Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

The sensitive scalp is a complex syndrome characterised by abnormal nerve sensations, such as stinging, itching, burning, and tightness, and diminished tolerance to physical or chemical stimuli that would not typically cause such unpleasant responses, with its pathology involving physical barrier destruction at the stratum corneum level, neural hyperreactivity and sensory nerve sensitization, and local immunological dysregulation and chronic low‑grade inflammation. The homeostasis of the scalp microenvironment plays a crucial regulatory role in maintaining the hair follicle growth cycle, yet this “soil” factor has long been underappreciated in hair loss research, which has traditionally centered on intrinsic follicular defects, such as genetic predisposition or androgen-driven mechanisms. In this review, we summarized the potential mechanisms underlying the imbalance in the “barrier-neural-immune” network in sensitive scalps. Sensitive scalp is further manifested as impaired skin barrier, including increased transepidermal water loss and abnormal lipid secretion. These alterations are accompanied by increased surface pH, excessive secretion of sebum rich in free fatty acids, reduced microbial diversity, and dysbiosis characterized by a reduction in Cutibacterium and an increase in Staphylococcus colonization. Mechanistically, we also analyzed how neurogenic inflammation, mediated by substances such as substance P (SP) and calcitonin gene-related peptide (CGRP), along with persistent low-grade inflammation, disrupts the microenvironment of the hair follicle stem cell niche through mechanisms involving mechanosensitive ion channels (e.g., Piezo1), oxidative stress, and cytokine cascades. When the barrier is compromised, the weakened stratum corneum may facilitate the penetration of external stimuli, sensitizing cutaneous nerve endings. Those hyperresponsive nerves then fire off neuropeptides like substance P and CGRP. These peptides activate mast cells and other immune cells via the MrgprB2 receptor, prompting degranulation and a wave of pro-inflammatory mediators that kick off neurogenic inflammation. At the same time, oxidative stress and inflammatory cytokines drive a persistent low-grade inflammation that directly damages the hair follicle stem cell niche. Physical compression from shrinking hair shafts activates Piezo1 channels, setting off calcium influx and Caspase‑3‑dependent apoptotic signaling. We primarily considered the interactions between inflammatory signaling and the sensitization of the androgen receptor (AR) pathway, as well as the inhibition of the Wnt/β‑catenin pathway, which may subsequently contribute to hair follicle miniaturization and disruption of the growth cycle. The inflammatory microenvironment appears to boost AR expression in dermal papilla cells, making them more sensitive to dihydrotestosterone (DHT). This heightened sensitivity may promote the expression of transforming growth factor-β1 (TGF-β1), TGF-β2, and Dickkopf-1 (DKK1), which suppress the Wnt/β‑catenin pathway—essential for follicle growth and regeneration—potentially accelerating follicular miniaturization and stalling the growth cycle. Coupled with direct inflammatory apoptosis, oxidative stress, and circadian disruption, these routes may collectively speed up hair follicle stem cell depletion and diffuse hair thinning. These findings point to the need for more mechanistic and translational research to test the proposed pathways and explore therapies that target the microenvironment in sensitive scalp-related hair loss. Ultimately, we hope to provide theoretical support for the intervention of hair loss by restoring the steady state of the scalp microenvironment and combining with new precision delivery technologies such as microneedles.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

ObjectiveObesity has been identified as one of the most important risk factors for cognitive dysfunction. Physical exercise can ameliorate learning and memory deficits by reversing synaptic plasticity in the hippocampus and cortex in diseases such as Alzheimer’s disease. In this study, we aimed to determine whether 8 weeks of treadmill exercise could alleviate hippocampus-dependent memory impairment in high-fat diet-induced obese mice and investigate the potential mechanisms involved. MethodsA total of sixty 6-week-old male C57BL/6 mice, weighing between 20-30 g, were randomly assigned to 3 distinct groups, each consisting of 20 mice. The groups were designated as follows: control (CON), high-fat diet (HFD), and high-fat diet with exercise (HFD-Ex). Prior to the initiation of the treadmill exercise protocol, the HFD and HFD-Ex groups were fed a high-fat diet (60% fat by kcal) for 20 weeks. The mice in the HFD-Ex group underwent treadmill exercise at a speed of 8 m/min for the first 10 min, followed by 12 m/min for the subsequent 50 min, totally 60 min of exercise at a 0° slope, 5 d per week, for 8 weeks. We employed Y-maze and novel object recognition tests to assess hippocampus-dependent memory and utilized immunofluorescence, Western blot, Golgi staining, and ELISA to analyze axon length, dendritic complexity, number of spines, the expression of c-fos, doublecortin (DCX), postsynaptic density-95 (PSD95), synaptophysin (Syn), interleukin-1β (IL-1β), and the number of major histocompatibility complex II (MHC-II) positive cells. ResultsMice with HFD-induced obesity exhibit hippocampus-dependent memory impairment, and treadmill exercise can prevent memory decline in these mice. The expression of DCX was significantly decreased in the HFD-induced obese mice compared to the control group (P<0.001). Treadmill exercise increased the expression of c-fos (P<0.001) and DCX (P=0.001) in the hippocampus of the HFD-induced obese mice. The axon length (P<0.001), dendritic complexity (P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P<0.001) in the hippocampus were significantly decreased in the HFD-induced obese mice compared to the control group. Treadmill exercise increased the axon length (P=0.002), dendritic complexity(P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P=0.001) of the hippocampus in the HFD-induced obese mice. Our study found a significant increase in MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of HFD-induced obese mice compared to the control group. Treadmill exercise was found to reduce the number of MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of obese mice induced by a HFD. ConclusionTreadmill exercise led to enhanced neurogenesis and neuroplasticity by increasing the axon length, dendritic complexity, dendritic spine numbers, and the expression of PSD95 and DCX, decreasing the number of MHC-II positive cells and neuroinflammation in HFD-induced obese mice. Therefore, we speculate that exercise may serve as a non-pharmacologic method that protects against HFD-induced hippocampus-dependent memory dysfunction by enhancing neuroplasticity and neurogenesis in the hippocampus of obese mice.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

The sternalis muscle is a rare supernumerary muscle representing a normal anatomical variant in the anterior thoracic musculature. Due to wide variation in its morphology and relative unfamiliarity among radiologists, it has been implicated in the misdiagnosis of breast masses on mammography. A 23-year-old male with no significant medical history was referred to our institution for further management of painless bilateral breast enlargement since adolescence. Physical examination revealed breasts of slightly prominent size but there was no palpable breast lump. Mammography work-up found symmetrical, well-defined soft tissue masses projected over the posteromedial aspect of both breasts. Imaging findings were consistent with bilateral sternalis muscles, unusually hypertrophic in size due to intense upper body weight training by the patient. This case highlights the importance of recognizing the usual and unusual presentations of the sternalis muscles on mammography to avoid any unnecessary work-up.