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Abstract Colorectal cancer (CRC) ranks as the third most prevalent cancer globally. It’s recognized that the molecular subtype of CRC, characterized by mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H), plays a critical role in determining appropriate treatment strategies. This review examines the current molecular classifications, focusing on dMMR/MSI-H CRC and its subtypes: Lynch syndrome (LS), Lynch-like syndrome (LLS), and sporadic cases. Despite advances in understanding of these genetic backgrounds, clinical trials have not conclusively differentiated the efficacy of immune checkpoint inhibitors among these subgroups. Therefore, while this review details the molecular characteristics and their general implications for treatment and prognosis, it also highlights the limitations and the need for more refined clinical studies to ascertain tailored therapeutic strategies for each subtype. Furthermore, this review summarizes completed and ongoing clinical studies, emphasizing the importance of developing treatments aligned more closely with molecular profiles. By discussing these aspects, the review seeks to provide a comprehensive analysis of oncological characteristics, presenting a detailed understanding of their implications for treatment and prognosis in dMMR/MSI-H CRC.

Abstract In cross-regional cultural interactions, the frequent and controversial practice of cultural borrowing has attracted attention. According to the different relative statuses and comparative directions of the cultural subjects, cultural borrowing can be divided into strong-to-weak (weak-to-strong) cultural borrowing between subjects with strong (weak) status and subjects with weak (strong) status in cultural interactions, as well as equal cultural borrowing between subjects with equal status in cultural interactions. After the concept and types of cultural borrowing are defined, a multisituation experimental method is used to confirm the internal mechanisms and effect boundaries of consumers’ cultural borrowing acceptance. The results of five experiments based on over a thousand subjects indicate that different types of cultural borrowing (strong-to-weak, equal, weak-to-strong) arouse consumers’ perceived cultural threat, thereby reducing their acceptance of cultural borrowing to varying degrees. The influence of different types of cultural borrowing on perceived cultural threat is moderated by the degree of incongruent use and reality of the presentation of the borrowed culture; the influence of perceived cultural threat on cultural borrowing acceptance is moderated by the positioning of the borrowing subjects and the degree of identity in the relationship. By exploring cultural borrowing and consumer acceptance issues in the field of consumption through a series of experiments, this study effectively reveals the differentiated impacts and underlying mechanisms of different types of cultural borrowing on consumers’ acceptance responses.

Abstract Background Many factors contribute to quality of life (QoL) in patients with schizophrenia, yet limited research examined these factors in patients in China. This cross-sectional study explores subjective QoL and its associated factors in patients. Methods The QoL was assessed using the Schizophrenia Quality of Life Scale (SQLS). Clinical symptoms were evaluated using the Brief Psychiatric Rating Scale (BPRS) and seven factors were extracted. Patient Health Questionnaire-9 (PHQ-9), and Generalized Anxiety Disorder Scale (GAD-7) were used to assess depression and anxiety. Cognitive impairment was assessed using the Ascertain Dementia 8 (AD8). The Treatment Emergent Symptom Scale (TESS) and Rating Scale for Extrapyramidal Side Effects (RSESE) were used to evaluate the side effects of medications. Results We recruited 270 patients (male:142,52.6%, mean age:41.9 ± 9.4 years). Positive correlations were observed between SQLS and its subdomains with the total score of BPRS, PHQ-9, GAD-7, AD8, TESS, and RSESE (all P

High Mountain Asia (HMA) shows a remarkable warming tendency and divergent trend of regional precipitation with enhanced meteorological extremes. The rapid thawing of the HMA cryosphere may alter the magnitude and frequency of nature hazards. We reviewed the influence of climate change on various types of nature hazards in HMA region, including their phenomena, mechanisms and impacts. It reveals that: 1) the occurrences of extreme rainfall, heavy snowfall, and drifting snow hazards are escalating; accelerated ice and snow melting have advanced the onset and increased the magnitude of snowmelt floods; 2) due to elevating trigger factors, such as glacier debuttressing and the rapid shift of thermal and hydrological regime of bedrock/snow/ice interface or subsurface, the mass flow hazards including bedrock landslide, snow avalanche, ice-rock avalanches or glacier detachment, and debris flow will become more severe; 3) increased active-layer detachment and retrogressive thaw slumps slope failures, thaw settlement and thermokarst lake will damage many important engineering structures and infrastructure in permafrost region; 4) multi-hazards cascading hazard in HMA, such as the glacial lake outburst flood (GLOF) and avalanche-induced mass flow may greatly enlarge the destructive power of the primary hazard by amplifying its volume, mobility, and impact force; and 5) enhanced slope instability and sediment supply in the highland areas could impose remote catastrophic impacts upon lowland regions, and threat hydropower security and future water shortage. In future, ongoing thawing of HMA will profoundly weaken the multiple-phase material of bedrock, ice, water, and soil, and enhance activities of nature hazards. Compounding and cascading hazards of high magnitude will prevail in HMA. As the glacier runoff overpasses the peak water, low flow or droughts in lowland areas downstream of glacierized mountain regions will became more frequent and severe. Addressing escalating hazards in the HMA region requires tackling scientific challenges, including understanding multiscale evolution and formation mechanism of HMA hazard-prone systems, coupling thermo‒hydro‒mechanical processes in multi-phase flows, predicting catastrophes arising from extreme weather and climate events, and comprehending how highland hazards propagate to lowlands due to climate change.

Abstract Fibroblast growth factor (FGF) signaling encompasses a multitude of functions, including regulation of cell proliferation, differentiation, morphogenesis, and patterning. FGFs and their receptors (FGFR) are crucial for adult tissue repair processes. Aberrant FGF signal transduction is associated with various pathological conditions such as cartilage damage, bone loss, muscle reduction, and other core pathological changes observed in orthopedic degenerative diseases like osteoarthritis (OA), intervertebral disc degeneration (IVDD), osteoporosis (OP), and sarcopenia. In OA and IVDD pathologies specifically, FGF1, FGF2, FGF8, FGF9, FGF18, FGF21, and FGF23 regulate the synthesis, catabolism, and ossification of cartilage tissue. Additionally, the dysregulation of FGFR expression (FGFR1 and FGFR3) promotes the pathological process of cartilage degradation. In OP and sarcopenia, endocrine-derived FGFs (FGF19, FGF21, and FGF23) modulate bone mineral synthesis and decomposition as well as muscle tissues. FGF2 and other FGFs also exert regulatory roles. A growing body of research has focused on understanding the implications of FGF signaling in orthopedic degeneration. Moreover, an increasing number of potential targets within the FGF signaling have been identified, such as FGF9, FGF18, and FGF23. However, it should be noted that most of these discoveries are still in the experimental stage, and further studies are needed before clinical application can be considered. Presently, this review aims to document the association between the FGF signaling pathway and the development and progression of orthopedic diseases. Besides, current therapeutic strategies targeting the FGF signaling pathway to prevent and treat orthopedic degeneration will be evaluated.

Leukoaraiosis (LA) manifests as cerebral white matter hyperintensities on T2-weighted magnetic resonance imaging scans and corresponds to white matter lesions or abnormalities in brain tissue. Clinically, it is generally detected in the early 40s and is highly prevalent globally in individuals aged >60 years. From the imaging perspective, LA can present as several heterogeneous forms, including punctate and patchy lesions in deep or subcortical white matter; lesions with periventricular caps, a pencil-thin lining, and smooth halo; as well as irregular lesions, which are not always benign. Given its potential of having deleterious effects on normal brain function and the resulting increase in public health burden, considerable effort has been focused on investigating the associations between various risk factors and LA risk, and developing its associated clinical interventions. However, study results have been inconsistent, most likely due to potential differences in study designs, neuroimaging methods, and sample sizes as well as the inherent neuroimaging heterogeneity and multi-factorial nature of LA. In this article, we provided an overview of LA and summarized the current knowledge regarding its epidemiology, neuroimaging classification, pathological characteristics, risk factors, and potential intervention strategies.

Objective To investigate the application value of combining the Demirjian’s method with machine learning algorithms for dental age estimation in northern Chinese Han children and adolescents. Methods Oral panoramic images of 10 256 Han individuals aged 5 to 24 years in northern China were collected. The development of eight permanent teeth in the left mandibular was classified into different stages using the Demirjian’s method. Various machine learning algorithms, including support vector regression （SVR）, gradient boosting regression （GBR）, linear regression （LR）, random forest regression （RFR）, and decision tree regression （DTR） were employed. Age estimation models were constructed based on total, female, and male samples respectively using these algorithms. The fitting performance of different machine learning algorithms in these three groups was evaluated. Results SVR demonstrated superior estimation efficiency among all machine learning models in both total and female samples, while GBR showed the best performance in male samples. The mean absolute error （MAE） of the optimal age estimation model was 1.246 3, 1.281 8 and 1.153 8 years in the total, female and male samples, respectively. The optimal age estimation model exhibited varying levels of accuracy across different age ranges, which provided relatively accurate age estimations in individuals under 18 years old. Conclusion The machine learning model developed in this study exhibits good age estimation efficiency in northern Chinese Han children and adolescents. However, its performance is not ideal when applied to adult population. To improve the accuracy in age estimation, the other variables can be considered.

Abstract Meandering flow can be formed during the advance of natural rivers by the scouring of river banks. However, this phenomenon is not common in artificial cement channels. This study used experimental scouring terrain data for a numerical simulation to study the meandering flow pattern formed between double alternating deflectors in a straight channel. The numerical results showed that the path of the accelerated flow generated by the upstream deflector was changed by installing a downstream deflector while the flow rate remained unchanged. Thus, a meandering flow formed, and a stable, narrow, high-speed zone formed in the downstream area. The accelerated flow between the two deflectors hit the channel bank soon after its direction changed. Then, a strong downward flow formed in this area, which may have produced an elliptical scour hole. A large-scale vortex structure was formed in the elliptical scour hole, which was influenced by the horseshoe vortex system before the downstream deflector.

Sex and thyroid hormones are critical for male reproductive health. However, the associations between haloacetic acid (HAA) exposure – a known endocrine disruptor – and sex and thyroid hormones in humans remains unclear. We thus recruited 502 male participants seeking fertility evaluation from a reproductive center. We measured concentrations of sex and thyroid hormones in a single blood sample and dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA) in repeated urine samples. Multivariable linear regression models were constructed to evaluate the associations between HAA concentrations and hormone measurements. After adjusting for potential confounders and urinary creatinine concentrations, urinary concentrations of TCAA were inversely associated with serum levels of sex hormone-binding globulin (SHBG), testosterone (T), T/luteinizing hormone ratio (T/LH), and thyroid stimulating hormone (TSH) (all P for trend

Volatolomics offers an opportunity for noninvasive detection and monitoring of human disease. While gas chromatography-mass spectrometry (GC-MS) remains the technique of choice for analyzing volatile organic compounds (VOCs), barriers to wider adoption in clinical practice still exist, including: sample preparation and introduction techniques, VOC extraction, throughput, volatolome coverage, biological interpretation, and quality control (QC). Therefore, we developed a complete pipeline for untargeted urinary volatolomic profiling. We optimized a novel extraction technique using HiSorb sorptive extraction, which exhibited high analytical performance and throughput. We achieved a broader VOC coverage by using HiSorb coupled with a set of complementary chromatographic methods and time-of-flight mass spectrometry. Furthermore, we developed a data preprocessing strategy by evaluating internal standard normalization, batch correction, and we adopted strict QC measures including removal of nonlinearly responding, irreproducible, or contaminated metabolic features, ensuring the acquisition of high-quality data. The applicability of this pipeline was evaluated in a clinical cohort consisting of pancreatic ductal adenocarcinoma (PDAC) patients (n = 28) and controls (n = 33), identifying four urinary candidate biomarkers (2-pentanone, hexanal, 3-hexanone, and p-cymene), which can successfully discriminate the cancer and noncancer subjects. This study presents an optimized, high-throughput, and quality-controlled pipeline for untargeted urinary volatolomic profiling. Use of the pipeline to discriminate PDAC from control subjects provides proof of principal of its clinical utility and potential for application in future biomarker discovery studies.