Effectiveness of a socioecological model-guided, smart device-based, self-management-oriented lifestyle intervention in community residents: protocol for a cluster-randomized controlled trial.

BACKGROUND: Healthy lifestyles are crucial for preventing chronic diseases. Nonetheless, approximately 90% of Chinese community residents regularly engage in at least one unhealthy lifestyle. Mobile smart devices-based health interventions (mHealth) that incorporate theoretical frameworks regarding behavioral change in interaction with the environment may provide an appealing and cost-effective approach for promoting sustainable adaptations of healthier lifestyles. We designed a randomized controlled trial (RCT) to evaluate the effectiveness of a socioecological model-guided, smart device-based, and self-management-oriented lifestyles (3SLIFE) intervention, to promote healthy lifestyles among Chinese community residents. METHODS: This two-arm, parallel, cluster-RCT with a 6-month intervention and 6-month follow-up period foresees to randomize a total of 20 communities/villages from 4 townships in a 1:1 ratio to either intervention or control. Within these communities, a total of at least 256 community residents will be enrolled. The experimental group will receive a multi-level intervention based on the socioecological model supplemented with a multi-dimensional empowerment approach. The control group will receive information only. The primary outcome is the reduction of modifiable unhealthy lifestyles at six months, including smoking, excess alcohol consumption, physical inactivity, unbalanced diet, and overweight/obesity. A reduction by one unhealthy behavior measured with the Healthy Lifestyle Index Score (HLIS) will be considered favorable. Secondary outcomes include reduction of specific unhealthy lifestyles at 3 months, 9 months, and 12 months, and mental health outcomes such as depression measured with PHQ-9, social outcomes such as social support measured with the modified Multidimensional Scale of Perceived Social Support, clinical outcomes such as obesity, and biomedical outcomes such as the development of gut microbiota. Data will be analyzed with mixed effects generalized linear models with family and link function determined by outcome distribution and accounting for clustering of participants in communities. DISCUSSION: This study will provide evidence concerning the effect of a mHealth intervention that incorporates a behavioral change theoretical framework on cultivating and maintaining healthy lifestyles in community residents. The study will provide insights into research on and application of similar mHealth intervention strategies to promote healthy lifestyles in community populations and settings. TRIAL REGISTRATION NUMBER: ChiCTR2300070575. Date of registration: April 17, 2023. https://www.chictr.org.cn/index.aspx .

Effectiveness of Rehabilitation Interventions in Individuals With Emerging Virtual Respiratory Tract Infectious Disease: A Systematic Review and Meta-Analysis.

OBJECTIVE: Assessing rehabilitation effectiveness for persistent symptoms post-infection with emerging viral respiratory diseases. DATA SOURCES: Systematic review of seven databases (MEDLINE, EMBASE, Cochrane Library, PEDro, MedRxiv, CNKI, Wanfang) until 30 December 2023. REVIEW METHODS: Evaluated 101 studies (9593 participants) on respiratory function, exercise capacity, and quality of life. Methodological quality was assessed using the Cochrane Collaboration's Risk of Bias tool for randomized controlled trials (RCTs), the Newcastle-Ottawa Scale (NOS) for observational studies and non-RCTs, and the NIH Quality Assessment Tools for before-after studies. RESULTS: The most common rehabilitation program combined breathing exercises with aerobic exercise or strength training. Rehabilitation interventions significantly enhanced respiratory function, as evidenced by improvements on the Borg Scale (MD, -1.85; 95% CI, -3.00 to -0.70, low certainty), the mMRC Dyspnea Scale (MD, -0.45; 95% CI, -0.72 to -0.18, low certainty), and the Multidimensional Dyspnoea-12 Scale (MD, -4.64; 95% CI, -6.54 to -2.74, moderate certainty). Exercise capacity also improved, demonstrated by results from the Six-Minute Walk Test (MD, 38.18; 95% CI, 25.33-51.03, moderate certainty) and the Sit-to-Stand Test (MD, 3.04; 95% CI, 1.07-5.01, low certainty). CONCLUSION: Rehabilitation interventions are promising for survivors of viral respiratory diseases, yet gaps in research remain. Future investigations should focus on personalizing rehabilitation efforts, utilizing remote technology-assisted programs, improving research quality, and identifying specific subgroups for customized rehabilitation strategies to achieve the best outcomes for survivors.

A cross-sectional survey on COVID-19 phobia and its influencing factors among undergraduate nursing students.

BACKGROUND: The COVID-19 pandemic has significantly impacted the psychological well-being of undergraduate nursing students in China. It is vital to have an understanding of their COVID-19 phobia and its predictors, especially during transitions in public health policy. OBJECTIVE: This study aims to evaluate the situation and factors contributing to COVID-19 phobia among nursing students in Southwestern China. METHODS: A cross-sectional study was conducted in December 2022 among nursing undergraduates in southwestern China. A convenience sample of 317 undergraduate nursing students from all grades at a medical university in Chengdu was assessed using the COVID-19 Phobia Scale (C19P). RESULTS: The mean COVID-19 Phobia Scale (C19P-SC) score was 52.92 (± 13.02), indicating moderate levels of phobia, with gender, chronic disease, and perceived susceptibility being significant predictors. 11.67% of the students reported an infection history, while 81.39% knew an infected individual. Notably, fourth-year students showed significantly higher phobia level than first-year. Gender, chronic disease, perceived susceptibility, and risk significantly predicted COVID-19 phobia, explaining 16.4% of the variance Results of the thematic analysis revealed four main themes related to COVID-19 phobia and career choice among nursing undergraduates: concerns of infection risk, professional commitment, compromise and acceptance, and confronting phobia. CONCLUSIONS: This study discovered a significant level of COVID-19 phobia among undergraduate nursing students and identified several risk factors, including being female, having chronic diseases, perceiving a high susceptibility to the virus, and perceiving a high level of harm after infection. These findings highlight the importance of educators focusing on the mental well-being of nursing students, particularly seniors, to reduce the impact of phobia on their social interactions and career aspirations. This will help ensure that they are well-prepared for their future roles in healthcare.

First Report of Sclerotinia Rot Caused by Sclerotinia sclerotiorum on Artemisia capillaris in China.

Artemisia capillaris (Asteraceae) is an annual herb found in ˃10 provinces in China. It is cultivated on ˃670 ha, with annual production around 2,500 tons. Its shoot is used in traditional Chinese medicine (Liu et al. 2021). From April to May 2023, Sclerotinia rot symptoms were seen at the Institute of Medicinal Plant Development (40.04°N, 116.28°E), Beijing, China. Disease incidence was up to 10% in the field through investigation of 300 plants. Initial symptoms were irregular tan-brown lesions (0.5 to 5.0 mm) that expended to circumferential necrosis on the roots and basal stem, aerial mycelia and sclerotia were developed on them. The leaves and stem tips were withered and droopy in severe cases. Twelve symptomatic primary roots of 12 plants from two sites were cut into 5 × 5 mm pieces, surface sterilized with 75% ethanol for 30 s and 5% NaClO for 60 s, rinsed with distilled water for three times, dried with sterile filter paper, put on potato dextrose agar (PDA), and incubated at 25°C in the dark for 2 days. Two Sclerotinia-like isolates were obtained using the hyphaltip method. White aerial mycelia were sparse and appressed for isolate YC1-3 and dense for isolate YC1-7. After incubated at 25°C in the dark for 15 days, 10 to 25 sclerotia were developed near the colony margin. Sclerotia of isolate YC1-3 were 1.0 to 3.9 × 1.2 to 4.5 (mean 1.8 × 2.2) mm (n = 60), ovoid or arc-shaped. Sclerotia of isolate YC1-7 were 1.5 to 3.4 × 2.7 to 9.2 (mean 2.3 × 4.3) mm (n = 60), ovoid, dumbbell shaped or curved. The isolates were identified as Sclerotinia sclerotiorum based on morphology (Maas 1998). To further identify the pathogens, molecular identification was performed with isolates YC1-3 and YC1-7. DNA of the two isolates were extracted by the cetyltrimethylammonium bromide (CTAB) method. Polymerase chain reaction was performed with primers ITS1/ITS4 for the internal transcribed spacer (ITS) region (Choi et al. 2020; White et al. 1990) and primers G3PDHfor/G3PDHrev for the glyceraldehyde 3-phosphate dehydrogenase (G3PDH) gene (Garfinkel. 2021). BLAST search analysis revealed that the ITS sequence (GenBank OR229758 and OR229762) was ≥99% similar to S. sclerotiorum (MN099281, MZ379265, KX781301, etc.), and the G3PDH sequence (OR778388 and OR761975) was too (MZ493894, JQ036048, OQ790148, etc.). Phylogenetic trees were computed with ITS and G3PDH sequences using the Maximum Likelihood in MEGA 11. Nine two-month-old seedlings of A. capillaris were used to test pathogenicity. The epidermis layer of each primary root was slightly wounded (2 × 2 mm, 1 mm deep) using a sterile dissecting blade. Three plants were inoculated with mycelial plugs (5 mm in diameter) of YC1-3 and YC1-7 that cultured on PDA for 7 days. Control plants were inoculated with sterile PDA plugs. All seedlings were then incubated at 25oC and 90% relative humidity. After isolate YC1-7 inoculation 3 days and isolate YC1-3 inoculation 5 days, inoculated roots had symptoms like those in the field, controls had no symptoms. S. sclerotiorum was consistently re-isolated from diseased roots, fulfilling Koch's postulates. Diseases caused by S. sclerotiorum have been reported threatens several important economical crops (Marin and Peres 2020; Guan et al. 2022). To our knowledge, this is the first report of S. sclerotiorum causes Sclerotinia rot on A. capillaris. To avoid of significant economic losses, it is urgent to establish an effective disease-management strategy.

Experience of clinical nurses engaged in caring for patients with COVID-19: A qualitative systematic review and meta-synthesis.

AIMS AND OBJECTIVE: This qualitative review summarises and synthesises the available evidence on subjective experiences of clinical nurses who cared for patients with COVID-19. BACKGROUND: Nurses are first responders and play a vital role in emerging infectious disease epidemics such as the COVID-19 pandemic. In this context, they also face many difficulties and challenges related, for example to the imbalance between extensive demands and low control over work tasks. DESIGN AND METHOD: A systematic review of qualitative studies and meta-synthesis focused on the experiences of clinical nurses caring for patients with COVID-19 during the pandemic was carried out. RESULTS: A total of 279 findings were extracted, aggregated into 21 categories and combined into seven synthesised findings, namely (1) professional nursing practice during the pandemic, (2) support systems, (3) somatic sensations and psychological experiences, (4) difficulties and challenges, (5) coping strategies and behaviour, (6) impact on life, profession and values, and (7) needs and expectations for the future. CONCLUSION: Nurses encountered considerable difficulties and challenges in caring for patients with COVID-19. Nurses caring for patients with COVID-19 need more support from organisations, families and society. It is essential to explore positive coping strategies suitable for working in different cultural backgrounds. Policymakers and decision-makers should pay attention to the experiences and voices of nurses. RELEVANCE TO CLINICAL PRACTICE: It is critical for nurse managers to consider how to enhance the support system and help nurses develop adaptive coping strategies in response to COVID-19. Nurses' experiences and voices are valuable in improving health emergency response systems. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution.

Naphthenic Acids Removal from Model Transformer Oil by Diethylamine Modified Resins.

Resins have enormous potential in the removal of naphthenic acids (NAs) from transformer oil due to their rich porosity and high mechanical and diversified functionality, whereas their poor adsorption capacity limits application. In this work, the polystyrene-diethylamine resin (PS-DEA-x) was prepared by grafting diethylamine (DEA) onto chloromethylated polystyrene (PS-Cl) resin to efficiently adsorb cyclopentane carboxylic acid from transformer oil for the first time. The characterization analysis results indicated that amine contents were significantly enhanced with the increase in DEA. Particularly, resin with a molar ratio of 1:5 depending on chloromethyl to DEA (PS-DEA-5) exhibited the highest amine contents and efficient adsorption of cyclopentane carboxylic acid (static adsorption capacity up to 110.0 mg/g), which was about 5 times higher than that of the pristine PS-Cl. The thermodynamic and kinetic studies showed that the adsorption behaviors could be well fitted to the Langmuir isotherm equation and pseudo-second-order rate equation. Moreover, it was found that 1 g of the PS-DEA-5 can decontaminate about 760 mL transformer oil to meet reuse standards by a continuous stream, indicating its potential application in industry.

The spatiotemporal regulations of epicatechin biosynthesis under normal flowering and the continuous inflorescence removal treatment in Fagopyrum dibotrys.

BACKGROUND: Flowering is a critical physiological change that interferes with not only biomass yield but also secondary metabolism, such as the biosynthesis of flavonoids, in rhizome/root plants. The continuous inflorescence removal (CIR) treatment is frequently conducted to weaken this effect. Fagopyrum dibotrys (D.Don) H.Hara (Golden buckwheat) is a kind of rhizome medicinal plant rich in flavonoids and is widely used for the treatment of lung diseases. The CIR treatment is usually conducted in F. dibotrys because of its excessive reproductive growth. To uncover the molecular mechanisms, comprehensive analysis was performed using metabolome and transcriptome data obtained from normally bloomed and the CIR treated plants. RESULTS: Metabolome results demonstrated that in the rhizomes of F. dibotrys, its bioactive compound called epicatechin has higher amount than most of the detected precursors. Compared with the normally bloomed plants, the level of epicatechin in the rhizomes of the CIR group increased by 25% at the withering stage. Based on 96 samples of the control and the CIR groups at 4 flowering stages for 4 tissues, RNA-Seq results revealed a 3 ~ 5 times upregulations of all the key enzyme genes involved in the biosynthesis of epicatechin in both time (from the bud stage to the withering stage) and spatial dimensions (from the top of branch to rhizome) under the CIR treatment compared to normal flowering. Integrated analysis of LC-MS/MS and transcriptome revealed the key roles of several key enzyme genes besides anthocyanidin reductase (ANR). A total of 93 transcription factors were identified to co-expressed with the genes in epicatechin biosynthetic pathway. The flowering activator SQUAMOSA promoter-binding protein like (SPLs) exhibited opposite spatiotemporal expression patterns to that of the epicatechin pathway genes; SPL3 could significantly co-express with all the key enzyme genes rather than the flowering repressor DELLA. Weighted gene co-expression network analysis (WGCNA) further confirmed the correlations among chalcone synthases (CHSs), chalcone isomerases (CHIs), ANRs, SPLs and other transcription factors. CONCLUSIONS: SPL3 might dominantly mediate the effect of normal flowering and the CIR treatment on the biosynthesis of epicatechin in rhizomes mainly through the negative regulations of its key enzyme genes including CHS, CHI and ANR.

Epidemiology of spinal cord injury in China: A systematic review of the chinese and english literature.

STUDY DESIGN: Systematic review. OBJECTIVES: We aimed to provide a comprehensive overview of the English and Chinese literature reporting epidemiological data on spinal cord injury (SCI) in China. METHODS: 3 English and 3 Chinese language electronic databases were searched from the earliest record to 15 March 2020. Sociodemographic characteristics, incidence rates, etiology and lesion characteristics, in-hospital mortality, and secondary health conditions and complications were extracted from included reports. RESULTS: A total of 51 studies were included, 32 in the Chinese language. Forty-seven studies were based on hospital records. Mean age of incident cases ranged from 34 to 55 years and male-to-female ratios ranged from 0.35:1 to 15.3:1. SCI incidence varied from 14.6 to 60.6 per million. Thirty-five studies reported only on traumatic SCI with traffic accidents, high falls, low falls and being hit by objects being the most common causes. Specific causes for non-traumatic SCI were poorly reported. Proportions with tetraplegia and complete injury ranged from 37.4% to 82.0% and 14.1% to 73.9%, respectively. Reported in-hospital mortality attributed to SCI varied from 1.1% to 18.4%. Leading cause of in-hospital mortality for acute SCI was respiratory problems; respiratory problems, urinary tract infections and pressure sores were the most common complications. CONCLUSION: Epidemiological data on SCI in China are only available for a limited number of provinces and mostly outdated. Updated data on incidence with accurate geographical information and etiology across all Chinese provinces are needed for targeted implementation of preventive strategies. Research on community outcomes needs to be developed in China.

Risk Stratification of Early-Stage Cervical Cancer with Intermediate-Risk Factors: Model Development and Validation Based on Machine Learning Algorithm.

BACKGROUND: Adjuvant therapy for patients with cervical cancer (CC) with intermediate-risk factors remains controversial. The objectives of the present study are to assess the prognoses of patients with early-stage CC with pathological intermediate-risk factors and to provide a reference for adjuvant therapy choice. MATERIALS AND METHODS: This retrospective study included 481 patients with stage IB-IIA CC. Cox proportional hazards regression analysis, machine learning (ML) algorithms, Kaplan-Meier analysis, and the area under the receiver operating characteristic curve (AUC) were used to develop and validate prediction models for disease-free survival (DFS) and overall survival (OS). RESULTS: A total of 35 (7.3%) patients experienced recurrence, and 20 (4.2%) patients died. Two prediction models were built for DFS and OS using clinical information, including age, lymphovascular space invasion, stromal invasion, tumor size, and adjuvant treatment. Patients were divided into high-risk or low-risk groups according to the risk score cutoff value. The Kaplan-Meier analysis showed significant differences in DFS (p = .001) and OS (p = .011) between the two risk groups. In the traditional Sedlis criteria groups, there were no significant differences in DFS or OS (p > .05). In the ML-based validation, the best AUCs of DFS at 2 and 5 years were 0.69/0.69, and the best AUCs of OS at 2 and 5 years were 0.88/0.63. CONCLUSION: Two prognostic assessment models were successfully established, and risk grouping stratified the prognostic risk of patients with CC with pathological intermediate-risk factors. Evaluation of long-term survival will be needed to corroborate these findings. IMPLICATIONS FOR PRACTICE: The Sedlis criteria are intermediate-risk factors used to guide postoperative adjuvant treatment in patients with cervical cancer. However, for patients meeting the Sedlis criteria, the choice of adjuvant therapy remains controversial. This study developed two prognostic models based on pathological intermediate-risk factors. According to the risk score obtained by the prediction model, patients can be further divided into groups with high or low risk of recurrence and death. The prognostic models developed in this study can be used in clinical practice to stratify prognostic risk and provide more individualized adjuvant therapy choices to patients with early-stage cervical cancer.

Light scattering pattern specific convolutional network static cytometry for label-free classification of cervical cells.

Cervical cancer is a major gynecological malignant tumor that threatens women's health. Current cytological methods have certain limitations for cervical cancer early screening. Light scattering patterns can reflect small differences in the internal structure of cells. In this study, we develop a light scattering pattern specific convolutional network (LSPS-net) based on deep learning algorithm and integrate it into a 2D light scattering static cytometry for automatic, label-free analysis of single cervical cells. An accuracy rate of 95.46% for the classification of normal cervical cells and cancerous ones (mixed C-33A and CaSki cells) is obtained. When applied for the subtyping of label-free cervical cell lines, we obtain an accuracy rate of 93.31% with our LSPS-net cytometric technique. Furthermore, the three-way classification of the above different types of cells has an overall accuracy rate of 90.90%, and comparisons with other feature descriptors and classification algorithms show the superiority of deep learning for automatic feature extraction. The LSPS-net static cytometry may potentially be used for cervical cancer early screening, which is rapid, automatic and label-free.

Analysis and Optimization for Downlink Cell-Free Massive MIMO System with Mixed DACs.

This paper concentrates on the rate analysis and optimization for a downlink cell-free massive multi-input multi-output (MIMO) system with mixed digital-to-analog converters (DACs), where some of the access points (APs) use perfect-resolution DACs, while the others exploit low-resolution DACs to reduce hardware cost and power consumption. By using the additive quantization noise model (AQNM) and conjugate beamforming receiver, a tight closed-form rate expression is derived based on the standard minimum mean square error (MMSE) channel estimate technique. With the derived result, the effects of the number of APs, the downlink transmitted power, the number of DAC bits, and the proportion of the perfect DACs in the mixed-DAC architecture are conducted. We find that the achievable sum rate can be improved by increasing the proportion of the perfect DACs and deploying more APs. Besides, when the DAC resolution arrives at 5-bit, the system performance will invariably approach the case of perfect DACs, which indicates that we can use 5-bit DACs to substitute the perfect DACs. Thus, it can greatly reduce system hardware cost and power consumption. Finally, the weighted max-min power allocation scheme is proposed to guarantee that the users with high priority have a higher rate, while the others are served with the same rate. The simulation results prove the proposed scheme can be effectively solved by the bisection algorithm.

SERPINA3 Silencing Inhibits the Migration, Invasion, and Liver Metastasis of Colon Cancer Cells.

OBJECTIVE: To investigate the impact of SERPINA3 on the migration, invasion, and liver metastasis of colon cancer cells. METHODS: Immunohistochemical staining was conducted to determine SERPINA3 expression in the cancer and adjacent normal tissues of 131 patients suffering from colon cancer. In vitro experiment, colon cancer cells with low (HT-29P), intermediate (KM-12C), and high (HT-29LMM, KM-12L4) metastatic potential were obtained to examine SERPINA3 expression levels. Besides, quantitative real-time PCR (qRT-PCR) and Western Blot were performed to detect SERPINA3 expression in HT-29LMM and KM-12L4 cells transfected with SERPINA3 siRNA; Wound-healing and Transwell assays to measure cell migration and invasion, respectively; and ELISA to detect MMP-2 and MMP-9 levels. In vivo experiment, mice with liver metastasis of colon cancer were established to observe the effect of SERPINA3 silencing on liver metastasis. Immunohistochemical assay was applied to evaluate the expressions of Serpina3, Mmp-2, Mmp-9, and proliferating cell nuclear antigen (Pcna) in liver metastasis tissues. RESULTS: SERPINA3 in colon cancer tissues was higher than in adjacent normal tissues, which was associated with patients' clinicopathological features. Besides, SERPINA3 expression showed a rising trend in low, intermediate, and high metastatic potential colon cancer cells. After KM-12L4 and HT-29LMM cells transfected with SERPINA3 siRNA, the migration and invasive ability of cells, as well as the expression levels of MMP-2 and MMP-9 were all decreased. Moreover, SERPINA3 siRNA could not only reduce live metastasis of mice, but also down-regulate the expression of Mmp-2 and Mmp-9 in liver metastasis tissues. CONCLUSION: SERPINA3 silencing could inhibit the migration, invasion, and liver metastasis of colon cancer cells.

Activated Yes-Associated Protein Accelerates Cell Cycle, Inhibits Apoptosis, and Delays Senescence in Human Periodontal Ligament Stem Cells.

Objectives: To provide insight into the biological effects of activated Yes-associated protein (YAP) on the proliferation, apoptosis, and senescence of human periodontal ligament stem cells (h-PDLSCs). Methods: h-PDLSCs were isolated by the limiting dilution method, and their surface markers were quantified by flow cytometry. Enhanced green fluorescence protein (EGFP)-labeled lentiviral vector was used to activate YAP in h-PDLSCs, then qRT-PCR and Western blotting were used to evaluate the expression level of YAP. Immunofluorescence was used to detect the location of YAP in h-PDLSCs. The proliferation activity was detected by cell counting kit-8 (CCK-8) and 5-ethynyl-2'-deoxyuridine (EdU), and the cell cycle was determined by flow cytometry. Apoptosis was analyzed by Annexin V-APC staining. Cell senescence was detected by ß-galactosidase staining. Proteins in ERK, Bcl-2, and p53 signaling pathways were detected by Western blotting. Results: h-PDLSCs were isolated successfully and were positive for human mesenchymal stem cell surface markers. After YAP was activated by lentiviral vector, the mRNA and protein of YAP were highly expressed, and more YAP translocated into the nucleus. When YAP was overexpressed in h-PDLSCs, proliferation activity was improved; early and late apoptosis rates decreased (P<0.05); the proportion of cells in G2/M phases increased (P<0.05), while that in G0/G1 phase decreased (P<0.05); cellular senescence was delayed (P<0.01); the expression of P-MEK, P-ERK, P-P90RSK and P-Msk increased, while the expression of Bcl-2 family members (Bak, Bid and Bik) decreased. Conclusions: Activated YAP promotes proliferation, inhibits apoptosis, and delays senescence of h-PDLSCs. The Hippo-YAP signaling pathway can influence ERK and Bcl-2 signaling pathways.

2D light scattering static cytometry for label-free single cell analysis with submicron resolution.

Conventional optical cytometric techniques usually measure fluorescence or scattering signals at fixed angles from flowing cells in a liquid stream. Here we develop a novel cytometer that employs a scanning optical fiber to illuminate single static cells on a glass slide, which requires neither microfluidic fabrication nor flow control. This static cytometric technique measures two dimensional (2D) light scattering patterns via a small numerical aperture (0.25) microscope objective for label-free single cell analysis. Good agreement is obtained between the yeast cell experimental and Mie theory simulated patterns. It is demonstrated that the static cytometer with a microscope objective of a low resolution around 1.30 µm has the potential to perform high resolution analysis on yeast cells with distributed sizes. The capability of the static cytometer for size determination with submicron resolution is validated via measurements on standard microspheres with mean diameters of 3.87 and 4.19 µm. Our 2D light scattering static cytometric technique may provide an easy-to-use, label-free, and flow-free method for single cell diagnostics.

Pattern recognition cytometry for label-free cell classification by 2D light scattering measurements.

We develop a pattern recognition cytometric technique for label-free cell classification. Two dimensional (2D) light scattering patterns from single cells and cell aggregates are obtained with a static cytometer. Good performance of the cytometric setup is verified by comparing yeast cell experimental results with theoretical simulations. Adaptive boosting (AdaBoost) method (a machine learning algorithm) is adopted for the analysis of the 2D light scattering patterns. It is shown that aggregates of three yeast cells can be well differentiated from aggregates of four yeast cells by this pattern recognition cytometric technique. We demonstrate that the pattern recognition cytometry can perform label-free classification of normal cervical cells and HeLa cells with a high accuracy rate.

Lamprey variable lymphocyte receptors mediate complement-dependent cytotoxicity.

An alternative adaptive-immune system is present in the most basal vertebrates--lampreys and hagfish--the only surviving jawless vertebrates. These eel-like fish use leucine-rich repeat-based receptors for Ag recognition instead of the Ig-based receptors used in jawed vertebrates. We report that in Japanese lamprey (Lampetra japonica), variable lymphocyte receptor (VLR)B interacts with C1q and C3 proteins to mediate complement-dependent cytotoxicity for bacteria and tumor cells. The immune-based lysis involves deposition of VLRB and C1q-like protein complex on the surface of target cells, activation of C3, and ultimate disruption of cell wall integrity. The demonstration of functional interaction between VLRB and complement components in lamprey provides evidence for the emergence of cooperative innate and adaptive-immune responses at a pivotal point in vertebrate evolution, before or in parallel with the evolution of Ig-based Abs and the classical complement-activation pathway.

DeepSAP: A Novel Brain Image-Based Deep Learning Model for Predicting Stroke-Associated Pneumonia From Spontaneous Intracerebral Hemorrhage.

RATIONALE AND OBJECTIVE: Stroke-associated pneumonia (SAP) often appears as a complication following intracerebral hemorrhage (ICH), leading to poor prognosis and increased mortality rates. Previous studies have typically developed prediction models based on clinical data alone, without considering that ICH patients often undergo CT scans immediately upon admission. As a result, these models are subjective and lack real-time applicability, with low accuracy that does not meet clinical needs. Therefore, there is an urgent need for a quick and reliable model to timely predict SAP. METHODS: In this retrospective study, we developed an image-based model (DeepSAP) using brain CT scans from 244 ICH patients to classify the presence and severity of SAP. First, DeepSAP employs MRI-template-based image registration technology to eliminate structural differences between samples, achieving statistical quantification and spatial standardization of cerebral hemorrhage. Subsequently, the processed images and filtered clinical data were simultaneously input into a deep-learning neural network for training and analysis. The model was tested on a test set to evaluate diagnostic performance, including accuracy, specificity, and sensitivity. RESULTS: Brain CT scans from 244 ICH patients (mean age, 60.24; 66 female) were divided into a training set (n = 170) and a test set (n = 74). The cohort included 143 SAP patients, accounting for 58.6% of the total, with 66 cases classified as moderate or above, representing 27% of the total. Experimental results showed an AUC of 0.93, an accuracy of 0.84, a sensitivity of 0.79, and a precision of 0.95 for classifying the presence of SAP. In comparison, the model relying solely on clinical data showed an AUC of only 0.76, while the radiomics method had an AUC of 0.74. Additionally, DeepSAP achieved an optimal AUC of 0.84 for the SAP grading task. CONCLUSION: DeepSAP's accuracy in predicting SAP stems from its spatial normalization and statistical quantification of the ICH region. DeepSAP is expected to be an effective tool for predicting and grading SAP in clinic.

Trajectories of cognitive function among people aged 45 years and older living with diabetes in China: Results from a nationally representative longitudinal study (2011~2018).

OBJECTIVES: Diabetes is associated with decline of cognitive function. Exploring different trajectories of cognitive function occurring in people with diabetes is important to improved prognosis. This study aimed to investigate differential patterns of trajectories of cognitive function and baseline determinants of trajectory group membership utilizing data from middle-aged and older Chinese adults with diabetes. METHODS: Participants of the Chinese Health And Retirement Longitudinal Study (CHARLS) aged 45 years and above received biennial assessments between 2011 and 2018. The primary outcome was overall cognitive function score operationalized as sum of mental intactness and episodic memory scores derived from the Telephone Interview of Cognitive Status (TICS). A weighted growth mixture model was used to estimate cognitive function trajectories of CHARLS participants with diabetes, and baseline factors associated with trajectory group membership were investigated with weighted multinomial logistic regression. RESULTS: Data from 1,463 participants with diabetes aged 45 years and above were analyzed, a three-group trajectory model showed the best fit for overall cognitive scores: low baseline, linear declining (22.1%); moderate baseline, linear declining (37.5%) and high-stable (40.3%). Older participants, females, participants with low education, with nighttime sleep <6 h, without daytime napping habits, and with depressive symptoms were at a higher risk of unfavorable cognitive function trajectories. CONCLUSIONS: We identified heterogeneous trajectories of cognitive function among middle-aged and older people living with diabetes in China. Socially vulnerable groups including females, rural residents, and those with low education were at a higher risk for unfavorable trajectories. In health programs aimed at preventing and mitigating cognitive decline in individuals with diabetes more attention should be given to vulnerable groups. Reduced nighttime sleep, lack of daytime napping, and depressive symptoms appear to be modifiable risk factors.

Multiphase comparative study for WHO/ISUP nuclear grading diagnostic model based on enhanced CT images of clear cell renal cell carcinoma.

To compare and analyze the diagnostic value of different enhancement stages in distinguishing low and high nuclear grade clear cell renal cell carcinoma (ccRCC) based on enhanced computed tomography (CT) images by building machine learning classifiers. A total of 51 patients (Dateset1, including 41 low-grade and 10 high-grade) and 27 patients (Independent Dateset2, including 16 low-grade and 11 high-grade) with pathologically proven ccRCC were enrolled in this retrospective study. Radiomic features were extracted from the corticomedullary phase (CMP), nephrographic phase (NP), and excretory phase (EP) CT images, and selected using the recursive feature elimination cross-validation (RFECV) algorithm, the group differences were assessed using T-test and Mann-Whitney U test for continuous variables. The support vector machine (SVM), random forest (RF), XGBoost (XGB), VGG11, ResNet18, and GoogLeNet classifiers are established to distinguish low-grade and high-grade ccRCC. The classifiers based on CT images of NP (Dateset1, RF: AUC = 0.82 ± 0.05, ResNet18: AUC = 0.81 ± 0.02; Dateset2, XGB: AUC = 0.95 ± 0.02, ResNet18: AUC = 0.87 ± 0.07) obtained the best performance and robustness in distinguishing low-grade and high-grade ccRCC, while the EP-based classifier performance in poorer results. The CT images of enhanced phase NP had the best performance in diagnosing low and high nuclear grade ccRCC. Firstorder_Kurtosis and firstorder_90Percentile feature play a vital role in the classification task.

TopMarker: Computational screening biomarkers of hepatocellular carcinoma from transcriptome and interactome based on differential network topological parameters.

Identifying diagnostic biomarkers for cancer is crucial in the field of personalized medicine. The available transcriptome and interactome provide unprecedented opportunities and challenges for biomarker screening. From a systematic perspective, network-based medicine methods provide alternative approaches to organizing the available high-throughput omics data for deciphering molecular interactions and their associations with phenotypic states. In this work, we propose a bioinformatics strategy named TopMarker for discovering diagnostic biomarkers by comparing the network topology differences in control and disease samples. Specifically, we build up gene-gene interaction networks in the two states of control and disease respectively. The network rewiring status across the two networks results in differential network topologies reflecting dynamics and changes in normal samples when compared with those in disease. Thus, we identify the potential biomarker genes with differential network topological parameters between the control and disease gene networks. For a proof-of-concept study, we introduce the computational pipeline of biomarker discovery in hepatocellular carcinoma (HCC). We prove the effectiveness of the proposed TopMarker method using these candidate biomarkers in classifying HCC samples and validate its signature capability across numerous independent datasets. We also compare the discriminant power of biomarker genes identified by TopMarker with those identified by other baseline methods. The higher classification performances and functional implications indicate the advantages of our proposed method for discovering biomarkers from differential network topology.