms for calcifications and masses, the MoRFSE model effectively emulates radiologists’ diagnostic process. These findings suggest that MoRFSE has the potential to improve the accuracy of breast cancer diagnosis based on mammograms.

Retraction: Analysis of China’s carbon market price fluctuation and international carbon credit financing mechanism using random forest model

Constraining Earth’s core composition from inner core nucleation

Abstract The composition of Earth’s core is a fundamental property of the Earth’s deep interior, defining its present structure and long term thermal and magnetic evolution. However, the composition of the core is not well understood, with several combinations of light elements being able to satisfy the traditional constraints from cosmochemistry, core formation and seismology. The classic view of inner core formation does not include the necessity for liquids to be supercooled to below their melting point before freezing. Attempts to calculate the magnitude of this supercooling have found that several binary core compositions are incompatible with inner core nucleation. Here we show, through molecular dynamics simulations, that nucleation from an Fe 1− x C x =0.1-0.15 composition is compatible with a range of geophysical constraints. Whilst not a complete description of core chemistry, our results demonstrate that inner core nucleation places a strong constraint on the composition of Earth’s core that may allow discrimination between previously identified potential compositions.

Barriers to effective communication among nurses and family members of patients admitted to the intensive care unit at Muhimbili National Hospital in Dar es Salaam: A descriptive qualitative study

Background Effective communication in healthcare is essential for ensuring quality patient care. As healthcare shifts toward family-centered care, nurses are expected to engage families in information sharing and decision-making about their patients. However, barriers to effective communication in intensive care units (ICUs) exist. While global studies have addressed nurse-family communication, most are quantitative and conducted in contexts not similar to Tanzania. This study aimed to qualitatively explore the barriers nurses face in the Tanzanian context when communicating with family members in the ICUs at Muhimbili National Hospital, Dar es Salaam, Tanzania. Methods A descriptive qualitative study was conducted using semi-structured interviews to explore communication barriers. Purposive sampling was used to select fifteen ICU nurses and twelve family members of ICU patients at Muhimbili National Hospital. All interviews were audio-recorded with consent and transcribed verbatim. Data were analyzed thematically following Braun and Clarke’s six-phase framework. Results The study identified two main themes emerging from the interviews: 1) Interpersonal barriers affecting the nurse-family relationship, and 2) Organizational barriers related to the work environment and resource limitations. Conclusion The study highlights that improving communication in ICU settings goes beyond individual efforts; it requires investment in staff training, adequate infrastructure, and a supportive organizational culture. Addressing both interpersonal and organizational barriers through targeted interventions can foster trust, enhance family satisfaction, and contribute to improved patient outcomes in critical care environments.

Engrafted nitrergic neurons derived from hPSCs improve gut dysmotility in mice

Abstract Gastrointestinal (GI) motility disorders represent a major medical challenge, with few effective therapies available. These disorders often result from dysfunction of inhibitory nitric oxide (NO)-producing motor neurons in the enteric nervous system, which are essential for regulating gut motility. Loss or dysfunction of NO neurons is linked to severe conditions, including achalasia, gastroparesis, intestinal pseudo-obstruction and chronic constipation1,2. Here we introduce a platform based on human pluripotent stem cells (hPSCs) for therapeutic development targeting GI motility disorders. Using an unbiased screen, we identified drug candidates that modulate NO neuron activity and enhance motility in mouse colonic tissue ex vivo. We established a high-throughput strategy to define developmental programs driving the specification of NO neurons and found that inhibition of platelet-derived growth factor receptors (PDGFRs) promotes their differentiation from precursors of the enteric nervous system. Transplantation of these neurons into NO-neuron-deficient mice led to robust engraftment and improved GI motility, offering a promising cell-based therapy for neurodegenerative GI disorders. These studies provide a new framework for understanding and treating enteric neuropathies.

Genetic design of soybean hosts and bradyrhizobial endosymbionts reduces N2O emissions from soybean rhizosphere

What the public wants to know about the recycling of contaminated soil

After the Fukushima Daiichi Nuclear Power Plant accident of March 11, 2011, the Japanese government implemented a soil decontamination program as part of disaster area recovery. This resulted in approximately 14 million cubic meters of contaminated soil being stored in an interim facility in Fukushima. Management of the soil has included radioactivity measurement, separation and screening. When recycled the soil may be used in public works projects, but the public objected to soil recycling demonstration projects planned for the Tokyo metropolitan area, and the use of recycled soil in their communities. This study seeks to understand key factors associated with the public’s desire for more information about soil recycling. We conducted a nationwide survey and received 5257 responses from people between the ages of 18 and 89 living in the country’s 47 prefectures and eight geographic regions. The results showed that approximately 60% of residents did not want recycled soil to be relocated near where they live. A large number (75.9%, n = 3991) of respondents had never received information on radiation and its health effects, while 66.1% (3473) of respondents wanted more information about recycled soil. Those who wanted more information about soil recycling prioritized learning of its health effects, effects on food and water, environmental effects, radioactivity levels and monitoring methods, and intergenerational health effects. A binary logistic regression analysis clarified several independent factors related to wanting more information, including interest in the recovery of the area surrounding the FDNPP, receipt of information on radiation and its health effects, and the belief that the FDNPP accident will result in intergenerational health effects. The study results provide a greater understanding of the public’s information needs and can help to improve communication and understanding related to this controversial topic.

Repeated heatwaves can age you as much as smoking or drinking

Identification of Neuritin 1 as a local metabolic regulator of brown adipose tissue

Detection of social anxiety using multiple simultaneous biosignals: A pilot study

Social Anxiety Disorder (SAD) is a prevalent and debilitating condition characterized by heightened anxiety and avoidance behaviors in social situations. Despite the availability of treatment options, remission rates for SAD remain low, highlighting the need for more effective interventions. To support the development of more effective therapies, a better understanding of the psychophysiological mechanisms underlying SAD is needed. This pilot study investigates whether anticipatory anxiety before a social interaction can be detected by multiple biosignals, with the aim of identifying potential biomarkers for SAD. Using a modified version of the Internet-based Stress Test for Social Anxiety Disorder, we measured physiological responses of 17 healthy volunteers, including heart rate, respiratory rate, electrodermal activity, head movements, and electroencephalography power across various frequencies. We found that anticipatory anxiety was associated with increased heart rate, respiratory rate, tonic EDA, and variance in head roll, alongside elevated theta, beta, and gamma power in EEG. Our results suggest that a combination of these biosignals may provide valuable insight into the psychophysiology of social anxiety, which could be useful for both mechanistic research and clinical applications. Future research should explore the role of these signals in clinical populations and during acute threat conditions to refine diagnostic and prognostic tools for SAD.

Auditory and cognitive contributions to recognition of degraded speech in noise: Individual differences among older adults

This study examined individual differences in how older adults with normal hearing (ONH) or hearing impairment (OHI) allocate auditory and cognitive resources during speech recognition in noise at equal recognition. Associations between predictor variables and speech recognition were assessed across three datasets that each included 15–16 conditions involving temporally filtered speech. These datasets involved (1) degraded spectral cues, (2) competing speech-modulated noise, and (3) combined degraded spectral cues in speech-modulated noise. To minimize effects of audibility differences, speech was spectrally shaped according to each listener’s hearing thresholds. The extended Short-Time Objective Intelligibility metric was used to derive psychometric functions that relate the acoustic degradation to speech recognition. From these functions, speech recognition thresholds (SRTs) were determined at 20%, 50%, and 80% recognition. A multiple regression dominance analysis, conducted separately for ONH and OHI groups, determined the relative importance of auditory and cognitive predictor variables to speech recognition. ONH participants had a stronger association of vocabulary knowledge with speech recognition, whereas OHI participants had a stronger association of speech glimpsing abilities with speech recognition. Combined with measures of working memory and hearing thresholds, these predictors accounted for 73% to 89% of the total variance for ONH and OHI, respectively, and generalized to other diverse measures of speech recognition.

Correction: Population genetic diversity and structure of the endangered species Tetracentron sinense Oliver (Tetracentraceae) with SNPs based on RAD sequencing

Orthogonally polarized dual-wavelength Nd:LaMgAl11O19/Nd:SrAl12O19 laser at 1297 and 1306 nm with adjustable ratio of output powers

Using tunable in-band laser diode (LD) pumping (791.1–798.2 nm), an orthogonally polarized dual-wavelength (OPDW) Nd:LaMgAl11O19/Nd:SrAl12O19 (Nd:LMA/Nd:SA) operation at 1297 nm and 1306 nm for the 4F3/2 → 4I13/2 transition is demonstrated for the first time. Optimization of LD temperature and pump focus position enabled efficient generation of both wavelengths at balanced power. The maximum combined continuous-wave (CW) output reached 3.32 W at 1297 nm and 1306 nm with a near 1:1 power ratio. Relative to the absorbed 796.56 nm pump power, the laser achieved maximum total slope efficiency and optical-to-optical conversion efficiency of 20.7% and 18.5%, respectively. This 1297 nm and 1306 nm OPDW source shows significant potential for medical and scientific applications.

Application of Sterile Insect Technique (SIT) for Aedes albopictus (Skuse, 1895) in Sri Lanka: Dose optimization, mating competitiveness and release ratios

Background Sri Lanka has experienced severe dengue epidemics in recent years, despite the extensive vector control measures taken. Therefore, it is necessary to find sustainable vector control strategies against dengue. Novel vector control tools need to be tested for the feasibility of applying them against local vectors. Sterile Insect Technique (SIT) is an increasingly popular vector control technique which has been adopted by many countries to suppress insect pest populations and is being tested for dengue vectors. Methods In this study, SIT was developed for Aedes albopictus (Skuse, 1895), one of the 2 dengue vectors present in Sri Lanka. The optimum radiation dose for sterilizing male pupae (age 24–48 hours) using a Co 60 source was determined based on the post-irradiation pupal and adult survival in males and induced sterility in females at different doses. Further, the effect of irradiation on mating competitiveness of the selected mosquito strain was assessed under laboratory and semi-field conditions. The optimum release ratio of irradiated males to wild males was assessed in laboratory and semi-field settings. Results The optimum radiation dose was 50 Gy among the series of doses (25, 30, 40, 50, 60, and 70 Gy) tested. When pupae were exposed to the optimal radiation dose, 100% pupal survival, 19-day median adult survival time and 99% induced sterility resulted. A 5:1 ratio of irradiated males to non-irradiated laboratory-reared or wild males in laboratory cages resulted in induced sterility of 75% and 62%, respectively. The respective values were 74% and 61% in large semi-field cages. Fried Competitiveness Index (FCI) of irradiated males against wild males of laboratory and wild origin were 0.63 and 0.43 in laboratory cages and 0.57 and 0.55 in large semi-field cages. Conclusion The males of Ae. albopictus irradiated at 50 Gy are adequately sterile and are competitive against the wild males. The release ratio of 5:1 irradiated males to wild males is a suitable ratio for the field application of SIT. The findings of the study will be important for the development of a protocol for future application of SIT for Ae. albopictus in Sri Lanka.

Pig lung transplanted into a person in world first

Hyperspectral anomaly detection leveraging spatial attention and right-shifted spectral energy

In this research, we have proposed a novel anomaly detection algorithm for processing hyperspectral images (HSIs), called the Graph Attention Network–Beta Wavelet Graph Neural Network-based Hyperspectral Anomaly Detection (GAN–BWGNN HAD). This algorithm treats each pixel as a node in a graph, where edges represent pixel correlations and node attributes correspond to spectral features. The algorithm integrates spatial and spectral information, utilizing graph neural networks to identify nonlinear relationships within the image, thereby enhancing anomaly detection precision. The K-nearest neighbor (KNN) algorithm facilitates the creation of edges between pixels, enabling the incorporation of distant pixels and improving resilience to noise and local irregularities. The GAN component incorporates an adaptive attention mechanism to dynamically prioritize relevant spatial features. The BWGNN component employs beta wavelets as a localized bandpass filter, effectively identifying spectral anomalies by addressing the right-shifted spectral energy phenomenon. Furthermore, the utilization of beta wavelets obviates the necessity for computationally intensive Laplacian matrix decompositions, thereby enhancing processing efficiency. This approach effectively integrates spatial and spectral information, providing a more accurate and efficient solution for hyperspectral anomaly detection. Experiments on six real-world hyperspectral datasets and one simulated dataset demonstrate the superior performance of our proposed method. It consistently achieved high Area Under the Curve (AUC) values (e.g., 0.9986 on AVIRIS-II, 0.9961 on abu-beach-2, 0.9982 on abu-urban-3, 0.9999 on Salinas-simulate, 0.9872 on Cri), significantly outperforming state-of-the-art methods. The proposed method also exhibited sub-second detection times (0.20–0.28 s) on most datasets, significantly faster than traditional methods (achieving a speedup of 100 to 500 times) and deep learning models (achieving a speedup of 6 to 8 times).

Effectiveness and user experiences of a valgus brace in patients with knee osteoarthritis: A mixed-method randomised controlled trial

Background Patients with medial compartment knee osteoarthritis (OA) may benefit from wearing a valgus brace, but previous studies lacked consideration for brace wearing time, co-interventions and the brace users’ perceptions. This mixed-method randomised controlled trial investigated the effectiveness of a valgus brace on knee pain and activity limitations alongside exploring user perceptions. Materials and methods Participants randomised to the intervention group (n = 23) received regular care and a customisable valgus brace for 6 months while the participants randomised to the waitlist control group (n = 23) were allowed any regular care treatment except for a knee brace. Outcomes were evaluated with a multilevel linear regression analysis at baseline, 2 weeks, 3 months and 6 months. The primary outcome was knee pain intensity at 6 months measured by a 10-cm Visual Analogue Scale (VAS). Secondary outcomes included walking distance, generic health status, knee functioning and satisfaction with the brace. Qualitative interviews were conducted with a subsample of intervention group participants and transcripts were analysed using deductive thematic analysis. Results After 6 months, only a statistically significant and clinically important difference of 2.13 cm (95% CI −3.57 to −0.69) on the VAS score for knee pain intensity after a walk test was found between the intervention and control groups. Although the qualitative findings echoed some participants’ negative or mixed feelings about the brace, several participants perceived positive changes in pain, other body functions, during activities and had positive user experiences. Conclusion Using a valgus brace decreased knee pain intensity during walking activities. Although other outcomes showed limited effectiveness, the study’s underpowered nature increased the risk of type II errors. Qualitative data highlighted positive user experiences, suggesting potential benefits beyond the measured quantitative outcomes.