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Background Major Depressive Disorder (MDD) is a prevalent mental health condition with significant societal impact. Structural magnetic resonance imaging (sMRI) and machine learning have shown promise in psychiatry, offering insights into brain abnormalities in MDD. However, predicting treatment response remains challenging. This study leverages inter-brain similarity from sMRI as a novel feature to enhance prediction accuracy and explore disease mechanisms. The method’s generalizability across adult and adolescent cohorts is also evaluated. Methods The study included 172 participants. Based on remission status, 39 participants from the Hangzhou Dataset and 34 from the Jinan Dataset were selected for further analysis. Three methods were used to extract brain similarity features, followed by a statistical test for feature selection. Six machine learning classifiers were employed to predict treatment response, and their generalizability was tested using the Jinan Dataset. Group analyses between remission and non-remission groups were conducted to identify brain regions associated with treatment response. Results Brain similarity features outperformed traditional metrics in predicting treatment outcomes, with the highest accuracy achieved by the model using these features. Between-group analyses revealed that the remission group had lower gray matter volume and density in the right precentral gyrus, but higher white matter volume (WMV). In the Jinan Dataset, significant differences were observed in the right cerebellum and fusiform gyrus, with higher WMV and density in the remission group. Conclusions This study demonstrates that brain similarity features combined with machine learning can predict treatment response in MDD with moderate success across age groups. These findings emphasize the importance of considering age-related differences in treatment planning to personalize care. Trial registration Clinical trial number: not applicable.

Background Low back pain has become a globally challenging health problem, and about 90% of cases are nonspecific. Due to the risks associated with opioid use and the limited effectiveness of drug treatment, acupuncture and other non-drug methods have become the first-line treatment for this disease. However, the best acupuncture method has not yet been determined. In this study, the effects of different acupuncture methods on chronic nonspecific low back pain (CNLBP) were compared by network meta-analysis, aiming at identifying the best option and providing a basis for precise treatment of CNLBP. Methods Clinical randomized controlled trials (RCTs) on acupuncture in the treatment of NSLBP were searched in eight databases including PubMed, Embase, Cochrane Library, Web of Science, Sinomed, CNKI, Wanfang Data and VIP from the inception of databases to January 21, 2024. The Cochrane risk-of-bias tool 2.0 (RoB 2.0) and Stata 15.0 (Stata Corp, College Station, Texas, USA) were used to evaluate the literature quality and meta-analysis, and the evidence quality was assessed based on GRADE guidelines. This systematic review was registered at the International Prospective Register of Systematic Reviews. Results A total of 27 articles were included, involving 2579 patients. The results of the network meta-analysis showed that the top three treatment schemes were warm needle acupuncture, intensive silver needle therapy and meridian-sinew theory-based treatment. In terms of relieving pain, the top three treatments were electrical warm needling, intensive silver needle therapy and warm needle acupuncture. In improving mobility, the top three were meridian-sinew theory-based treatment, routine acupuncture and electroacupuncture. Conclusion For CNLBP patients, warm needle acupuncture, electrical warm needling and meridian-sinew theory-based treatment are mainly recommended. If patients have significant pain, electroacupuncture is strongly suggested. On the contrary, for patients with decreased joint mobility, meridian-sinew theory-based treatment is advocated.

Molnupiravir is an orally administered prodrug of β‐D‐N4‐hydroxycytidine (NHC) that is conditionally approved in China for the treatment of mild to moderate COVID‐19 in nonhospitalized adults at high risk of disease progression. Molnupiravir is rapidly absorbed and hydrolyzed to deliver NHC into systemic circulation. An open‐label, fixed‐sequence, Phase 1 study was conducted to evaluate the tolerability, safety, and pharmacokinetics (PK) following single and multiple (every 12 h for 5.5 days) oral dosing of molnupiravir 800 mg in 16 healthy, male Chinese participants. After multiple doses of molnupiravir, the median time to maximum concentration was 2.0 h for plasma NHC. NHC concentrations generally decreased in a biphasic manner, with a terminal half‐life of 21.9 h, and NHC exposures (i.e., area under the curve and maximum plasma concentration) were similar following single and multiple doses of molnupiravir. No accumulation of NHC in plasma was observed. When compared with historical data from published clinical trials of similar study design, NHC exposure in Chinese participants was marginally higher than that in non‐Asian participants but remained within established clinical bounds. Overall, molnupiravir was generally well‐tolerated. Ten participants (63.5%) experienced at least one adverse event throughout the study, the severity of which was mild or moderate, and none led to treatment discontinuation. There were no clinically meaningful findings in other safety evaluations. These data support use of the standard 5‐day regimen of molnupiravir 800 mg every 12 h without dose adjustment for the treatment of COVID‐19 in the Chinese population. Study Highlights What is the current knowledge on the topic? ○Molnupiravir is an orally administered prodrug of β‐D‐N4‐hydroxycytidine (NHC) with potent, broad‐spectrum preclinical activity against RNA viruses, including SARS‐CoV‐2, and a high barrier to the development of resistance. ○Molnupiravir is conditionally approved in China for the treatment of mild to moderate COVID‐19 in nonhospitalized adults at high risk of disease progression. ○The safety and pharmacokinetics (PK) of molnupiravir have been extensively studied in clinical trials in which healthy volunteers and patients with COVID‐19 were enrolled. ○Tolerability and PK data in Asian populations are limited. What question did this study address? ○An open‐label, fixed‐sequence, Phase 1 study was conducted to evaluate the tolerability, safety, and PK following single and multiple (every 12 h for 5.5 days) oral dosing of molnupiravir 800 mg in 16 healthy, male Chinese participants. What does this study add to our knowledge? ○Molnupiravir was generally well tolerated in healthy Chinese participants; all adverse events were mild or moderate in severity, and none resulted in treatment discontinuation. ○NHC concentrations generally decreased in a biphasic manner and NHC exposures were similar following single and multiple doses of molnupiravir in healthy Chinese participants; no accumulation of NHC in plasma was observed. ○The NHC exposure observed in Chinese participants was marginally higher than the exposure previously reported in non‐Asian individuals but remained within the established clinical bounds for NHC. How might this change clinical pharmacology or translational science? ○These results support the use of the standard regimen of molnupiravir for the treatment of COVID‐19 (i.e., 800 mg every 12 h for 5 days) in the Chinese population without the need for dose adjustment.

Hepatitis B virus (HBV) is a globally prevalent pathogen that poses significant public health challenges. Active HBV replication can trigger immune responses that result in liver damage. Tuberculosis (TB), caused by ( ), remains one of the leading causes of death from a single infectious agent worldwide. Notably, in TB patients with HBV infection and, the incidence of adverse events is six times higher than in those with TB alone, and HBV infection increases the risk of latent TB. However, the relationship between HBV and TB have not been thoroughly investigated. To elucidate the relationship between HBV and TB, we performed an integrated bioinformatics analysis using expression profiling and RNA sequencing data from the GSE83148 and GSE126614 datasets. We identified differentially expressed genes (DEGs) associated with both diseases and analyzed shared biological pathways, key genes, transcriptional regulatory networks, and gene-disease associations. Furthermore, we predicted potential therapeutic agents targeting these shared molecular features. A total of 35 overlapping DEGs were identified for in-depth analysis. Functional enrichment revealed that these genes are involved in both immune-related pathways and cellular metabolic regulation, underscoring their potential role in the progression of HBV and TB. Protein-protein interaction (PPI) network analysis highlighted four hub genes: CCL2, CD69, EGR2, and CCL20. Additionally, 35 transcription factors (TFs) were predicted to regulate these hub genes. Several candidate drugs, including etoposide, 8-azaguanine, menaquinone, emetine and N-acetyl-L-cysteine, were identified as potential therapeutic options. The DEGs were also significantly associated with other conditions such as pneumonia. This study provides novel insights into the relationship between HBV and TB, offering potential targets for diagnosis and treatment. Our findings may contribute to the development of integrated strategies to manage HBV infection and TB more effectively.

The feline calicivirus, herpesvirus, and panleukopenia viruses are major infections that cause serious diseases in cats; however, current trivalent vaccines have limitations in immune efficacy and their duration of protection. This study assesses the immune-enhancing effects of novel adjuvants (feline IL-15, IL-23, and metabolic modulators) on vaccine responses. Forty mice were randomly assigned to four groups: Group A (composite adjuvants), Group B (metabolic regulatory molecules and Mn adjuvant), Group C1 (Mn adjuvant), and Group C2 (a blank commercial vaccine). The results showed that Group A had significantly higher neutralizing antibody titers against calicivirus post-booster immunization, while both Groups A and B exhibited enhanced antibody responses against the herpesvirus and panleukopenia viruses. Notably, Group A displayed increased proportions of memory T cells, follicular B cells, and activated B cells. These findings suggest that the combination of feline IL-15, IL-23, and metabolic modulators are safe and effective immunoadjuvants for trivalent feline vaccines to promote immune cell differentiation and antibody production, thus representing a promising strategy to optimize vaccine efficacy.

Continued expansion of the power grid and the increasing proportion of wind power centralized integration leads to requirements in sharing both energy and reserves among multiple areas under a hierarchical control structure, which successively requires a correction between schedule plans within multi-time scale. In order to address this problem, this paper develops an information integration method integrating complicated relationships among fuel cost, total thermal power output, reserve capacity, owned reserves and expectations of load shedding and wind curtailment, into three types of time-related relationship curves. Furthermore, a multi-time scale tieline energy and reserves allocation model is proposed, which contains two levels in the control structure, two time scales in dispatch sequence and multiple areas integrated within wind farms as scheduling objects. The efficiency of the proposed method is tested in a 9-bus test system and IEEE 118-bus system. The results show that a cross-regional control center is able to approach the optimal scheduling results of the whole system with the integrated uploaded relationship curves. The proposed model not only relieves energy and reserve shortages in partial areas but also allocates them to more urgent need areas in a high effectivity manner in both day-ahead and intraday time scales.

Antidepressant treatment, as an important method in clinical practice, is not suitable for all major depressive disorder (MDD) patients. Although magnetic resonance imaging (MRI) studies have found thalamic abnormalities in MDD patients, it is not clear whether the features of the thalamus are suitable to serve as predictive aids for treatment responses at the individual level. Here, we tested the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) of the thalamus using multivariate pattern analysis (MVPA). A total of 74 MDD patients and 44 healthy control (HC) subjects were recruited. Thirty-nine MDD patients and 35 HC subjects underwent scanning twice. Between the two scanning sessions, patients in the MDD group received selective serotonin reuptake inhibitor (SSRI) treatment for three-month, and HC group did not receive any treatment. Gaussian process regression (GPR) was trained to predict the percentage decrease in the Hamilton Depression Scale (HAMD) score after treatment. The percentage decrease in HAMD score after SSRI treatment was predicted by building GPRs trained with baseline thalamic data. The results showed significant correlations between the true percentage of HAMD score decreases and predictions (p<0.01, r2=0.11) in GPRs trained with GMD. We did not find significant correlations between the true percentage of HAMD score decreases and predictions in GMV (p=0.16, r2=0.00), ALFF (p=0.125, r2=0.00) and fALFF (p=0.485, r2=0.10). Our results suggest that GMD of the thalamus has good potential as an aid in individualized treatment response predictions of MDD patients.

Heavy hydrocarbons (HHCs) in soils impacted by crude oil spills are generally recalcitrant to biodegradation due to their low bioavailability and complex chemical structure. In this study, soils were pretreated with varying concentrations of ultraviolet radiation A (UVA) or ultraviolet radiation C (UVC) activated titanium dioxide (TiO2) (1%–5%) under varying moisture conditions (0%–300% water holding capacity (WHC)) to enhance biodegradation of HCCs and shorten remediation timeframes. We demonstrate that pretreatment of impacted soils with UVC-activated TiO2 in soil slurries could enhance bioremediation of HHCs. Total petroleum hydrocarbon (TPH) removal after 24 h exposure to UVC (254 nm and 4.8 mW/cm2) was (19.1 ± 1.6)% in slurries with 300% WHC and 5 wt-% TiO2. TPH removal was non-selective in the C15-C36 range and increased with moisture content and TiO2 concentration. In a 10-d bioremediation test, TPH removal in treated soil increased to (26.0 ± 0.9)%, compared to (15.4 ± 0.8)% for controls without photocatalytic pre-treatment. Enhanced biodegradation was also confirmed by respirometry. This suggests that addition of UVC-activated TiO2 to soil slurries can transform recalcitrant hydrocarbons into more bioavailable and biodegradable byproducts and increase the rate of subsequent biodegradation. However, similar results were not observed for soils pretreated with UVA activated TiO2. This suggests that activation of TiO2 by sunlight and direct addition of TiO2 to unsaturated soils within landfarming setting may not be a feasible approach. Nevertheless, less than 1% of UVA (7.5 mW/cm2) or UVC (1.4 mW/cm2) penetrated beyond 0.3 cm soil depth, indicating that limited light penetration through soil would hinder the ability of TiO2 to enhance soil bioremediation under land farming conditions.

Sustainability is an important concern for many countries. Some plans are usually made in advance to guide the sustainable development. Sustainability assessment based on development plans can provide pre-judgment about the sustainability prospect of the evaluated objects. The paper predictively assessed the sustainability of the provincial-level regions in China according to the 14th 5-Year Development Plan. Firstly, the indicator system was constructed based on the indicators given in the development plans. Then, the assessment methods were developed by considering the historical performances and the target values given in development plans simultaneously. A development-oriented sequential relationship analysis weighting method was proposed, which is conducive to the smooth advancement of sustainability construction. The validity of the proposed methods was illustrated by comparison with the mean method. The assessment results show that the sustainability and coordination level of all the provincial-level regions will be improved in 2025. The sustainability performances are most affected by society, followed by economy and environment. It is found that “Number of high-value invention patents per 10,000 population,” “Per capita disposable income increased,” and “Reduction of energy consumption per unit GDP” are the key factors for sustainable development. Based on the findings, valuable suggestions were provided as references.

The revitalization of Northeastern China has been an important topic in China in recent years. Sustainable development of cities plays a strong role in the revitalization process. In this paper, we evaluated the sustainability of the 34 prefecture-level and above cities in Northeastern China. The evaluation process was viewed as a dynamic evaluation problem. A dynamic technique for order preference by similarity to ideal solution (TOPSIS) and entropy method was developed by extending the entropy weight and TOPSIS to dynamic situation. It was found that the sustainability levels of the cities in Northeastern China were comparatively low. Only four sub-provincial cities’ average performances were over 0.5 (accounting for 11.8%). Except for Jixi, nearly all the cities had dim sustainability because of the lower positive or even negative growth rates. In addition to Shenyang, Dalian, Changchun, Harbin, and Daqing, the other cities performed worst in the economic sustainability with performance values below 0.3. This implicates that the necessity and urgency of improving the economic sustainability levels of the cities in Northeastern China to realize the coordinated development of the three dimensions (economy, society and environment). In terms of the cities located in Liaoning province, they need to pay more attention to the economic sustainability, even though their economy basis (or levels) were comparatively better than that in Jilin and Heilongjiang provinces. For the cities in Jilin and Heilongjiang provinces, the decline of their environmental sustainability was serious. This case should arouse the attention of local authorities.