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T cells play a key role in cell-mediated immunity, and strategies to genetically modify T cells, including chimeric antigen receptor (CAR) T cell therapy and T cell receptor (TCR) T cell therapy, have achieved substantial advances in the treatment of malignant tumors. In clinical trials, CAR-T cell and TCR-T cell therapies have produced encouraging clinical outcomes, thereby demonstrating their therapeutic potential in mitigating tumor development. This article summarizes the current applications of CAR-T cell and TCR-T cell therapies in clinical trials worldwide. It is predicted that genetically engineered T cell immunotherapies will become safe, well-tolerated, and effective therapeutics and bring hope to cancer patients.

Remote sensing image scene classification is one of the most challenging problems in understanding high-resolution remote sensing images. Deep learning techniques, especially the convolutional neural network (CNN), have improved the performance of remote sensing image scene classification due to the powerful perspective of feature learning and reasoning. However, several fully connected layers are always added to the end of CNN models, which is not efficient in capturing the hierarchical structure of the entities in the images and does not fully consider the spatial information that is important to classification. Fortunately, capsule network (CapsNet), which is a novel network architecture that uses a group of neurons as a capsule or vector to replace the neuron in the traditional neural network and can encode the properties and spatial information of features in an image to achieve equivariance, has become an active area in the classification field in the past two years. Motivated by this idea, this paper proposes an effective remote sensing image scene classification architecture named CNN-CapsNet to make full use of the merits of these two models: CNN and CapsNet. First, a CNN without fully connected layers is used as an initial feature maps extractor. In detail, a pretrained deep CNN model that was fully trained on the ImageNet dataset is selected as a feature extractor in this paper. Then, the initial feature maps are fed into a newly designed CapsNet to obtain the final classification result. The proposed architecture is extensively evaluated on three public challenging benchmark remote sensing image datasets: the UC Merced Land-Use dataset with 21 scene categories, AID dataset with 30 scene categories, and the NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that the proposed method can lead to a competitive classification performance compared with the state-of-the-art methods.

This systematic review and meta-analysis was performed to assess effectiveness of home-based exercise compared with control interventions for functional rehabilitation in elderly patients after hip fracture surgery. Comprehensive literature search was performed on PubMed, EMBASE, Web of Science, Cochrane library, and Clinicaltrails.gov to identify eligible randomized controlled trials (RCTs). Standard mean difference (SMD) and risk ratio (RR) with 95% confidence interval (CI) was calculated. The certainty of evidence of each outcome was assessed by using Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. A total of 28 articles reporting 21 unique RCTs (n = 2470) were finally included. Compared with control interventions, home-based exercise significantly improved Berg balance scale (BBS, SMD = 0.28, 95%CI: 0.03 to 0.53, P = 0.030), timed-up-and-go test (TUG, SMD = -0.28, 95%CI: -0.50 to -0.07, P = 0.009), Short Fort-36 physical component score (SF-36 PCS, SMD = 0.49, 95%CI: 0.28 to 0.70, P<0.001), and knee extensor strength (SMD = 0.23, 95%CI: 0.09 to 0.37, P = 0.001). No significant improvement was observed in gait speed, 6-minute walking test, short physical performance battery performance (SPPB), activities of daily living (ADL), or fear of falling in the home exercise group. Risk of adverse events, including emergency department visits, hospital readmissions, and falls, did not differ between both groups. According to GRADE, the overall certainty of evidence was moderate for usual gait speed, SPPB, ADL, fear of falling, and SF-36 PCS, and was low or very low for the other outcomes. Our meta-analysis demonstrated home-based exercise had positive effect on physical function after hip fracture surgery. Home-based rehabilitation might be recommended for rehabilitation of fractured patients after hospital discharge.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. Renin-angiotensin-aldosterone system (RAAS) inhibitors and sodium-glucose co-transporter 2 (SGLT2) inhibitors have shown efficacy in reducing the risk of ESRD. However, patients vary in their response to RAAS blockades, and the pharmacodynamic responses to SGLT2 inhibitors decline with increasing severity of renal impairment. Thus, effective therapy for DKD is yet unmet. Transforming growth factor-β1 (TGF-β1), expressed by nearly all kidney cell types and infiltrating leukocytes and macrophages, is a pleiotropic cytokine involved in angiogenesis, immunomodulation, and extracellular matrix (ECM) formation. An overactive TGF-β1 signaling pathway has been implicated as a critical profibrotic factor in the progression of chronic kidney disease in human DKD. In animal studies, TGF-β1 neutralizing antibodies and TGF-β1 signaling inhibitors were effective in ameliorating renal fibrosis in DKD. Conversely, a clinical study of TGF-β1 neutralizing antibodies failed to demonstrate renal efficacy in DKD. However, overexpression of latent TGF-β1 led to anti-inflammatory and anti-fibrosis effects in non-DKD. This evidence implied that complete blocking of TGF-β1 signaling abolished its multiple physiological functions, which are highly associated with undesirable adverse events. Ideal strategies for DKD therapy would be either specific and selective inhibition of the profibrotic-related TGF-β1 pathway or blocking conversion of latent TGF-β1 to active TGF-β1.

The triglyceride-glucose (TyG) index and the Atherogenic Index of Plasma (AIP) are both predictors of cardiovascular diseases (CVD). However, their combined and individual contributions to CVD risk are not well understood. This study evaluate the joint and individual associations of the TyG index and AIP with CVD events in middle-aged and older Chinese adults. This nationwide, retrospective cohort study utilized data from CHARLS. The diagnosis of CVD in this study was determined based on self-reported information provided by participants regarding their medical history( heart disease and/or stroke). Cross-sectional analyses in 2011 and longitudinal analyses over a 9-year follow-up were conducted to assess these associations. In the cross-sectional analysis, 8,531 participants were included at baseline. The odds ratio (OR) for TyG alone was 1.06 (95% CI 0.96–1.22) for CVD, while the OR for AIP alone was 1.16 (95% CI 1.02–1.33). Combined analysis showed that compared to the low TyG & low AIP group, the OR for the high TyG & high AIP group was 1.23 (95% CI 1.07–1.42) for CVD. In the survival Analysis, the hazard ratio (HR) for TyG alone was 1.19 (95% CI 1.04–1.35) for CVD, while the HR for AIP alone was 1.25 (95% CI 1.09–1.43). Combined analysis showed that compared to the low TyG & low AIP group, the HR for the high TyG & high AIP group was 1.27 (95% CI 1.10–1.43) for CVD. The findings underscore the significant coexposure effects of the TyG index and AIP on CVD, particularly in middle-aged adults.

Background Previous studies have identified sarcopenia as a significant risk factor for cardiovascular disease (CVD). However, these studies primarily focused on sarcopenia status at baseline, without considering changes in sarcopenia status during follow-up. The aim of this study is to investigate the association between changes in sarcopenia status and the incidence of new-onset cardiovascular disease. Methods This study utilized prospective cohort data from the China Health and Retirement Longitudinal Study (CHARLS). Sarcopenia status was assessed using the 2019 Asian Working Group for Sarcopenia (AWGS) algorithm and categorized as non-sarcopenia, possible sarcopenia, or sarcopenia. Changes in sarcopenia status were evaluated based on assessments at baseline and at the second follow-up survey 2 years later. CVD was identified through self-reported physician diagnoses of heart disease, including angina, myocardial infarction, congestive heart failure, and other heart problems, or stroke. Cox proportional hazards models were employed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for potential confounding factors. Results Based on the inclusion and exclusion criteria, a total of 7499 CHARLS participants were included in the analysis, with 50.8% being female and an average age of 58.5 years. Compared to participants with stable non-sarcopenia status, those who progressed from non-sarcopenia to possible sarcopenia or sarcopenia exhibited a significantly increased risk of new-onset CVD (HR 1.30, 95% CI 1.06–1.59). Conversely, participants who recovered from sarcopenia to non-sarcopenia or possible sarcopenia had a significantly reduced risk of new-onset CVD compared to those with stable sarcopenia status (HR 0.61, 95% CI 0.37–0.99). Among participants with baseline possible sarcopenia, those who recovered to non-sarcopenia had a significantly lower risk of new-onset CVD compared to those with stable possible sarcopenia status (HR 0.67, 95% CI 0.52–0.86). Conclusions Changes in sarcopenia status are associated with varying risks of new-onset CVD. Progression in sarcopenia status increases the risk, while recovery from sarcopenia reduces the risk of developing cardiovascular disease. Graphical Abstract

Background Human papillomavirus (HPV) infection can cause cervical and other cancers, including vulva, vagina, penis, anus, or oropharynx. However, in China's northern Henan Province, data on the prevalence and genotype distribution of HPV among women attending gynecology clinics is limited. This study aimed to investigate the current prevalence and genotype distribution of HPV among women attending gynecology clinics in northern Henan Province. Methods This study included 15,616 women aged 16–81 years old who visited the Xinxiang central hospital's gynecology department between January 2018 and December 2019. HPV DNA was detected by a conventional PCR method followed by HPV type-specific hybridization, which was designed to detect 17 high-risk HPV (HR-HPV) genotypes and 20 low-risk HPV (LR-HPV) genotypes. HPV prevalence and corresponding 95% confidence intervals (95% CI) were calculated using SPSS 18.0. Results The overall HPV prevalence was 19.7% among women in northern Henan Province. Single, double, and multiple HPV infections accounted for 13.7%, 4.3%, and 1.8% of the total cases. Most infections were caused by HR-HPV (71.8%), and single genotype HPV infection (13.7%) was the most common pattern. The most common HR-HPV genotype was HPV16 (4.3%), followed by HPV52 (3.5%) and HPV58 (2.0%). The most common LR-HPV genotype was HPV6 (1.4%), followed by HPV61 (1.1%) and HPV81 (1.1%). Conclusions HPV infection is high among women attending gynecology clinics in northern Henan Province. The highest prevalence was found in women less than 20 years old. In northern Henan Province, the 9-valent HPV vaccine is strongly recommended for regular immunization.

High fluoride concentrations in groundwater represent a substantial global public health concern. In China, over 70 million individuals suffer from drinking water fluorosis. This study reports national surveillance data in 2014 and 2018, dividing affected areas into six regions. The compliance rate for safe fluoride concentrations in drinking water improved by 13.1%. The data revealed a statistically significant difference in fluoride concentration between areas that underwent improvements and those that did not ( Z  = − 10.583, P  < 0.001). The potential health risks for minors were evaluated, with hazard index ( HI ) values for minors exceeding 1, indicating the possibility of non-carcinogenic health risks associated with fluoride exposure. Furthermore, in certain regions, the non-carcinogenic health risks related to the current Chinese national standard for fluoride in drinking water (1.0 mg/L) for infants have surpassed the acceptable threshold. The implementation of improvement initiatives led to a reduction in the non-carcinogenic risk of fluoride exposure for minors, with odds ratios ( 95% CI ) for infants, children, and teens were 0.369 (0.268, 0.509), 0.556 (0.452, 0.683), and 0.823 (0.740, 0.914), respectively. These findings can assist governmental agencies in formulating more effective policies for the protection of minors, particularly infants, from fluoride exposure.

Diabetic kidney disease (DKD) is the most common cause of end-stage renal disease (ESRD) and is associated with increased morbidity and mortality in patients with diabetes. Identification of risk factors involved in the progression of DKD to ESRD is expected to result in early detection and appropriate intervention and improve prognosis. Therefore, this study aimed to establish a risk prediction model for ESRD resulting from DKD in patients with type 2 diabetes mellitus (T2DM). Between January 2008 and July 2019, a total of 390 Chinese patients with T2DM and DKD confirmed by percutaneous renal biopsy were enrolled and followed up for at least 1 year. Four machine learning algorithms (gradient boosting machine, support vector machine, logistic regression, and random forest (RF)) were used to identify the critical clinical and pathological features and to build a risk prediction model for ESRD. There were 158 renal outcome events (ESRD) (40.51%) during the 3-year median follow up. The RF algorithm showed the best performance at predicting progression to ESRD, showing the highest AUC (0.90) and ACC (82.65%). The RF algorithm identified five major factors: Cystatin-C, serum albumin (sAlb), hemoglobin (Hb), 24-hour urine urinary total protein, and estimated glomerular filtration rate. A nomogram according to the aforementioned five predictive factors was constructed to predict the incidence of ESRD. Machine learning algorithms can efficiently predict the incident ESRD in DKD participants. Compared with the previous models, the importance of sAlb and Hb were highlighted in the current model. Highlights What is already known? Identification of risk factors for the progression of DKD to ESRD is expected to improve the prognosis by early detection and appropriate intervention. What this study has found? Machine learning algorithms were used to construct a risk prediction model of ESRD in patients with T2DM and DKD. The major predictive factors were found to be CysC, sAlb, Hb, eGFR, and UTP. What are the implications of the study? In contrast with the treatment of participants with early-phase T2DM with or without mild kidney damage, major emphasis should be placed on indicators of kidney function, nutrition, anemia, and proteinuria for participants with T2DM and advanced DKD to delay ESRD, rather than age, sex, and control of hypertension and glycemia.

Cloud liquid water content (LWC) and droplet effective radius (re) have an important influence on cloud physical processes and optical characteristics. The microphysical properties of a three-layer pure liquid stratus were measured by aircraft probes on 26 April 2014 over a coastal region in Huanghua, China. Vertical variations in aerosol concentration (Na), cloud condensation nuclei (CCN) at supersaturation (SS) 0.3%, cloud LWC and cloud re are examined. Large Na in the size range of 0.1–3 μm and CCN have been found within the planetary boundary layer (PBL) below ~1150 m. However, Na and CCN decrease quickly with height and reach a level similar to that over marine locations. Corresponding to the vertical distributions of aerosols and CCN, the cloud re is quite small (3.0–6 μm) at heights below 1150 m, large (7–13 μm) at high altitudes. In the PBL cloud layer, cloud re and aerosol Na show a negative relationship, while they show a clear positive relationship in the upper layer above PBL with much less aerosol Na. It also shows that the relationship between cloud re and aerosol Na changes from negative to positive when LWC increases. These results imply that the response of cloud re to aerosol Na depends on the combination effects of water-competency and collision-coalescence efficiency among droplets. The vertical structure of aerosol Na and cloud re implies potential cautions for the study of aerosol-cloud interaction using aerosol optical depth for cloud layers above the PBL altitude.